University of Groningen Pharmacotherapy in Frail Elderly

University of Groningen

Pharmacotherapy in frail elderly Dijk, Karen Nanette van

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Pharmacotherapy in frail elderly: Pharmacy data as a tool for improvement

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This research was financially supported by the Scientific Institute Dutch Pharmacists (WINAp). Publication of this thesis was kindly sponsored by the Royal Dutch Association for the Advancement of Pharmacy (KNMP) and the Groningen Universtity Institute for Drug Exploration (GUIDE).

Several sections of this thesis are based on published papers, which are reproduced with p ermission of the co-authors and the publishers. Copyright of these papers remains with the publishers.

Vormgeving en lay-out: Robbin van Nek, Vos & Libert reclame, Leeuwarden Rijksuniversiteit Groningen

Paranimfen: Petra de Boer-Stoter Pharmacotherapy in frail elderly: 4 Karen Cromheecke-Berghuis Pharmacy data as a tool for improvement 5

Proefschrift

ter verkrijging van het doctoraat in de Wiskunde en Natuurwetenschappen aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus, dr. D.F.J. Bosscher, in het openbaar te verdedigen op vrijdag 7 juni 2002 om 14.15 uur

door

Karen Nanette van Dijk geboren op 23 oktober 1966 te ‘s-Gravenhage 6 7 Promotores: Prof. dr. L.T.W. de Jong- van den Berg Rien n’est simple, tout est possible Prof. dr. J.R.B.J. Brouwers

Referent: Dr. C.S. de Vries

Beoordelingscommissie: Prof. dr. A.C.G. Egberts

Prof. dr. F.M. Haaijer-Ruskamp

Prof. dr. J.P.J. Slaets Contents

Page Page

Chapter 1 Scope, objective and setting 11 Chapter 3 Risk assessment studies in the elderly 115

1.1 Scope and objective 13 3.1 Constipation as an adverse effect of drug use in nursing home patients: an overestimated risk 117 8 1.2 Setting 18 9 3.2 Potential interaction between acenoucoumarol and diclofenac, naproxen and ibuprofen and the role of CYP2C9 genotype 133 Chapter 2 Drug utilisation studies in the elderly 23

Part one: nursing home residents Chapter 4 General discussion and perspectives 147

2.1 Background 25

2.2 Use of hospital pharmacy data in pharmaco- Summary 159 epidemiologic research in nursing homes 31

2.3 Drug utilisation in Dutch nursing homes 44 Samenvatting 164

2.4 Occurrence of potential drug-drug interactions in nursing home residents 60 Dankwoord 169

2.5 Prescribing indicators as a tool to evaluate drug use in nursing homes: a pilot study 76 Publications 172

Part two: elderly outpatients Curriculum vitae 173

2.6 Concomitant prescribing of benzodiazepines during antidepressant therapy in the elderly 90

2.7 Prescribing of gastroprotective drugs among elderly NSAID users in the Netherlands 103 Chapter 1 10 11

Scope, objective and setting Outline 1.1 Scope and objective

In this introductory chapter, the objective and contents of the thesis are outlined in section 1.1. Section 1.2 gives an overview of the setting in which the studies presented in this thesis Introduction were carried out. A description is given of both the medical and pharmaceutical setting for ambulatory elderly and nursing home residents aged 65 and over in the Netherlands. Drug utilisation in the elderly has been subject of many studies [1-4]. In the Netherlands, people aged 65 and over comprise about 14% of the Dutch population and account for 40% of 12 the drug prescription costs spent in hospital and community pharmacies [5]. Multiple chronic 13 conditions and the fact that the possibilities for both preventive and therapeutic medical therapies for many diseases have increased in recent years, contribute to the high frequency of drug use in the elderly. The prescribing of a drug to counteract adverse effects of another drug (‘prescribing cascade’) may further increase drug use in the elderly [6]. In view of multiple co-morbidity, changes in drug kinetics and effects and the prescription of several drugs simultaneously (polypharmacy), elderly people are at an increased risk of drug-related problems such as drug-drug interactions, drug-disease interactions and adverse drug reactions (ADRs) [7]. The prevalence of ADRs ranges from 1.5 to 44% in elderly inpatients and from 2.5 to 50.6% in elderly outpatients [8]. Examples of age-related risks of ADRs are bleeding from oral anticoagulants and gastropathy associated with non-steroidal anti-inflammatory drugs [9]. Apart from the risk of overprescribing in this group [6,10], underprescribing of effective agents, such as statins, may also be harmful to the elderly [11-13]. Also, underdiagnosing of certain diagnoses, such as depression, is reported to be an issue in the elderly [14]. Despite the awareness of the problems associated with drug use in the elderly and the attention that has been given to rational prescribing, the frequency of drug-related hospital admissions among elderly people aged 65 and over is still considerable [15-17]. The incidence of drug- related problems is reported to be even higher in nursing home patients, due to the higher levels of drug use and the complexity of the conditions these patients are cared for [18,19]. Physicians are faced with a complex task when prescribing to elderly people [20-22]. Advanced age leads to increased frailty and altered pharmacokinetics and pharmacodynamics with large interindividual variability, often leading to unpredictable drug responses [23]. Elderly people are mostly not included in randomised clinical trials, both because of age and co-morbidity [24], and as a result information on efficacy, optimum drug dosages and toxicity are frequently lacking in this vulnerable age group [25,26]. Also, in daily clinical practice the circumstances, under which drugs are used, especially in the elderly, differ from those in randomised clinical trials. In view of the considerations mentioned above, prescribers need a thorough understanding of the risks, benefits and consequences of drug therapy in the elderly, especially the frail elderly. By studying the uses and effects of drugs in this population in daily outline of the thesis are given. Furthermore, background information is given into the setting clinical practice such insight into these matters can be obtained. In particular in nursing homes, of the studies presented in this thesis. Chapter 2 describes drug use and determinants of drug where frail elderly people reside with often high levels of drug use, and where adverse drug use in nursing home patients and elderly outpatients. A description is given of the pharmacy effects may lead to serious clinical consequences, it is useful to perform pharmacoepidemiolo- prescription data that were collected from 6 nursing homes. These data comprised the main gic studies. In the United States many such studies have been carried out, addressing three dataset used throughout this thesis. Several drug utilisation studies were performed with this main issues: the measurement, determinants, and outcomes of drug use. The structure and dataset. Prescribing indicators were used with the aim to study drug use systematically. organisation of Dutch nursing homes and the type of residents that is cared for, differ conside- Furthermore, using prescription data from the InterAction database, we investigated drug use 14 rably from those in other European countries and the United States [27]. As a consequence, the in elderly outpatients, focusing on psychotropics and non-steroidal anti-inflammatory drugs. 15 concern that has been expressed in the United States regarding the excessive and inapprop- Chapter 3 describes studies that focus on the outcome of drug use in both nursing home riate use of drugs in nursing homes, especially psychotropics [28], cannot automatically be patients and elderly outpatients. In chapter 4, the main findings of the studies are discussed applied to Dutch nursing homes. and suggestions for clinical practice are given. Relatively few drug utilisation studies in Dutch nursing homes have been carried out. Several reasons may account for this fact. First, the medical speciality ‘nursing home medicine’ is the youngest of the 34 medical specialities in the Netherlands and has been acknowledged as an official medical speciality since 1990. In view of this short history, the extent of research in this speciality is relatively small. Second, the nursing home population in the Netherlands mainly consists of frail elderly patients. In this group ethical aspects, although this is not typically a Dutch issue, therefore may play a role. Ethical and practical questions arise when the value of certain medical interventions is assessed, such as the withdrawal of benzodiazepines. Furthermore, studies on clinical relevant outcomes are often lacking due to ethical considerations. A third reason why studies on drug use in Dutch nursing homes have not been performed more extensively, is that until the 1990s medication use on individual patient level was only registered in the medical chart and not in pharmacy computer systems. Only in the last decade, medication registration on individual patient level in computerised systems is more common. Performing pharmacoepidemiologic studies, which often requires large datasets, has therefore not been feasible until recent years.

Objective and outline of the thesis

The objective of this thesis is to provide insight in drug use, determinants of drug use and outcomes of drug use in the elderly and in particular in the frail elderly that reside in Dutch nursing homes. The studies that provide this information may lead to a better understanding of the risks of drug use in the (institutionalised) elderly and may serve as a starting point to improve prescribing practices. Furthermore, the results of these investigations may provide the tool for monitoring individual patients at risk for drug-related problems. In chapter 1 the objective and 27 Ribbe MW. Care for the elderly: the role of the nursing home in the Dutch health care system. Int Psychogeriatr References 1993; 5: 213-22. 28 Beers MH, Ouslander JG, Fingold SF, Morgenstern H, Reuben DB, Rogers W et al. Inappropriate medication pre- 1 Heerdink ER. Clustering of drug use in the elderly: population-based studies into prevalence and outcomes scribing in skilled-nursing facilities. Ann Intern Med 1992; 151: 1825-31. [Thesis]. University of Utrecht, 1995. 2 Lau HS. Drug related problems in the elderly: studies on occurrence and interventions [Thesis]. University of Utrecht, 1998. 3 Veehof LJG. Polypharmacy in the elderly [Thesis]. University of Groningen, 1999. 4 Avorn J. Gurwitz JH. Drug use in the nursing home. Ann Intern Med 1995; 123: 195-204. 5 Tinke JL. Farmacie in cijfers (SFK): Geneesmiddelgebruik door ouderen. Pharm Weekbl 2001; 136: 589. 16 6 Rochon PA, Gurwitz JH. Optimising drug treatment for elderly people: the prescribing cascade. 17 BMJ 1997; 315: 1096-9. 7 Van den Bemt PMLA, Egberts ACG, De Jong-van den Berg LTW, Brouwers JRBJ. Drug related problems in hospitalised patients: a review. Drug Saf 2000; 22: 321-33. 8 Hanlon JT, Maher RL, Lindblad CI, Ruby CM, Twersky J, Cohen HJ, Schmader KE. Comparison of methods for detecting potential adverse drug events in frail elderly inpatients and outpatients. Am J Health-Syst Pharm 2001; 58: 1622-6. 9 Beyth RJ, Shorr RI. Epidemiology of adverse drug reactions in the elderly by drug class. Drugs Aging 1999; 14: 231-9. 10 Gurwitz JH, Avorn J. The ambiguous relation between aging and adverse drug reactions. Ann Intern Med 1991; 114: 956-66. 11 Rochon PA, Gurwitz JH. Prescribing for seniors. Neither too much, nor too little. JAMA 1999; 282: 113-5. 12 Redelmeier DA, Tan SH, Booth GL. The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med 1998; 338: 1516-20. 13 Avorn J. Improving drug use in elderly patients: getting to the next level. JAMA 2001; 22: 2866-8. 14 NIH Consensus Conference. Diagnosis and treatment of depression in late life. JAMA 1992; 268: 1018-24. 15 Atkin PA, Veitch PC, Veitch EM, Ogle SJ. The epidemiology of serious adverse drug reactions among the elderly. Drugs Aging 1999; 14: 141-52. 16 Van Kraaij DJW, Haagsma CJ, Go IH, Gribnau FWJ. Drug use and adverse drug reactions in 105 elderly patients admitted to a general medical ward. Neth J Med 1994; 44: 166-73. 17 Bero LA, Lipton HL, Bird JA. Characterization of geriatric drug-related hospital readmissions. Med Care 1991; 29: 989-1003. 18 Seppälä M, Sourander L. A practical guide to prescribing in nursing homes. Avoiding the pitfalls. Drugs Aging 1995; 6: 426-35. 19 Monette J, Gurwitz JH, Avorn J. Epidemiology of adverse drug events in the nursing home setting. Drugs Aging 1995; 7: 203-11. 20 Beers MH, Ouslander JG. Risk factors in geriatric drug prescribing. A practical guide to avoid problems. Drugs 1989; 37: 105-112. 21 Hughes SG. Prescribing for the elderly: why do we need to exercise caution? Br J Clin Pharmacol 1998; 46: 531-3. 22 Denham MJ, Barnett NL. Drug therapy and the older person. Role of the pharmacist. Drug Saf 1998; 19: 243-50. 23 Kinirons MT, Crome P. Clinical pharmacokinetic considerations in the elderly. An update. Clin Pharmacokinet 1997; 33: 302-12. 24 Zhan C, Sangl J, Bierman AS, Miller MR, Friedman B, Wickizer SW, Meyer GS. Potentially inappropriate medication use in the community-dwelling elderly. JAMA 2001; 22: 2823-9. 25 Turnheim K. Drug dosage in the elderly. Is it rational? Drugs Aging 1998; 13: 357-79 26 Avorn J. Including elderly people in clinical trials. BMJ 1997; 315: 1033-4. 1.2 Setting made services for elderly people in need of continuous medical care, such as a daily need of dressing renewals or continuous pain relief. When the need for medical care becomes such that people cannot live totally in their own home anymore, admission into residential homes or Ambulatory elderly nursing homes is possible on strict medical indication and depending on the amount of care needed. Regional pre-selection boards carry out assessment of eligibility for care in nursing The Dutch health care system is geared to facilitate elderly people (aged 65 and older) to homes and residential homes. However, no measuring instrument has been able to assess the live at home for as long and as independently as possible. Eighty-two percent of the people need for care objectively and in a standardised way that is universally applicable [6]. 18 aged 65 and over live independently in the community [1]. Most people have healthcare insu- 19 rance, which covers the costs of primary care and medication as well as the costs of in-hospi- Institutionalised elderly tal and outpatient treatment. In addition, every Dutch citizen is insured under the Exceptional Medical Expenses Act (AWBZ). This act provides the general public with insurance for health In the Netherlands, of the people aged 65 and over 5.5% live in residential homes and risks not covered by normal healthcare insurance, such as admission to nursing homes and 2.7% live in nursing homes [1]. Residential homes offer board, lodging and care to elderly who residential homes and the costs of home care (e.g. meals-on-wheels and household help) [1]. are no longer able to cope on their own. These homes do not offer nursing. Medical care is pro- General medical care is provided through general practitioners and pharmacies providing pri- vided by the residents’ general practitioner and medication is provided by the residents’ com- mary care services. In the Netherlands, more than 90% of healthcare problems are dealt with munity pharmacy. There are 1425 residential homes in the Netherlands, with a total of 117,500 in primary care. General practitioners can refer patients to 143 hospitals (with almost 60,000 beds (55 per 1000 inhabitants aged 65 and over) [1]. The Dutch nursing home is a healthcare beds). Every academic hospital and each large teaching hospital (approximately 17 in total) has institution for chronically ill persons in need of permanent medical and paramedical attention a specialised geriatric department, together with clinical geriatric teaching and research facili- and complex nursing care and is compared to skilled nursing facilities in the US [1]. The type of ties [1]. In other non-teaching hospitals separate ‘Geriatrische Afdeling Algemeen Ziekenhuis’ care can be characterised as continuous, long-term, systematic and multidisciplinary [7]. (GAAZ)-departments are present, providing medical care for geriatric patients. Several features make them different from nursing homes in other countries. First, clear crite- In recent years, several initiatives have been issued towards improvements in quality of life ria based on medical diagnoses, activities of daily living, behavioural characteristics and men- of elderly people. Increasingly, attention has been given to quality of drug use. In Dutch com- tal functioning for nursing home admission exist. On the basis of these criteria, a distinction is munity pharmacies, pharmaceutical care is gradually implemented in daily community practi- made between eligibility for admission and whether people should be admitted to either a ce [2]. Community pharmacists have addressed some of the problems of medication use in the somatic nursing home or a psychogeriatric nursing home. Residents with predominantly psy- elderly and have given suggestions for improvement [3]. Internationally, several studies have chogeriatric disorders (mainly dementia) are cared for in psychogeriatric nursing homes, whe- focused on pharmaceutical care. In a multicenter international study performed in 7 European reas in somatic nursing homes people with predominantly somatic disorders, such as countries, it was found that community pharmacy-based provision of pharmaceutical care Parkinson’s disease or diabetes mellitus, reside. Often, psychogeriatric care and somatic care is improved the well-being of elderly patients [4]. Patients reported better control of their medi- provided in the same nursing home, and the division between the two types of care is between cal conditions and cost savings associated with pharmaceutical care provision were observed wards. Second, the way care is provided in Dutch nursing homes is markedly different from in most countries. In a 12-month controlled intervention study it was found that community other countries. For instance, specially trained nursing home physicians provide medical care pharmacy-based interventions improved lung function, health-related quality of life, and self- on a continuous basis. This medical speciality requires a two-year postgraduate academic edu- management in asthma patients [5]. cation. In other countries, medical care in nursing homes is provided by general practitioners, Several secondary medical care services are provided on an outpatient basis, such as the mostly on an on-demand basis and not continuously. Furthermore, in the Netherlands, care is home visits of the Outpatient Thrombosis Services throughout the country to monitor oral anti- provided by a multidisciplinary team, in which nursing home physicians (1 full-time doctor per coagulant therapy by measuring the prothrombin times. Home care organisations provide tailor- 100 residents), nurses, physical therapists, speech therapists, and psychologists closely colla- borate. Medical specialists, such as neurologists and psychiatrists, provide specialised medical References care on consult basis. There are 330 nursing homes in the Netherlands, with a total of 57,000 1 Hoek JF, Penninx BW, Ligthart GJ, Ribbe MW. Health care for older persons, a country profile: the Netherlands. beds (27 per 1000 inhabitants aged 65 and older) [1]. As mentioned earlier, all nursing home J Am Geriatr Soc 2000; 48: 214-7. admissions are financed by the AWBZ. The AWBZ reimburses about 98% of all nursing homes 2 Van Mil FJW, Tromp DF, McElnay JC, De Jong-van den Berg LTW, Vos R. Development of pharmaceutical care in expenses. In addition to addressing financial stability issues, this act regulates the care stan- The Netherlands: pharmacy’s contemporary focus on the patient. J Am Pharm Assoc (Wash) 1999; 39: 395-401. 3 Van Mil JWF. Results of pharmaceutical care in the elderly, the OMA study. In Van Mil JWF. Pharmaceutical care, dards for this sector, monitored by regional health inspectors. Another act that relates to quali- the furure of pharmacy. Theory, research and practice [Thesis]. University of Groningen, 2000. ty issues in nursing homes is the ‘Care Institutions Quality Act’ (Kwaliteitswet Zorginstellingen). 4 Bernsten C, Bjorkman I, Caramona M, Crealey G, Frokjaer B, Grundberger E, et al. (Pharmaceutical care of the 20 This act aims at adequate quality assurance in health care institutions. elderly in Europe Research Group (PEER)). Improving the well-being of elderly patients via community phar- 21 Either community pharmacists or hospital pharmacists can provide the distribution of macy-based provision of pharmaceutical care. Drugs Aging 2001; 18: 63-77. 5 Schulz M, Verheyen F, Muhlig S, Muller JM, Muhlbauer K, Knop-Scheickert E, Petermann F, Bergmann KC. medicines in Dutch nursing homes. To investigate the quality of the medication distribution Pharmaceutical care services for asthma patients: a controlled intervention study. process and other pharmaceutical activities, in 1997 the Dutch Health Care Inspectorate held a J Clin Pharmacol 2001; 41: 668-76. survey among 33 nursing homes. About half of these nursing homes were served by a hospital 6 Dijkstra GJ. De indicatiestelling voor verzorgingshuizen en verpleeghuizen [Proefschrift]. Rijksuniversiteit Groningen, 2001. pharmacy, the other half by a community pharmacy. It was concluded that quality aspects 7 Ribbe MW. Care for the elderly: the role of the nursing home in the Dutch health care system. should be more incorporated in the medication distribution processes. The pharmacist should Int Psychogeriatr 1993; 5: 213-22. play a more profound role in the pharmaceutical care to nursing home residents, such as par- 8 Health Care Inspectorate. Medication distribution in nursing homes (in Dutch). Ministery of Health, Welfare and Sports, The Hague, the Netherlands, 1997. ticipation in drug and therapeutics committees, evaluation of prescribing on patient level, and 9 Dutch Association for Nursing Home Care (Vereniging voor Verpleeghuiszorg (NVVz) in samenwerking met regular updates of drug formularies [8]. As a result of this survey, a ‘Guideline Pharmaceutical KNMP, NVZA, NVVA): Guideline Pharmaceutical Care in Nursing Homes (in Dutch). Utrecht, 1998. Care in Nursing Homes’ was drafted in 1998 [9]. This guideline describes how pharmaceutical 10 Gurwitz JH, Soumerai SB, Avorn J. Improving medication prescribing and utilization in the nursing home. care by the pharmacist in nursing homes is best performed, and serves as a guideline for imple- J Am Geriatr Soc 1990; 38: 542-52. 11 Shorr RI, Fought RL, Ray WA. Changes in antipsychotic drug use in nursing homes during implementation of menting quality assurance processes. For both economic and therapeutic reasons, a drug for- the OBRA-87 regulations. JAMA 1994; 271: 358-62. mulary is used in almost every Dutch nursing home, constituting of a limitative list of preferred 12 Schmidt I, Claesson CB, Westerholm B, Nilsson LG, Svarstad BL. The impact of regular mulidisciplinary team medications. In several Dutch nursing homes, drug therapy issues are regularly discussed in interventions on psychotropic prescribing in Swedish nursing homes. J Am Geriatr Soc 1998; 46: 77-82. 13 Schmidt I, Claesson CB, Westerholm B, Svarstad BL. Resident characteristics and organizational factors Pharmacotherapy Discussion Groups, in which both nursing home physicians and pharmacists influencing the quality of drug use in Swedish nursing homes. Soc Sci Med 1998; 47: 961-71. participate. For certification, these meetings should be held at least 6 times a year. Studies 14 Lunn J, Chan K, Donoghue J, Riley B, Walley T. A study of the appropriateness of prescribing in nursing homes. addressing the quality of pharmaceutical care in nursing homes have not been performed Int J Pharm Pract 1997; 5: 6-10. 15 Janzig JGE, Van ‘t Hof MA, Zitman FG. Drug use and cognitive function in residents of homes for the elderly. extensively. Mainly this work has been carried out in the United States [10,11], but in recent Pharm World Sci 1997; 19: 279-82. years European studies also focus on this issue [12-16]. 16 Wagner C, Van der Wal G, Groenewegen PP, De Bakker DH. The effectiveness of quality systems in nursing homes: a review. Qual Health Care 2001; 10: 211-7. Chapter 2 22 23

Drug utilisation studies in the elderly Outline 2.1 Background

In this chapter, we present several drug utilisation studies in the elderly. This chapter comprises two parts: in part one (section 2.1 through 2.5) drug utilisation studies in nursing home Introduction residents are described, and in part two (section 2.6 and 2.7) drug use in ambulatory elderly is described. In section 2.6, both ambulatory elderly and nursing home residents are studied Several reviews on drug utilisation and quality of prescribing in elderly outpatients have separately. been carried out demonstrating high levels of drug use and a considerable number of patients 24 In section 2.1 some major international studies on drug use and quality of prescribing in receiving inappropriate medications [1]. In the Netherlands, drug utilisation studies have 25 nursing homes are summarised and the Dutch studies that have been published on this subject demonstrated that the prevalence of multiple chronic drug use in elderly outpatients is high [2]. are reviewed. Section 2.2 describes how pharmacy prescription data from nursing homes have Recently, the extent of polypharmacy in Dutch elderly outpatients was investigated and it was been used to build a nursing home database with the aim to perform drug utilisation and risk concluded that the problem of polypharmacy was less than in other countries [3]. While drug assessment studies. This section also presents a suggestion for the criteria such data should use in elderly outpatients has been extensively studied, less is known about drug utilisation meet to perform pharmacoepidemiological studies. In section 2.3, a drug utilisation study in 6 and quality of prescribing in Dutch nursing homes. In the next paragraphs, a review is given of nursing homes is presented. In this study, detailed information is given on determinants of drug some major studies on drug use and quality of prescribing in nursing homes. use in a cohort of 2,355 residents. The results of this study served as a starting point to investigate some of the issues on prescribing quality in more detail in the next sections. Section 2.4 Drug utilisation studies in nursing homes describes the occurrence and nature of potential drug-drug interactions in the same cohort of nursing home patients. Section 2.5 presents a pilot study that used several prescribing indica- Drug use in nursing homes has been reviewed in several articles [4-7] and a number of drug tors, based on the studies in 2.3 and 2.4, to evaluate drug prescribing in Dutch nursing homes. utilisation studies have been performed in nursing homes [8-24]. Many of these focus on cer- Section 2.6 presents a study on the concomitant use of benzodiazepines and antidepres- tain drugs or drug groups, in particular psychotropics [21-24]. In table 1 a summary of some sants in elderly outpatients and nursing home patients. We assessed whether differences major studies on drug use in nursing homes during 1990-2000 is given. The number of nursing between co-prescribing with tricyclic antidepressants and selective serotonine re-uptake inhi- home residents reviewed varies from 60 to 1854, and the average number of drugs prescribed bitors existed. In section 2.7, the concomitant use of non-steroidal anti-inflammatory drugs and per resident varies from 2.5 to 8.8. These differences might be due to the different lengths of gastroprotective drugs, as an example of a beneficial drug-drug combination was investigated. time for which drug use was studied. In many of these studies, data on drug use was collected by medical chart review or by interviews. Three drug utilisation studies have been published from the Netherlands [12,13,18]. Troost and co-workers used hospital-dispensing data to assess the defined daily dosages (DDDs) per 100 beddays [12]. Drug use was not analysed on an individual patient level. Koopmans and colleagues studied drug use of psychogeriatric patients [13], and Verkoulen-Wijers [18] reviewed drug use of 60 patients using a cross-sectional design. Two other Dutch studies were published before 1990 [25,26]. Merkus and co-workers [25] investigated drug use at admission and 3.5 years later in 112 patients aged 75 and over. In people residing in homes providing somatic care, medication increased from 3.8 to 5 prescriptions per day, and in people residing in nursing homes providing psychogeriatric care, medication increased from 2.7 to 3.4 prescriptions per day. Van Zuylen [26] showed that 80% of the patients (n=198) used 2 to 7 drugs (on average 4.4). The drugs used most frequently were psychotropics, analgesics, cardiovascular drugs, diuretics and laxatives. Table 1: A review of studies on drug use in nursing homes In conclusion, several studies have investigated the rate of drug use in nursing homes. Ref Country N Study design Average Main findings Many used cross-sectional designs, and only few studies used longitudinal prescription data to (year of number of publication) prescriptions evaluate effects over time. The number of nursing home residents included in each study varied 8 US 81 Analysis of medication 4.7 (entry) Increase in medication prescribing considerably. The studies carried out in the Netherlands involved relatively small numbers of (1990) prescribed at entry and 6.2 (3 months) due to increase in prn* medications after 3 months residents. To obtain more insight into drug use in Dutch nursing homes, a study among 2,355

9 Belgium 198 Cross-sectional chart 4.5 Drug use increased with age but residents was carried out (section 2.3). (1992) review in sample of stabilises after 80 yrs patients aged ≥ 62 yrs 26 Quality of prescribing in nursing homes 27 10 US 1106 Cross-sectional study 7.2 Inappropriate prescribing was common (1992) using pharmacy data of patients ≥ 65 yrs In particular in the United States, much attention has been given to rational and approp- 11 US 120 Effect of drug regimen 7.2-5.3 Pharmacist reduced medication riate prescribing in nursing homes. In 1987, the Omnibus Reconciliation Act (OBRA ‘87) was pas- (1992) review on medication use in nursing home by computerised use drug regimen review sed as a result of increasing public concern about the overuse of neuroloptics in nursing homes. These federal regulations were established to ensure appropriate care in US nursing homes, 12 Netherlands 147 Analysis of pharmacy - Drug use in general according to (1993) dispensing data drug formulary and in particular to reduce the unnecessary prescribing of antipsychotic medications [27]. Since (number of DDDs/100 beddays) during 1991-1992 OBRA ‘87 numerous studies have addressed the problem of unnecessary or inappropriate drug use in nursing homes in the US and other countries and have investigated opportunities for 13 Netherlands 390 Retrospective chart review 2.5-2.9 Increase in drug use (mainly laxatives) (1994) among psychogeriatric after admission to nursing home improvement [28-32]. Several tools have been developed to assess the appropriateness of pre- patients scribing [33]. Many of these tools were developed for assessing medication appropriateness in 14 South Africa 85 Intervention study; review 4.8 41% reduction in incidence of elderly outpatients, and not nursing homes. Most tools used information on clinical status or (1996) of medical profile charts polypharmacy due to for drug related problems pharmacist intervention diagnoses. In 1991, Beers and colleagues developed a set of criteria for identifying inapprop-

15 UK 101 Intervention study; review 6.5 53% of residents showed ≥ 1 riate medication use in nursing home residents in the US [34]. These criteria, based on expert (1997) of medical records to study inappropriate prescription consensus, consisted of a list of 23 medications that should be avoided and 13 medication doses, appropriateness of prescribing frequencies, or duration of prescriptions that generally should not be exceeded. The list of inap-

16 Sweden 1854 Intervention study; review 7.7 No effect of intervention on overall propriate drugs needs to be updated periodically, as it was based on state of knowledge at that (1998) of medical records use of medication time (1989). An update, incorporating clinical information, was published in 1997 [35]. 17 Australia 998 Cross-sectional survey of 6.6 Nursing home culture exerts a major Internationally, several studies have used Beers’ criteria to assess medication appropriateness. (1998) medication use by chart (prescribed) influence over prescribing and review 4.8 administration of medications In 1992, a prospective cohort study was carried out using Beers criteria among 12 nursing (administered) homes in the US (n=1106) [8]. It was found that 40% of the residents received at least one 18 Netherlands 60 Cross-sectional survey of 4.9 Laxatives, diuretics, psycholeptics and inappropriate prescription, and 10% received two or more inappropriate medications concur- (1999) medication use by chart including prn*; antithrombotics used most frequently review 4,6 rently. Female residents and residents of large nursing homes were at the highest risk of recei- excluding prn ving inappropriate medications. In 1996, Gupta and co-workers [36] investigated the associa- 19 Sweden 1001 Cross-sectional survey in 3.4 High prevalence of drug use and tion between costs and inappropriate prescribing using a slightly modified version of Beers cri- (1999) ('87-'89); cohort of subject aged 81 ('87-'89); polypharmacy in very elderly 681 and over 4.6 teria in a retrospective, cross-sectional study among nursing home residents (Medicaid benefi- ('94-'96) ('94-'96) ciaries; n=19,932). It was found that cost of pharmaceutical services for a resident was positi- 20 Sweden 1549 Controlled intervention 8.0 (1995) Intervention homes showed higher vely correlated with the number of different inappropriate drugs prescribed, number of physi- (2000) study in 36 nursing homes 8.8 (1998) quality of drug use

# expressed as ‘time pattern of drug exposure’: uninterrupted period of usage of the same drug * prn = pro re nata = as required cians and pharmacies used and geographic region. In 1997, Lunn and colleagues [37] developed formed on the appropriateness or quality of prescribing in nursing homes. In section 2.4 to 2.7 a set of 18 explicit criteria, based on expert’s opinions, for identifying inappropriate prescribing we have made an attempt to identify suboptimal prescribing by using several aspects of pre- in 101 nursing home residents in the UK. Fifty-three percent of the residents had one or more scribing indicators from the international literature, such as the occurrence of drug-drug inter- inappropriate prescriptions. Medicines most frequently associated with inappropriate prescri- actions, the concomitant use of certain drug groups, and selection of formulary drug use. bing were cardiovascular drugs and drugs for the central nervous system [37]. In Sweden, an attempt was made to identify inappropriate psychotropic drug prescribing in 33 Swedish nursing homes (1823 residents) by Schmidt and colleagues [38]. They developed a list of 13 criteria, References 28 based on Swedish guidelines for measuring excessive use of psychotropic drug use in the elder- 29 1 Aparasu RR, Mort JR. Inappropriate prescribing for the elderly: Beers criteria-based review. Ann Pharmacother ly. A wide variability in the appropriateness of drug use among the 33 nursing homes was 2000; 34: 338-46. found. Drug use for a majority of residents had deviated from one or more of the drug use cri- 2 Heerdink ER. Clustering of drug use in the elderly: population-based studies into prevalence and outcomes teria. Overall, concern was expressed about the quality of drug prescribing practices in Swedish [Thesis]. University of Utrecht, 1995. 3 Veehof LJG. Polypharmacy in the elderly [Thesis]. University of Groningen, 1999. nursing homes. The drug use criteria developed addressed three main issues: deviation of 4 Lamy P. Institutionalisation and drug use in older adults in the US. Drugs Aging 1993; 3: 232-7. documentation on indication of drug (for example: antipsychotic drug prescribed; psychotic 5 Avorn J, Gurwitz JH. Drug use in the nursing home. Ann Intern Med 1995; 123: 195-204. diagnosis absent), deviations of drug choice (for example: prescribing of non recommended 6 Furniss L,Craig SKL, Burns A. Medication use in nursing homes for elderly people. Int J Geriatr Psychiatry 1998; hypnotic drug), and deviations of excess (for example: prescribing of more than 2 psychotropic 13: 433-9. 7 Gurwitz JH, Soumarai SB, Avorn J. Improving medication prescribing and utilization in the nursing home. drugs concomitantly). Again, these criteria used in part clinical information. In another Swedish J Am Geriatr Soc 1990; 38: 542-52. study [20] prescribing indicators were used to assess the effect of an intervention aimed at 8 Wayne SJ, Rhyne RL, Stratton M. Longitudinal prescribing patterns in a nursing home population. improving drug use through improved teamwork among physicians, pharmacists, nurses and J Am Geriatr Soc 1990; 40: 53-6. 9 Vander Stichele RH, Mestdagh J, Van Haecht CH, De Potter B, Bogaert MG. Medication utilization and patient nurses’ assistants. In the intervention homes, a higher quality of drug use was seen after the information in homes for the aged. Eur J Clin Pharmacol 1992; 3: 319-21. intervention, compared with the control homes. The prescribing indicators addressed three 10 Beers MH, Ouslander JG, Fingold SF, Morgenstern H, Reuben DB, Rogers W et al. Inappropriate medication issues: indication of drug (for example: antipsychotic drug prescribed without diagnoses of psy- prescribing in skilled-nursing facilities. Ann Intern Med 1992; 151: 1825-31. 11 Laucka PV, Hoffman NB. Decreasing medication use in a nursing-home patient-care unit. Am J Hosp Pharm chotic symptom); quantity of drug use (more than 2 psychotropic drugs) and potential interac- 1992; 49: 96-9. tions. 12 Troost SJ, Smit LH, Wentink DH, Neef C. Gebruikscijfers van geneesmiddelen uit het verpleeghuis ‘De Cromhoff’ In conclusion, studies on prescribing appropriateness in nursing homes have shown that a te Enschede [Drug utilization figures in a nursing home]. Pharm Weekbl 1993; 128: 1511-6. considerable proportion of the nursing home residents received inappropriate prescribing. The 13 Koopmans RT, de Haan HH, van den Hoogen HJ, Gribnau FW, Hekster YA, van Weel C. Veranderingen in geneesmiddelgebruik tijdens een verblijf in een psychogeriatrisch verpleeghuis. [Changes in drug use during way prescribing appropriateness was assessed differed among the studies as different prescri- stay in a psychogeriatric nursing home]. Ned Tijdschr Geneeskd 1994; 138: 1122-6. bing or quality indicators are in use. Prescribing indicators used in one health care system are 14 Belligan M, Wiseman IC. Pharmacist intervention in an elderly care facility. Int J Pharm Pract 1996; 4: 25-9. not automatically applicable to other health care systems due to differences in national phar- 15 Lunn J, Chan K, Donoghue J, Riley B, Walley T. A study of the appropriateness of prescribing in nursing homes. Int J Pharm Pract 1997; 5: 6-10. macotherapy guidelines and drug formularies. Furthermore, for many prescribing indicators 16 Claesson CB, Schmidt IK. Drug use in Swedish nursing homes. Clin Drug Invest 1998; 16: 441-52. information on clinical status, such as laboratory results or diagnoses are needed, which makes 17 Roberts MS, King M, Stokes JA, Lynne TA, Bonner CJ, McCarthy S, Wilson A, Glasziou P, Pugh John W. Medication them unsuitable to apply them based solely on pharmacy prescription data. To assess medica- prescribing and administration in nursing homes. Age Ageing 1998; 27: 385-92. 18 Verkoulen-Wijers MJ, Koopmans RTCM, Schimmel W. Geneesmiddelengebruik van somatische verpleeghuis- tion appropriateness in nursing homes, indicators should be used that reflect deviations from bewoners en verzorgingshuisbewoners in Zorgcentrum Tilburg-zuid. Tijdschr Verpleeghuisgeneeskd 1999; 1: 4-7. national pharmacotherapy guidelines and drug formularies. As these vary with time and loca- 19 Giron MST, Claesson C, Thorslund M, Oke T, Winblad B, Fastbom J. Drug use patterns in a very elderly tion, prescribing indicators are dependent on the country or even the institution where the population. Clin Drug Invest 1999; 17: 389-98. 20 Schmidt IK, Fastbom J. Quality of drug use in Swedish nursing homes. A follow-up study. Clin Drug Invest 2000; research is performed. To our knowledge, in Dutch nursing homes, no studies have been per- 20: 433-446. 21 Nygaard HA, Naik M. Use of psychotropic drugs in homes for the aged in Bergen, Norway: a comperative study. 2.2 Use of hospital pharmacy data in Norwegian Journal of Epidemiology 1998; 8: 133-8. 22 McGrath AM, Jackson GA. Survey of neuroleptic prescribing in residents of nursing homes in Glasgow. pharmacoepidemiologic research BMJ 1996; 312: 611-2. 23 Cohen-Mansfield J, Lipson S, Gruber-Baldini AL, Farley J, Woosley R. Longitudinal prescribing pattern of in nursing homes psychotropic drugs in nursing home residents. Exp Clin Psychopharmacol 1996; 4: 224-33. 24 Koopmans RTCM, van Rossum JM, van den Hoogen HJM, Hekster YA, Willekens-Bogaers MAJH, van Weel C. Psychotropic drug use in a group of Dutch nursing home patients with dementia: many users, long-term use, but low doses. Pharm World Sci 1996; 18: 42-7. K.N. van Dijk 1, 2, C.S. de Vries 3, J.R.B.J. Brouwers 1, 2, 25 Merkus JW, Deurenberg HP, Pollmann AM. Het geneesmiddelgebruik in 3 verpleeghuizen voor lichamelijk 1 30 zieken [Drug utilization in 3 nursing homes for somatic patients]. Tijdschr Gerontol Geriatr 1985; 16: 87-95. L.T.W. de Jong-van den Berg 31 26 Van Zuylen C, Oostendorp FMGM, van Beusekom BR, Cools HJM, Bolk JH, Ligthart GJ. Toenemend geneesmiddelgebruik in het verpleeghuis [Increasing use of medication in nursing homes]. Ned Tijdschr Geneesk 1988; 132: 1692-5. 1 27 Llorente MD, Olsen EJ, Leyva O, Silverman MA, Lewis JE, Rivero J. Use of antipsychotic drugs in nursing homes: Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, University current compliance with OBRA regulations. J Am Geriatr Soc 1998; 46: 198-201. Centre for Pharmacy, Groningen University Institute for Drug Exploration (GUIDE), 28 Semla TP, Palla K, Poddig P, Brauner DJ. Effect of the Omnibus Reconciliation Act 1987 on antipsychotic Groningen, the Netherlands prescribing in nursing home residents. J Am Geriatr Soc 1994; 42: 648-52. 2 29 Garrard J, Makris L, Dunham T, Heston LL, Cooper S, Ratner ER, et al. Evaluation of neuroleptic drug use by Clinical Pharmacy Department, Medical Centre Leeuwarden, the Netherlands nursing home elderly under proposed Medicare and Medicaid regulations. JAMA 1991; 265: 463-7. 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, 30 Rovner BW, Edelman BA, Cox MP, Shmuely Y. The impact of antipsychotic drug regulations on psychotropic Guildford, United Kingdom prescribing practices in nursing homes. Am J Psychiatr 1992; 149: 1390-2. 31 Schorr RI, Fought RL, Ray WA. Changes in antipsychotic drug use in nursing homes during implementation of the OBRA-87 regulations. JAMA 1994; 271: 358-62. 32 Ray WA, Taylor JA, Meador KG, Lichtenstein MJ, Griffin MR, Fought R, et al. Reducing antipsychotic drug use in nursing homes: a controlled trial of provider education. Arch Intern Med 1993; 153: 713-21. 33 Shelton PS, Fritsch MA, Scott MA. Assessing the medication appropriateness in the elderly. A review of available measures. Drugs Aging 2000, 16: 437-50. 34 Beers MH, Ouslander JG, Rollingher I, Reuben DB, Brooks J, Beck J. Explicit criteria for determining inappropriate medication use in nursing homes. Arch Intern Med 1991; 151: 1825-32. 35 Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. Arch Intern Med 1997; 157: 1531-6. 36 Gupta S, Rappaport HM, Bennett LT. Inappropriate drug prescribing and related outcomes for elderly Medicaid benificiaries residing in nursing homes. Clin Therap 1996; 18: 183-96. 37 Lunn J, Chan K, Donoghue J, Riley B, Walley T. A study of the appropriateness of prescribing in nursing homes. Int J Pharm Pract 1997; 5: 6-10. 38 Schmidt IK, Claesson CB, Westerholm B, Svarstad BL. Resident characteristics and organizational factors influencing the quality of drug use in Swedish nursing homes. Soc Sci Med 1998; 47: 961-71. Introduction Data available

In pharmacoepidemiology, computerised medication databases are a useful tool. To study Medication order data drug use in primary health care in the Netherlands several computerised medication databa- The study was carried out in six nursing homes for long-term care in the Netherlands. ses are available, such as the PHARMO-database [1], the InterAction-database [2], and the These nursing homes each had a bed capacity that varied between 90 and 225, and each was IPCI-database [3]. Both the InterAction-database and the PHARMO-database are based on served by one of three hospital pharmacies. In the drug dispensing system in the nursing community pharmacy records. Because patients generally attend only one pharmacy and com- homes studied, all drugs that were dispensed to residents were registered in the hospital phar- 32 munity pharmacies are entirely automated, almost complete individual medication profiles macy computer system (Apho-data®). Routinely, the nursing home physicians have to write 33 covering several years are available. Community pharmacy records have been reported to be a medication orders for each change in the drug regimen, such as a dosage or frequency change, reliable source of drug exposure [4]. The PHARMO database is record-linked with hospital the discontinuation of the drug and, obviously, the start of a new drug. In this way, any changes diagnoses data. The IPCI-database is based on general practitioners’ (GPs) prescribing data and in medication are updated routinely on a daily basis in the hospital pharmacy computer system as such the information recorded is comparable with the GPRD-database in the UK [5], al- and a complete medication history is kept for each individual resident. Every day, nurses dis- though the IPCI-database is much smaller [3]. A variety of drug utilisation and drug safety stu- pense medication to individual nursing home residents on the basis of the information recor- dies have been performed using these Dutch databases [6-9]. ded in the computer system (drug, dosage, route and time of administration). As a consequen- In the Netherlands, drug utilisation studies in secondary (hospitals) and tertiary (nursing ce, the recording of actual drug use can be considered very accurate. homes) health care are performed sparingly, partly because computerised individual hospital medication records have not been available until the mid 90s. Internationally, in particular in SIVIS data the United States and Canada, several drug utilisation studies have been carried out in nursing In the Netherlands, a national information system on nursing home residents (SIVIS) is homes using large administrative databases [10-14]. In the US a Minimum Data Set, a data col- operational. The SIVIS database consists of anonymous administrative, nursing and medical lection instrument containing more than 300 demographic, clinical and treatment variables, is data collected on individual nursing home residents. More than 70% of the Dutch nursing used for each patient that is admitted to a certified nursing home [15]. Although not all drug use homes contribute to the SIVIS database. The SIVIS data are collected quarterly in each nursing is included in these databases, the fact that they contain medical diagnoses makes them very home by the nursing home staff and, subsequently, these data are anonymised and registered valuable. In a large drug utilisation study in nursing homes in Sweden [16] medication use was nationally. The SIVIS morbidity classification is derived from the International Classification of recorded by research nurses. In the Netherlands, computerised medication databases in nur- Diseases (ICD-9) and contains 99 diagnoses. For each resident, a maximum of three diagnoses sing homes have not been available until recently. To our knowledge, these databases have not can be registered each time. yet been used in drug utilisation studies [17,18]. The applicability of computerised medication databases in pharmacoepidemiology in this population is therefore unknown. Ideally, both Data collection detailed information on patients’ drug use and health status should be available for drug research in nursing homes. Medication order data In this study we describe how medication order data from nursing homes have been used We collected medication order data of all nursing home residents for a 2-year period to build a nursing home database with the aim to perform drug utilisation and risk assessment between 01-10-1993 and 01-10-1995. Patient data for each nursing home resident included date studies. Furthermore, we make a suggestion for the criteria such data should meet to perform of birth, gender, date of admission to the nursing home, date of discharge, code of the nursing such studies. home, and code of the attending nursing home physician. For every prescription a start date and, if known, an end date was registered, enabling us to calculate the actual duration of drug use. Furthermore, the name of the drug, daily dose, dosage interval and route and time of administration were recorded. Each medication record was given a drug ID (KNMP-number, a Data verification unique code for every formulation and pack size of a drug that is on the market in the Netherlands). Each drug ID and hence every medication record was record-linked with the Medication order data national reference drug database of the Royal Dutch Association for the Advancement of Accuracy of the medication database was verified by comparing the medication history Pharmacy (KNMP, The Hague), to collect drug-specific information such as Anatomical from the original pharmacy computer system with the medication history in the newly built Therapeutic Chemical (ATC) codes and defined daily dosages (DDD). database for 10 randomly selected patients for each nursing home (total of 60 patients). In view of the drug distribution system described above, no other way of verifying the medication data- 34 SIVIS data and record-linkage base was possible (for example, patient interviews, or nurses’ charts). We did not find any dis- 35 The medication database was record-linked with the SIVIS database, by matching 3 patient crepancies. characteristics (date of birth, gender and nursing home code), in order to collect data on morbidity, type of care (somatic or psychogeriatric) and mobility (2 categories) from the SIVIS data- SIVIS data base. Fourteen percent of the patient records could not be record-linked to the SIVIS database. To verify the accuracy and completeness of the SIVIS diagnoses data we performed a sen- In figure 1 the structure of the databases is given. sitivity and specificity analysis in which we compared medication order records and SIVIS diagnoses records for diabetes mellitus and Parkinson’s disease. These diseases were chosen in view of the clearly defined drug groups that are used for these disorders; namely antiglycaemic Patient database Medication database drugs (ATC code A10) and anti-Parkinson drugs (ATC code N04). The validation of SIVIS diag- Patient ID Patient ID noses data resulted in three outcomes: registered SIVIS diagnosis and registered proxy drug Date of birth* Drug name use (true positive), no SIVIS diagnosis that could relate to proxy drug dispensed (false negati- Gender* Drug ID Nursing home code* Medication ID ve), and SIVIS diagnosis registered and no proxy drug prescribed (false positive). The positive Date of admission Start date predictive value of the SIVIS diagnosis was calculated as the proportion of patients with the Date of discharge (if applicable) Stop date SIVIS diagnosis and using the proxy drug among all patients who are registered with the SIVIS Daily dosage Dosage interval diagnosis. Sensitivity of the SIVIS diagnosis was the proportion of patients registered with the Prescriber code SIVIS diagnosis and using the proxy drug among the total number of patients who were prescribed the proxy drug. Specificity of the SIVIS diagnosis was the proportion of patients prescribed non-proxy drugs for other indications than the SIVIS diagnosis among the total number of patients prescribed non-proxy drugs. The results of these analyses are given in table 1.

Reference drug database (Z-index) Table 1a: Results of the sensitivity and specificity analysis of the SIVIS diagnoses data for diabetes mellitus Drug ID Pharmacy record ATC code A10 ATC code SIVIS database DDD value + - Total Date of birth* SIVIS diagnose + 152 24 176 Positive predictive value: Gender* diabetes mellitus 152 / 176 = 0.86 Nursing home code* - 207 1972 2179 Sensitivity: Diagnosis code 152 / 359 = 0.42 Type of care Total359 1996 2355 Specificity: Mobility code 1972 / 1996 = 0.99

Figure 1: Structure of the databases (*: used for record-linkage) Table 1b: Results of the sensitivity and specificity analysis of the SIVIS diagnoses data for M. Parkinson

Pharmacy record ATC code N04 Source population: N=2,966 + - Total SIVIS diagnose + 115 36 151 Positive predictive value: Age: 80.1 yrs (SD 10.6) Gender: 70.0% female M. Parkinson 115 / 151 = 0.76 # of medication records: 42,648 (14.4)¶ - 76 2128 2204 Sensitivity: 115 / 191 = 0.60 Total191 2164 2355 Specificity: N=194 (6.5%) < 65 yrs 36 2128 / 2164 = 0.98 Age: 52.6 (SD 10.6) 37 Gender: 55.2% female # of medication records: 2,855 (14.7)¶

Study population N=2,772 Age: 82.1 (SD 7.4) The source population consisted of 2,966 patients. Of this population, the admission date Gender: 71.1% female # of medication records: 39,793 (14.4)¶ was missing in 264 patients (9%) and the date of discharge was missing in 268 patients (10%). If the admission date was unknown, it was assumed to be the first medication start date. If the N=394 (14.2%) date of discharge was unknown, it was assumed to be the last end date of the medication used no SIVIS-data Age: 82.5 (SD 8.1) or as the last day of the study period (01-10-1995), whichever was the earliest. 194 of 2,966 Gender: 74.1% female (6.5%) people were excluded because they were younger than 65 years (average age 52.6 # of medication records: 4,607 (11.7)¶ years (SD 10.6) versus 82.1 years (SD 7.4) (p<0.05)). Compared with the remaining 2,772 patients, the excluded population included more men (44.8% versus 28.9% (p<0.05). Of the 2,772 N=2,378 patients left, 394 (14.2%) were excluded because they could not be linked to the SIVIS databa- Age: 82.0 (SD 7.3) Gender: 70.6% female se. Compared with the remaining 2,378 residents, they had the same average age (82.5 versus # of medication records: 35,186 (14.8)¶ 82.0 years), and there were slightly more women present (74.1% versus 70.6%; p>0.05). These patients were equally distributed over the six nursing homes. Of the 2,378 patients left, 23 (1%) N=23 (1%) were excluded because of missing data (for example, the period of stay could not be calcula- missing data Age: 79.4 (SD 8.1) ted). Compared with the remaining 2,355 patients, this population included more men (47.8% Gender: 52.2% female ¶ versus 29.3%; p<0.05). The final study population consisted of 2,355 patients. Figure 2 shows # of medication records: 270 (11.7) how the study population was constructed. In table 2 patient characteristics are given for the Study population: N=2,355 study population. Age: 82.0 (SD 7.3) Gender: 70.7% female # of medication records: 34,916 (14.8)¶

Figure 2: Construction of the study population Table 2: Characteristics of the study population (n=2,355) Discussion

Variable Number of residents (% of total) This study describes how hospital pharmacy data and SIVIS data can be used to build a Age 82 (SD 7.3) database to perform pharmacoepidemiological studies of drug utilisation and drug safety in Gender Male 689 (29%) nursing home residents [19-21]. Recommendations are summarised in table 3. We encountered Female 1666 (71%) several pitfalls during our study, which are described below. Type of nursing Data availability. Detailed information on individual patients’ drug utilisation profiles has 38 Psychogeriatric 700 (30%) to be available on a continuous basis. In most pharmacy computer systems, it is now common 39 Somatic 1609 (68%) Not known 46 (2%) use to register this information on a continuous basis for longer periods of time (e.g. 5-10 Morbidity years). In this study we retrieved data for a two-year period. Ideally, it should be possible to Parkinson's disease 151 (6%) retrieve data at any time for any period of time. Because information on morbidity and mobili- Diabetes mellitus 176 (7%) ty was needed to perform one study [19], we collected these data from the national nursing Depression 40 (2%) Dementia 689 (29%) home information database (SIVIS). At the moment, SIVIS data are the only source of automa- Mobility ted diagnoses data available. Mobile 1370 (58%) Data collection. An important aspect of the data collection is that the data are adequately Immobile 985 (42%) anonymised. Ideally, the pharmacy computer system should contain special ‘export files’ by Number of different medications 0-5 626 (27%) which drug utilisation data can be anonymously collected on an individual level. Collection of 6-10 969 (41%) the SIVIS data was done by record-linkage. Because the patient identifier used in the pharma- > 10 760 (32%) cy records was different from the patient identifier in the SIVIS database, we performed a Average number of different medications record-linkage on three variables: date of birth, sex and nursing home code. Fourteen percent per day per resident 4.9 of the residents could not be linked. This could have been due to the fact that these patients Average number of different medication had not been registered in the SIVIS database yet. (based on ATC-codes; fifth level) per resident during study residence in nursing home 8.9 (SD 4.9) Data completeness. Completeness and accuracy highly depends on the organisation and structure of the (hospital) pharmacy concerned. For example, adequate quality control proce- dures should ensure that all necessary information is recorded in the pharmacy computer system. The professional organisation of Dutch hospital pharmacies facilitates adequate quality Medication use control by both pharmacy technicians (who generally record the data), and hospital pharma- Initially, for the source population, an average number of 14.4 medication records per cists (who generally check and supervise). We found that in 10% of the patients the date of dis- patient were registered in the medication database. In figure 2 the number of medication charge was missing, and that in 9% of the patients the admission date was missing. These per- records for each patient cohort is given. In the final study population, the average number of centages could be decreased when it is made impossible not to fill in certain database fields at (registered) medication records per patient was 14.8. The relatively high number of medication the data entry stage (by pharmacy technicians). Use of over-the-counter (OTC) medication has records recorded per patient can be explained by the fact that each change (dosage or fre- not been included in our database. We expect this to be relatively low due to practical reasons quency change) in the therapeutic regimen is recorded separately [19]. such as immobility of the residents and continuous medical attention by both nursing and medical staff and the possibility to receive drugs that are available OTC via prescription by the nursing home physician. Data verification. In our study we used medication order data, which form the basis for the dispensing of medication by nurses to individual nursing home residents. One important con-

dition of this dispensing system is that every change in drug therapy is known to the hospital re with pharmacy. Unlike for community pharmacy records [4], the accuracy and completeness of the IVIS.

hospital pharmacy data has not been verified. In the nursing homes studied, nursing home phy- such as sicians are obliged to record every change in drug therapy and send these changes (by fax) immediately to the hospital pharmacy. As a result, hospital pharmacy data are a reliable sour- 40 ce of drug exposure of nursing home residents. We did not find any discrepancies when we 41 verified the medication data. From the SIVIS sensitivity and specificity analysis it was found

that the positive predictive value (PPV) of the SIVIS diagnoses diabetes mellitus was 0.86, and atabases 0.76 for M. Parkinson. These data indicate that 14% and 24% of the residents who are diagnosed in the SIVIS-database with diabetes mellitus and M. Parkinson respectively, do not use medication that is commonly used for these disorders. There is a discrepancy between the medication records and the SIVIS diagnoses data. This suggests that the prevalence of these disorders may be overestimated when using SIVIS diagnoses data alone. The sensitivity values of the SIVIS diagnoses are relatively low, indicating that 58% and 40% of the residents using drugs for diabetes mellitus and M. Parkinson respectively, are not registered as suffering from these disorders in the SIVIS database. This suggests a large underestimation of the percentage of residents with diabetes mellitus and M. Parkinson when SIVIS data alone are used, recorded recorded in original database, but they anonymously. were retrieved must (key remain in original database). drug drug database. be needed. they were slightly they older than the Dutch nursing home population. when pharmacy data are considered the ‘gold standard’. A reason for this could be the fact that used in current study these diagnoses are not one of the three diagnoses registered, however in view of the disabling consequences of M. Parkinson this seems unlikely. Further research is needed into the reasons for these discrepancies. The specificity values of the SIVIS diagnoses diabetes mellitus and M. Parkinson are high (0.99 and 0.98, respectively), indicating that no SIVIS diagnoses are recorded for residents that do not use medication for these diagnoses. We suggest combining both pharmacy data and SIVIS-diagnoses data to get a more reliable estimate of the true prevalence. Recently, Van de Vijver and co-workers showed that antiparkinsonian drugs in pharmacy by by which route of administration. through record-linkage with national could national drug database (Z-index) patients are used by those patients, and all drugs that are used by individual patients are registered. been found (10%). pharmacoepidemiologic research pharmacy prescription database perform pharmacoepidemiologic studies. Minimum required size will vary depending on the research different hospital question.pharmacies an obtained for the purposes of this study. adequate sample size (n=2,355) was use the same pharmacy computer system Hospital pharmacies should preferably (and hence hospital pharmacies). (or provide the same export record). records in ambulatory patients aged 55 and older can be used as a reliable marker for M. study drug use over a time sequence. study period. for 2-year compliance is required. histories for long period of time. by nursing home staff. Parkinson [22]. Misclassification of drug use could occur when medication that is prescribed and hence registered in the pharmacy computer system, is not actually consumed by the patient (either by non-compliance or by errors in the distribution process). However, a pilot study has shown that medication compliance in Dutch nursing homes is generally high (99%) [23]. Because we did not have information on the use of OTC-medication, this may lead to an representativeness for Dutch nursing home population. of age and sex and type of care although with national data from available S drug, dose and duration is frequency taken for how long and were obtained on DDD-and ATC-codes linkage and DDD-values ATC-codes, Detailed information on Which drug, in which dosage, in which Detailed information available, data obtain specific To drug data Accuracy, Accuracy, completeness medication database for individual All drugs that are registered in data inaccurate and omissions have Data entry althoughwas accurate, some data entry by training pharmacy technicians. Ensure data and completeness accurate Aspects Requirements for Data available in hospital Generalisability/ has Population to be representative had Population a similar distribution Recommendations Needs to be taken into account; compa Confidentiality Data need to be anonymous. data were not Patient anonymously Use patient encrypted identifiers Sample size Needs to be sufficiently large to By grouping patient data from data nursing Collect from several homes Continuity data Longitudinal are required to data Longitudinal were available Ensure continuity by keeping medication underestimation of exposure to OTC drugs and hence misclassification. Drug intake Other sources Information regarding medication known. Use of OTC-drugs Medication compliance ensured None use was considered negligible OTC-drug None Discrepancies between Discrepancies data required for pharmacoepidemiological and research data available in hospital pharmacy d prescription Drug Drug use Population Table 3: Table References

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and other as computer system applicable. ad hoc basis. against medical charts. drugs [Thesis]. University of Utrecht, 1990. 7 De Vries CS. Collaboration in healthcare, the tango to drug safety [Thesis]. University of Groningen, 1998. 8 Heerdink ER. Clustering of drug use in the elderly. Population-based studies into prevalence and outcomes [Thesis]. University of Utrecht, 1995. 9 Lau HS. Drug related problems in the elderly [Thesis]. University of Utrecht, 1998. 10 Avorn J, Gurwitz JH. Drug use in the nursing home. Ann Intern Med 1995; 123: 195-204. 11 Pies R, Gorman JM, Gorenstein EE, Katz IR, Rovner BW, Schneider L, Avorn J. Use of psychoactive drugs in nursing homes. New Engl J Med 1992; 327: 1392-3. 12 Llorente MD, Olsen EJ, Leyva O, Silverman MA, Lewis JE, Rivero J. Use of antipsychotic drugs in nursing homes: current compliance with OBRA regulations. J Am Geriatr Soc 1998; 46: 198-201. 13 Johnson RE, Vollmer WM. Comparing sources of drug data about the elderly. J Am Geriatr Soc 1991; 39: 1079-84. 14 Lamy PP. Institutionalisation and drug use in older aldults in the US. Drugs Aging 1993: 3: 232-7.

used in current study 15 Gambassi G, Landi F, Peng L, Brostrup-Jensen C, Calore K, Hiris J, et al. Validity of diagnostic and drug data in standardized nursing home residents assessments. Potential for geriatric pharmacoepidemiology. Med Care 1998; 36: 167-79. 16 Claesson CB, Schmidt IK. Drug use in Swedish nursing homes. Clin Drug Invest 1998; 16: 441-52. 17 Koopmans RT, Van Rossum JM, Van den Hoogen HJ, Hekster YA, Willekes-Bogaers MA, Van Weel C. Psychotropic drug use in a group of Dutch nursing home patients with dementia: many users, long-term use, but low doses. Pharm World Sci 1996; 18: 42-7. 18 Koopmans RT, de Vaan HH, Van den Hoogen HJ, Gribnau FW, Hekster YA, Van Weel C. Changes in drug use during a stay in a psychogeriatric nursing home (in Dutch). Ned Tijdschr Geneeskd 1994; 138: 1122-6. 19 Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Drug utilisation in Dutch nursing homes. Eur J Clin Pharmacol 2000; 55: 765-71. drug drug blood diagnostic levels, results. test pharmacoepidemiologic research pharmacy prescription database laboratory parameters, results, test linkage computer with system, physician care, care, such as hospital care. life style factors. disease-severity. with both exposure and outcome. with SIVIS-database. linkage. out Carry a validation study of each other. each 20 Van Dijk KN, De Vries CS, Van den Berg PB, Dijkema AM, Brouwers JRBJ, De Jong- van den Berg LTW. Constipation as an adverse effect of drug use in nursing home patients: an overestimated risk. Br J Clin Pharmacol 1998; 46: 255-61. 21 Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Occurrence of potential drug-drug interactions in nursing home residents. Int J Pharm Pract 2001; 9: 45-52. 22 Van de Vijver DAMC, Stricker BHCh, Breteler MMB, Roos RAC, Porsius AJ, De Boer A. Evaluation of antiparkinsonian drugs in pharmacy records as a marker for Parkinson’s disease. Pharm World Sci 2001; 23: 148-52. Aspects Requirements for Data available in hospital Recommendations Clinical status Information on diagnoses, biochemical Not available Obtain these data through record- Utilisation of health care Information on utilisation of health Not available Obtain data on hospital stay by record- Quality of life Information on quality of life.Indication for drug use Not available Indication for drug use, Co-morbidity Not available Diseases that might be associated through record-linkage Available This information could be collected on an pharmacy data and Verify SIVIS data against Record data on indication and disease severity. Demographics Age, sex, socio-economic status, Age and sex Record data on life style factors such as smoking. 23 Boogaard RG, Dercksen H. Therapietrouw in het verpleeghuis. Een onderzoek in het kader van de opleiding tot verpleeghuisarts. Verpleeghuis Het Zonnehuis, Zwolle, 1997 (report in Dutch). Discrepancies between Discrepancies data required for pharmacoepidemiological and research data available in hospital pharmacy d prescription Outcomes Confounders Table 3 (cont.): Table Abstract 2.3 Drug utilisation in Dutch nursing homes Objective: To quantify and evaluate drug utilisation in a sample of Dutch nursing homes. Methods: A retrospective analysis of computerised medication data of 2,355 residents aged 65 and over of six nursing homes in the Netherlands was performed. For each therapeutic drug group, the number of users was determined. The ten therapeutic groups used most frequently K.N. van Dijk1,2, C.S. de Vries1,3, P.B. van den Berg1, J.R.B.J. Brouwers1,2, were investigated further. For these, patient characteristics, use of therapeutic subgroups, the 44 L.T.W. de Jong-van den Berg1 average daily dosages, and the chronicity of drug use were determined. Chronicity was expres- 45 sed as the percentage of treatment days divided by the number of residents’ days in the nursing home. 1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen Results: During the study period, 89%, 77% and 56% of the study population used a drug University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, from ATC main group N (central nervous system), A (alimentary tract and metabolism) and C Groningen, the Netherlands (cardiovascular system), respectively. Eight of the ten therapeutic drug groups prescribed most 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands frequently were used for more than 50% of the time. In particular psycholeptic drugs, diurec- 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, tics, and laxatives were used chronically (83%, 81%, and 80% of the nursing home stay, Guildford, United Kingdom respectively). Except for a few drug groups such as laxatives and diuretics, the prescribed daily dosages were relatively low. Twenty-eight percent of the residents received loop diuretics; these were prescribed in relatively high dosages. A slightly modified version has been published in Conclusion: Drug utilisation in the nursing home was high and many drugs were used chroni- European Journal of Clinical Pharmacology 2000; 55: 765-71 cally. In view of the risk of possible side effects and drug-drug interactions, the prescribing and dosage of psycholeptic drugs, laxatives, loop diuretics and ulcer-healing drugs should be re- evaluated. Introduction Methods

Many studies have reported drug utilisation in nursing home residents to be disturbingly Study population high [1-3]. It has been estimated that of prescribed medication, approximately 25-40% is con- The study was conducted in residents aged 65 and over from six nursing homes in the nor- sumed by people over 65 years of age [4,5]. When elderly people are admitted to nursing thern part of the Netherlands. Compared to a national register on nursing home residents in homes, their medication use often increases [6,7]. In part this may be due to the reasons for the Netherlands (SIVIS), the study population had a similar distribution of gender and type of admission to the nursing home, however other studies suggest that the ‘prescribing cascade’, care, although nursing home residents in our study were slightly older (average age 82 in our 46 i.e. the prescription of a new drug to counteract the side effects of another drug, could also be study versus 79 in the SIVIS data) than the Dutch nursing home population. Physician care was 47 a reason [8]. This may lead to an increased frequency of unnecessary polypharmacy and of pos- provided by nursing home physicians who give medical care on a daily basis. From interview sible adverse drug effects [9-11]. Since elderly people often suffer from multiple disorders and data it was shown that nursing, physician, and pharmacist care, as well as food and fluid inta- consequently use many drugs, this population receives much emphasis. Also, the nursing home ke were comparable between the nursing homes [31]. The source population consisted of a environment provides an excellent opportunity for comprehensive drug regimen review [12]. dynamic cohort of 2,772 residents who were present at any time during the two-year study Special programs have been developed and implemented to improve drug utilisation in the period from 1 October 1993 to 1 October 1995. The average annual turnover rate (mostly due to community-dwelling elderly [13] and in nursing home residents [14,15]. Furthermore, several mortality) was 40%. groups have developed or applied prescribing indicators with the aim to create means to systematically assess medication appropriateness and thus a starting point to improve prescribing Data collection [16-23]. Many of these indicators were developed for assessing medication appropriateness in For each resident, pharmacy records and individual resident characteristics were collected. elderly outpatients, rather than nursing home residents. Beers’ criteria have been developed Pharmacy data included the generic name, strength, dosage, the frequency of use, the route of for elderly outpatients in the United States and are not necessarily representative for European administration, and the duration of drug use (in days) of each prescribed drug. This type of data pharmacotherapy standards. For example, according to Beers’ criteria trimethobenzamide, has been demonstrated to be an adequate source of information of the prescription drugs taken reserpine, chlorpropamide and dicyclomine use is discouraged [16,23] but in many European by elderly people [32,33]. Furthermore, age, gender, date of admission, and date of discharge countries these drugs are not even available. Therefore, to measure prescribing of these drugs were collected from the pharmacy records. Pharmacy records were linked with a national in not a good indicator for medication appropriateness in Europe. Typically European issues, information system on nursing homes (SIVIS) [34], to collect patient specific data regarding for example, are the prescribing of diuretics, psychotropics and laxatives [24]. To improve pre- morbidity (three diagnoses per resident), and the type of care: psychogeriatric or somatic care. scribing locally, an overview of current prescribing is needed. In Europe, only few studies have Somatic residents usually are characterised by serious physiological chronic disorders, such as been undertaken to describe and evaluate drug use in the elderly [25] and in nursing homes Parkinson’s disease, diabetes mellitus and rheumatoid arthritis. Psychogeriatric residents are [24,26-29] and few settings have the availability of computerised medication data to evaluate characterised by serious mental or psychiatric disorders such as dementia. As a consequence, drug utilisation continuously. pharmacotherapy between these groups will differ. Patient specific SIVIS data are collected The purpose of this study was to evaluate and quantify drug utilisation in six Dutch nursing four times a year by the nursing home staff, and subsequently these data are registered ano- homes. In relation to patient characteristics and published guidelines [30], frequency of drug nymously on a national basis. use, drug groups, daily dosages of relevant drug groups and chronicity of drug use are studied. This study highlights areas that deserve attention in prescribing practices in nursing homes. Data handling After identifying the pharmacotherapeutic domains that comprise the most serious problem Residents whose pharmacy records could not be linked to data from the SIVIS system areas, feedback may be provided to improve pharmacotherapy. (14.2%) and subsequently, residents whose period of residence could not be defined (1%) were excluded. The excluded residents did not differ from the other residents with respect to age, 400

gender or type of care. This resulted in a final study population of 2,355 residents. 350

Drugs were classified according to the Anatomical Therapeutic Chemical (ATC) classifica- 300 tion system [35]. Dosages were calculated as Defined Daily Dose (DDD) values, defined by the 250 World Health Organisation (WHO) [36], and Prescribed Daily Dose (PDD) values were determined for each prescribed drug. The PDD value is the daily dosage of drugs, expressed as the 200

daily number of DDDs that is actually prescribed; i.e. the daily dosage (in mg) divided by the 150 DDD (in mg) [37]. The fact that drug volume, or quantities of drug use, are expressed as a com- 100 48 parable unit of pharmacological efficacy rather than for example the number of milligrams or 49 prescriptions dispensed enables us to compare daily dosages between different drugs [38]. 50

When the PDD is greater than 1, the prescribed daily dosage is relatively high relative to WHO 0

0-25 26-50 51-75 76-100 guidelines. A PDD less than 1 indicates a relatively low daily dosage. Drugs that do not have a 101-125 126-150 151-175 176-200 201-225 226-250 251-275 276-300 301-325 326-350 351-375 376-400 401-425426-450 451-475476-500 501-525526-450 551-475576-600 601-525626-550 651-675 676-700 701-730 DDD value in the ATC-coding system such as injections and dermatological preparations and Figure 1: Duration of stay in nursing home study population (n=2,355) drugs that were prescribed ‘as needed’ (5% of all prescriptions), were left out when average PDD values were calculated. Table 1: Characteristics of the study population (n=2,355)

Drug utilisation Variable Number of residents Initially, all prescribed main drug groups were analysed on the levels of ATC anatomical (n) (%) main group (first level) and therapeutic group (second level). The number of users and the Age (years) 65-69 127 5 number of users who used these drugs for more than 50% of the nursing home stay were 70-74 288 12 determined for these drug groups. Of the ten therapeutic categories prescribed most frequent- 75-79 404 17 ly, further analyses were performed on the level of therapeutic ATC subgroups (third level). For 80-84 608 26 each therapeutic ATC subgroup the chronicity of pharmacotherapy and average and median 85-89 574 24 90-94 274 12 PDD values were studied. To obtain insight in the duration of drug use in relation to the period > 94 80 3 of stay in the nursing home, for each resident and for each drug the chronicity of pharmaco- Gender therapy was expressed as the number of drug utilisation days divided by the number of resi- Male 689 29 dents’ days in the nursing home. Software used was SPSS, version 6.01. Female 1666 71 Type of care Psychogeriatric 700 30 Results Somatic 1609 68 Not known 46 2 Population characteristics Morbidity Parkinson’s disease 151 6 The study population consisted of 2,355 nursing home residents. The mean age of the study Diabetes mellitus 176 7 population was 82 years (SD 7.3). Figure 1 represents the duration of stay in the nursing home Dementia 689 29 for individuals in the study population. The average number of different drugs (based on ATC Depression 40 2 codes; fifth level) per person was 8.9 (SD 4.9) during the total residence time; the average num- Duration of stay in the nursing home (months) < 1 349 15 ber of different drugs per day was 4.9. Other population characteristics are given in table 1. 1-5 990 42 6-11 306 13 12-17 205 9 ≥ 18 505 21 Drug consumption Figure 2 represents the number of residents on drugs from the ATC anatomical main groups, 2500 and the number of residents who received these drugs for more than 50% of their stay in the nursing home. Anatomical main groups A (alimentary tract and metabolism), B (blood and bloodforming organs), C (cardiovascular system), J (general anti-infective agents for systemic 2000 use) and N (central nervous system) were the drug groups from which drugs were prescribed most frequently and, with the exception of antibiotics, on average these drugs were used for 1500 50 more than 50% of the stay in the nursing home. Gastrointestinal drugs used most frequently 51 were laxatives and ulcer-healing drugs: in this population, 56% used laxatives and 24% used

anti-ulcer medication. Drug use from group B consists mainly of anti-thrombotic drugs and 1000 iron, drug use from group C consists mainly of cardiac drugs such as digoxin, anti-arrythmic Number of residents agents, diuretics and angiotensin-converting enzyme (ACE) inhibitors. Non-steroidal anti- inflammatory drugs (NSAIDs) are the only drugs that were used from group M. Drug use from 500 group N consists mainly of analgesics, such as paracetamol and aspirin, benzodiazepines, and antipsychotics. For the ten ATC main groups prescribed most frequently, drug consumption data are represented in descending order of frequency in table 2. From this table, differences in pre- 0 ABCGHJLMNPRSV scribing can be seen by gender (column 4 and 5) and by the type of care that residents receive (psychogeriatric or somatic, column 6 and 7). With respect to gender, striking differences occur ATC main group in the utilisation of antipsychotic agents (ATC code N05A; more frequently used by men) and pain medication (ATC code M01A and N02B; more frequently used by women). With respect to Figure 2: Number of residents for each anatomical therapeutic chemical (ATC) main group; Dark bars show the number the type of care, differences occur in psycholeptic prescribing for psychogeriatric and somatic of residents who use the drug for more than 50% of their duration of stay. A alimentary tract and residents: psychogeriatric residents receive more antipsychotics (59% versus 23%), whereas meta–bolism; B blood and bloodforming organs; C cardiovascular system, G genitourinary system; H hormo- nal preparations; J general anti-infectives; L antineoplastic agents; M musculoskeletal system; N central ner- somatic residents receive more benzodiazepines (ATC code N05C). Next, we studied chronicity vous system; R respiratory system; S sensory organs; V various agents and the daily dosage of drugs. The average chronicity of treatment (column 8) and average and median PDD values (column 9 and 10) are given. From column 8, it can be seen that in these nursing homes, most drugs are used for more than 50% of the nursing home stay. This includes diuretics and anti-coagulant drugs, but also laxatives, hypnotics and sedatives: on an average, 74% of the nursing home population use a psycholeptic drug for an average of 83% of their stay in the nursing home. Adjusting these results for the duration of stay in the nursing home had very little, if any, effect on the results. Leaving out the residents who only stayed for a very short period in the nursing home did not alter the results significantly (both statistical and clinical). Finally, drugs are given in relatively low dosages (column 9 and 10). Exceptions are laxative drugs, antibiotics, diuretics, NSAIDs, and proton-pump inhibitors. In general the mean PDD values are higher than the median PDD values. Discussion

In the nursing homes studied there is much long-term use of various medication types. Generally, prescribed daily dosages are low, which indicates that prescribers are aware of the pharmacokinetic and pharmacodynamic changes in the elderly. To our knowledge, no studies have been performed that study chronicity of drug use for all drug groups in the nursing home. This study shows that -with the exception of antibiotics- once they are on a certain drug, most 52 nursing home residents use these drugs for more than half of their stay in the nursing home. 53 Average Median Even though the authors are unaware of the complete morbidity of the individual residents and utilisation is studied on a population basis, this raises the question whether the residents’ need ‡

city for a drug is re-evaluated from time to time. Psychogeriatric residents use approximately the same drugs as residents in somatic care except for antipsychotics, anticoagulants and ulcer- 0.850.810.740.76 0.96 (0.39) 1.00 1.38 (1.24) 0.96 (0.31) 1.48 (1.42)0.72 1.00 1.000.54 1.00 0.750.69 0.93 (0.48)0.69 0.51 (0.25) 1.00 1.02 (0.43) 0.50 0.87 (0.25) 1.46 (0.52)0.52 1.00 1.00 1.16 0.48 (0.28) 0.48 0.830.680.58 0.71 (0.54) 0.38 (0.51) 0.55 (0.59) 0.51 0.20 0.40 healing drugs. This indicates that, next to their psychological complaints, they have similar somatic complaints as the other nursing home residents. The results with regard to the drug groups studied will be reviewed in the following sections. # # # # # # # # # # # # #

Psycholeptic drugs Psycholeptic drugs are used by 74% of the nursing home residents. Since the nursing ug category, the ug number category, of female users of this category per 1000 female residents

/1000 somatic/1000 homes offer psychogeriatric care facilities, utilisation of this drug group was expected in this † 466 471159381 0.54 157 369 0.39 (0.29) 0.72 0.33 0.49156 0.61 (0.37) 1.03 (0.49) 178 0.50 1.00 0.61 0.55 (0.38) 0.43 589 231

care of Type Chroni patient group. However, drug use from this group is more than 70% in both psychogeriatric and # # # # # in somatic care residents. A major part of this drug group are the benzodiazepines, especially the hypnotics and sedatives. In accordance with prescribing guidelines in the Netherlands, the prescribed daily dosages are about half the advised adult dosage [39]. However, Dutch prescribing guidelines also state that it is suboptimal to prescribe these drugs for more than 30 days, since the drugs become less effective but the adverse effects remain [39]. This part of the guidelines clearly is not followed. In view of previous studies that have demonstrated an increased risk of falls and fractures in the elderly [40,41] and in view of other adverse effects such as residents 1000* 1000* PDD (SD) PDD drowsiness that directly influence the residents’ quality of life, it would pay to re-evaluate the need for these drugs in those residents. However, we are aware of the fact that withdrawal from benzodiazepines is often difficult to achieve [42]. ATC codeATC Number of Male/ Female/ N06AB 91 (4) 28 43 33 42 0.56 0.89 (0.26) 1.00 J01 1183 (50) 517 496 531 484 0.12 1.14 (0.42) 1.00 Laxative drugs Constipation is a well-known complaint in the elderly. It could result from an impaired bowel function due to immobility, decreased fluid- and fibre intake, and, sometimes, the use of drugs with anti-cholinergic properties [31]. In this population, laxatives are used by more than || Number of residents for the top-10 ATC therapeutic main groups in Number the ATC of study populationfor residents the top-10 (n=2,355) -receptor -receptor antagonists A02BA 341 (14) 157 140 113 156 2 other 68 (3) 20 32 44 22 Thiazides diureticsLoop Other C03C C03AAntacidsDrugs for treatment of peptic ulcer 668 74H pump Proton inhibitors (28) (3) A02BC 284 A02B A02A 22 372 256 126 35 233 (16) 437 196 (5) 129 20 (19) (8) 58 170 200 308 87 52 179 82 37 26 133 59 65 207 93 PsychotropicsAnxiolytics and Hypnotics sedatives N05A N05BOpioidsOther analgesics and antipyretics 813 N05C (35) 665 418 (28) 1262 N02A N02B 296 315 (54) 277 511 339 1112 363 546 (14) (47) 497 158 415 243 138 496 133 551 0.77 152 (0.28) 0.74 0.21 0.59 0.33 (0.21) 0.30 Tricyclic antidepressantsTricyclic SSRIs N06AA 283 (12) 110 124 104 127 0.58 0.42 (0.25) 0.33 antirheumatic products Antianemic preparationsPsychoanaleptics B03 N06 521 (22) 406 206 (17) 227 144 229 184 209 0.64 0.65 (0.40) 0.67 Antithrombotic agents B01Antiinflammatory and 1230 (52) M01 514 526 883 340 (37) 321 605 397 † PG: psychogeriatric care ‡ chronicity was defined as the number of treatment days divided by the number of patient days in the nursing home || SSRIs: selective serotonin reuptake inhibitors # Statistically significant; test, Chi-square p<0,05 Legend to Table 2: Legend to Table * the male/1000: for number each drug category, of male users of this category per 1000 male female/1000: residents; for each dr Antibacterials for systemic use Table 2: Table Diuretics C03 973 (41) 383 426 374 431 Psycholeptics Psycholeptics N05 1733 (74) 739 735 791 709 Drug group Drug n (%) PG LaxativesAnalgesics A06 N02 1308 1241 (56) (53) 543 492 561 541 543 524 558 525 0.80 0.52 1.48 (0.95) 0.51 (0.27) 1.09 0.50 Antacids, drugs for treatment of peptic ulcer and flatulence A02 563 (24) 263 229 173 265 half of all residents for 80% of the nursing home stay. Like other studies, our data suggest that tics in dosages that extend well beyond the low dose range. Ulcer-healing drugs form an inte- laxatives are overused in institutions [43]. Although non-pharmacological approaches such as resting group in this population: the average daily dosage increases with increasing effective- adequate fluid- and fibre intake and physical exercise are considered beneficial [44], these ness of the prescribed drugs. Antacids are used by 8% of the population with an average PDD

approaches are often difficult to perform in the nursing home population. To decrease laxative of 0.51. Histamine H2-antagonists are used by 14% of the population with an average PDD of use and improve bowel function in the institutionalised elderly, an individual approach that 0.87. Proton-pump inhibitors are used by 5% of the population with an average PDD of 1.46. considers both pharmacological and non-pharmacological interventions is recommended. The reason why proton-pump inhibitors are prescribed in higher dosages than recommended is unknown. Again, more in-depth study of individual patient records is needed: do prescribers

54 Analgesics use antacids, H2-antagonists and H. pylori eradication optimally before the step towards pro- 55 The analgesic prescribed most frequently is paracetamol. Again, low dosages are given. As ton-pump inhibitors is made? According to Dutch guidelines [30], the latter should be saved as expected, opiates are given less frequently and less chronically than non-opioid analgesics, a final alternative; the prescribing pattern in this population suggests that this alternative may which seems rational [30]. Opioids may be helpful for relieving moderate to severe pain, espe- be used to solve reflux and gastric acid complaints. Although they are used quite frequently, cially nociceptive pain [45]. NSAIDs are used by 37% of the residents, which is 10% less than prescribing of antianaemic drugs does not seem exceptional from the data available. use of analgesics such as paracetamol. This seems appropriate [46], especially when the Antidepressant use, finally, stands out because many residents use tricyclic antidepressants NSAIDs are used as alternatives when paracetamol is not effective enough (e.g. for rheumatoid (TCAs). In the treatment of depression, the use of TCAs is questionable in the elderly in view of arthritis). The average PDD value is 1.03, which, in view of the risk of hypertension and renal unwanted adverse effects [30,43]. In some countries, the selective serotonin re-uptake inhibi- failure, is quite high for the elderly [47,48]. If prescribers are unaware of this, a reminder could tors (SSRIs) and monoamine oxidase inhibitors have superseded the TCAs for use in the elder- be given that paracetamol may be given in higher dosages (4 g/day maximum). ly [43], although data on their efficacy or adverse effects in frail, institutionalised elderly persons are inadequate [12]. Furthermore, TCAs are prescribed in relatively low dosages, which may Other drugs indicate that they are prescribed mainly for neuropathic pain disorders. All antidepressants are As expected, anticoagulant drugs are given chronically. Fifty percent of the nursing home prescribed for more than 50% of the time, which is considered rational in view of the time nee- residents use an antibiotic drug at any time during their stay; they are not used chronically, and ded to establish an antidepressive effect [30]. they are given in normal daily dosages (PDD=1) which usually also is desirable in this population. Use of diuretic drugs is more surprising: together with beta-blockers, thiazides are the Limitations drugs of first choice for the treatment of secondary hypertension [30]. They are used by 3% of Biases, to which this study may be subject, all boil down to the completeness of the data. nursing home residents; 16% use ‘other diuretics’ that include combination preparations of All residents for whom data were suspected to be incomplete because they could not be linked thiazides and potassium-sparing agents such as triamterene. Many more residents use loop- to the SIVIS database or because they were in the database but it was unclear when they ente- diuretics, the use of which in the elderly has been discouraged because of too severe blood red or left the nursing home, were excluded from the study. Since these residents did not differ pressure lowering resulting in needless postural hypotension, and, in some cases, stroke [49]. from the other residents with respect to demographic characteristics, no bias is expected from The average PDD value is 1.48, which indicates that the drugs are prescribed in relatively high exclusion of this subgroup. For the calculation of average PDD values, all medications which dosages. This calls for more in-depth research as to why prescribers choose loop diuretics so had been prescribed ‘as needed’, were not included in the calculations. This concerned 5% of often, why they are prescribed in such high dosages and whether prescribers are aware of the the prescriptions; they were mainly hypnotics, analgesics and laxative drugs. It will lead to a advice to be cautious with loop diuretics prescribing in the elderly. Furthermore, the average slight underestimation of the average PDD calculated for the drug groups concerned. dose of thiazides is surprising. Considerable evidence supports the efficacy of low doses of Calculations of the number of users and chronicity of drug use will not be affected. Other than thiazide diuretics in the treatment of hypertension in elderly people [30,50]. The average PDD, that, the data are complete with respect to prescription drug utilisation: the database origina- found in the study presented here (0.96), suggests that nursing home residents receive diure- tes from a drug-dispensing database and, therefore, it is continuously updated and kept adequate as a result of its main purpose. Next, nursing staff makes sure that each patient takes his References medication. Although use of over-the-counter (OTC) medication has not been quantified, we 1 Tamblyn RM, McLeod PJ, Abrahamowicz M, et al. Questionable prescribing for elderly patients in Quebec. expect this to be relatively low due to practical reasons such as immobility of the residents and CMAJ 1994; 150: 1801-9. continuous medical attention by both nursing and medical staff. Further, although fluid- and 2 Stewart RB. Poly-pharmacy in the aged: practical solutions. Drugs Aging 1994; 4: 449-61. food supplies are comparable between the nursing homes, no information is available on fluid- 3 Gill K, Hermans J, Vermeij P. Multiple drug use by the elderly in need of care and nursing and possibilities of reducing this practice (in Dutch). Ned Tijdschr Geneeskd 1996; 140: 1076-80. and food intake on an individual patient level. With the exception of laxative drug utilisation 4 Council on Scientific Affairs, American Medical Association. Report of the Council of Scietific Affairs, American review, this is not considered highly important for the drug utilisation study described. In the Medical Association. White paper on elderly health. Arch Intern Med 1990; 150: 2459-72. 56 case of laxative drugs, it would be useful to study fluid- and fibre intake on the individual resi- 5 Chrischilles EA, Foley DJ, Wallace RB, et al. Use of medications by persons 65 and over: data from the 57 dents’ level to determine whether dietary changes could lead to diminished laxative use. established populations for epidemiologic studies of the elderly. J Gerontol 1992; 47: M137-44. 6 Wayne SJ, Rhyne RL, Stratton M. Longitudinal prescribing patterns in a nursing home population. In conclusion, this drug utilisation study shows that drug use in the nursing home is high, J Am Geriatr Soc 1992; 40: 53-6. many drugs are used chronically and prescribed dosages are relatively low. Priorities for impro- 7 Van Zuylen C, Oostendorp FMGM, van Beusekom BR, Cools HJM, Bolk JH, Lighart GJ. Increasing use of vement should be given to the prescribing of benzodiazepines, laxatives, loop-diuretics and medication in nursing homes (in Dutch). Ned Tijdschr Geneeskd 1988; 132: 1692-5. 8 Rochon PA, Gurwitz JH. Optimising drug treatment for elderly people: the prescribing cascade. ulcer-healing drugs. In case of benzodiazepine prescibing, the high number of users (54%) and BMJ 1997; 315: 1096-9. the long-term use deserves attention. Possibilities for tapering drug use should be investiga- 9 Ackermann RJ, Meyer von Bremen GB. Reducing polypharmacy in the nursing home: an activist approach. ted. Attention should also be given to laxative use in nursing homes: besides the high percen- J Am Board Fam Pract 1995; 8: 195-205. 10 Colt HG, Shapiro AP. Drug-induced illness as a cause for admission to a community hospital. J Am Geriatr Soc tage of users (56%), we found that relatively high dosages were used. The number of residents 1989; 37: 323-6. who received loop diuretics was relatively high (28%) and, again, relatively high dosages were 11 Monette J, Gurwitz JH, Avorn J. Epidemiology of adverse drug events in the nursing home setting. Drugs Aging used. Feedback to prescribers is necessary to evaluate the necessity of this practice. In view of 1995; 7: 203-11. possible adverse effects, the possibility of parallel prescribing and drug-drug interactions, the 12 Avorn J, Gurwitz JH. Drug use in the nursing home. Ann Intern Med 1995; 123: 195-204. 13 Hunter KA, Florio ER, Langberg RG. Pharmaceutical care for home-dwelling elderly persons: a determination of use of these drug groups should be re-evaluated carefully. need and program description. Gerontologist 1996; 36: 543-8. 14 Schmidt I, Claesson CB, Westerholm B, Nilsson LG, Svarstad BL. The impact of regular multidisciplinary team Acknowledgements interventions on psychotropic prescribing in Swedish nursing homes. J Am Geriatr Soc 1998; 46: 77-82. 15 Beers MH, Fingold SF, Ouslander JG. A computerized system for identifying and informing physicians about problematic drug use in nursing homes. J Med Syst 1992; 16: 237-45. We express our gratitude to D.A. Bloemhof, RPh, for supplying pharmacy data; A.M. 16 Beers MH, Ouslander JG, Rollingher I, Reuben DB, Brooks J, Beck JC. Explicit criteria for determining Dijkema, RPh, for her valuable work interviewing the nursing homes’ staff ; SIG Informatics on inappropriate medication use in nursing homes. Arch Int Med 1991; 115: 1825-32. 17 Hanlon JT, Schmader KE, Samsa GP, Weinberger M, Uttech KM, Lewis IK, et al. A method for assessing drug Health and Welfare, Utrecht, for supplying data on patient characteristics; and nursing, medi- therapy appropriateness. J Clin Epidemiol 1992; 45: 1045-51. cal and pharmacy staff from all participating nursing homes for their co-operation. 18 Hanlon JT, Weinberger M, Samsa GP, Schmader KE, Uttech KM, Lewis KL, et al. A randomized, controlled trial of a clinical pharmacist intervention to improve inappropriate prescribing in elderly outpatients with polypharmacy. Am J Med 1996; 100: 428-37. 19 Oborne CA, Batty GM, Maskrey V, Swift CG, Jackson SHD. Development of prescribing indicators for elderly medical inpatients. Br J Clin Pharmacol 1997; 43: 91-7. 20 Schmader KE, Hanlon JT, Landsman PB, Samsa GP, Lewis IK, Weinberger M. Inappropriate prescribing and health outcomes in elderly veteran outpatients. Ann Pharmacother 1997; 31: 529-33. 21 Shelton PS, Hanlon JT, Landsman PB, Scott MA, Lewis IK, Schmader KE, et al. Reliability of drug utilization evaluation as an assessment of medication appropriateness. Ann Pharmacother 1997; 31: 533-42. 22 Aparasu RR, Fliginger SE. Inappropriate medication prescribing for the elderly by office-based physicians. Ann Pharmacother 1997; 31: 823-9. 23 Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. An update. Arch Intern Med 1997; 157: 1531-6. nonsteroidal anti-inflammatory drug therapy. JAMA 1994; 781-6. 24 Koopmans RTCM, de Haan HH, van den Hoogen HJM, Gribnau FW, Hekster YA, van Weel C. Changes in drug use 49 Kumar PJ, Clark ML. Clinical Medicine 2nd Ed. Ballière Tindall, London, 1990. during stay in a psychogeriatric nursing home (in Dutch). Ned Tijdschr Geneeskd 1994; 138: 1122-6. 50 Freis ED, Papademetriou V. Current drug treatment and treatment patterns with antihypertensive drugs. 25 Nobili A, Tettamanti M, Frattura L, Spagnoli A, Farraro L, Marrazzo E, et al. Drug use by the elderly in Italy. Drugs 1996; 52: 1-16. Ann Pharmacother 1997; 31: 416-22. 26 Claesson CB, Schmidt IK. Drug use in Swedish nursing homes. Clin Drug Invest 1998; 16: 441-52. 27 Koopmans RTCM, van Rossum JM, van den Hoogen HJM, Hekster YA, Willekens-Bogaers MAJH, van Weel C. Psychotropic drug use in a group of Dutch nursing home patients with dementia: many users, long-term use, but low doses. Pharm World Sci 1996; 18: 42-7. 28 Vander Stichele RH, Mestdagh J, Van Haecht CH, De Potter B, Bogaert MG. Medication utilization and patient 58 information in homes for the aged. Eur J Clin Pharmacol 1992; 43: 319-21. 59 29 Roberts MS, King M, Stokes JA, Lynne TA, Bonner CJ, McCarthy S, Wilson A, Glasziou P, Pugh John W. Medication prescribing and administration in nursing homes. Age Ageing 1998; 27: 385-92. 30 Thomas S, Geijer RMM, van der Laan JR, Wiersma T. Guidelines for the physician II (in Dutch). Bunge, Utrecht, 1996. 31 Van Dijk KN, de Vries CS, van den Berg PB, Dijkema AM, Brouwers JRBJ, De Jong-van den Berg LTW. Constipation as an adverse effect of drug use in nursing home patients: an overestimated risk. Br J Clin Pharmacol 1998; 46: 255-61. 32 Johnson RE, Vollmer WM. Comparing sources of drug data about the elderly. J Am Geriatr Soc 1991; 39: 1079-84. 33 Lau HS, de Boer A, Beuning KS, Porsius A. Validation of pharmacy records in drug exposure assessment. J Clin Epidemiol 1997; 50: 619-25. 34 SIG Informatics in Health and Welfare, Utrecht, the Netherlands 35 World Health Organisation Collaborating Centre for Drug Statistics Methodology, Oslo. Anatomical Therapeutical Chemical (ATC) classification index including defined daily doses (DDDs) for plain substances. Oslo: World Health Organisation Collaborating Centre for Drug Statistics Methodology, 1997. 36 Wertheimer AI. The defined daily dose system (DDD) for drug utilisation review. Hosp Pharm 1986: 21: 233-58. 37 Merlo J, Wessling A, Melander A. Comparison of dose standard units for drug utilisation studies. Eur J Clin Pharmacol 1996; 50: 27-30. 38 Bogle SM, Harris CM. Measuring prescribing: the shortcomings of the item. BMJ 1994; 308: 637-40. 39 Knuistingh Neven A, Graaff de WJ, Lucassen PLBJ et al. Dutch College of General Practitioners-guideline ‘Insomnia and hypnotics’ (in Dutch) Huisarts Wet 1992: 35: 212-9. 40 Ryynanen OP, Kivela SL, Honhanen R, Laippala P, Saano V. Medications and chronic disease as risk factors for falling injuries in the elderly. Scand J Soc Med 1988; 21: 264-71. 41 Herings RMC, Stricker BHC, Boer de A, Bakker A, Sturmans F. Benzodiazepines and the risk of falling leading to femur fractures. Arch Intern Med 1995; 155: 1801-7. 42 Busto U, Sellers EM, Naranjo CA, Capell H, Sanchez-Craig M, Sykora K. Withdrawel reaction after long-term use of benzodiazepines. N Eng J Med 1986; 315: 854-9. 43 Seppälä, Sourander L. A practical guide to prescribing in nursing homes. Avoiding the pitfalls. Drugs Aging 1995; 6: 426-35. 44 Towers AL, Burgio KL, Locher JL, Merkel IS, Safaeian M, Wald A. Constipation in the elderly: influence of dietary, psychological, and physiological factors. J Am Geriatr Soc 1994; 42: 701-6. 45 Anonymous. New guidelines on managing chronic pain in older persons. JAMA 1998: 280: 311. 46 Ferrell BA. Pain evaluation and management in the nursing home. Ann Intern Med 1995; 123: 681-7. 47 Solomon DH, Gurwitz JH. Toxicity of nonsteroidal anti-inflammatory drugs in the elderly: is advanced age a risk factor? Am J Med 1997; 102: 208-15. 48 Gurwitz JH, Avorn J, Bohn RL, Glynn RJ, Monane M, Mogun H. Initiation of antihypertensive treatment during 2.4 Occurrence of potential drug-drug Abstract interactions in nursing home residents Objective: It has been suggested that elderly people are at an increased risk of drug-related problems such as drug-induced adverse effects, drug-drug interactions and drug-disease interactions. This is particularly the case for nursing home residents because of the often complica- K.N. van Dijk 1,2, C.S. de Vries 1,3, P.B. van den Berg 1, J.R.B.J. Brouwers1,2, ted and multiple co-morbidity that occurs in these people. The aim of this study was to deve- L.T.W. de Jong-van den Berg 1 lop prescribing indicators to assess systematically the occurrence and nature of potential drug- 60 drug interactions (DDIs) in a cohort of Dutch nursing home residents. 61 Methods: The study was conducted in residents aged 65 years and over in six nursing homes 1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen (n=2,355, two-year study period). Computerised medication data for the residents were evalu- University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, ated with respect to co-prescribing of potentially interacting drugs. All DDIs that were classi- Groningen, the Netherlands fied as clinically relevant according to the Dutch National Drug Interaction Database were stu- 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands died. DDIs were classified into three categories according to their pharmacological mechanism: 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, 1- pharmacokinetic interactions at the level of gastrointestinal (GI) absorption, 2- pharmacoki- Guildford, United Kingdom netic interactions at the level of metabolism and excretion and 3- pharmacodynamic interactions. Results: Thirty-two percent (n=748) of all residents were exposed to one or more combinations International Journal of Pharmacy Practice 2001; 9: 45-52 of drugs that could lead to clinically adverse outcomes. The numbers of residents who received drug combinations with a mechanism of interaction from category 1, 2 or 3 were 73 (3%), 164 (7%) and 612 (26%) respectively. The number of medications prescribed was significantly associated with the occurrence of a potential DDI (p<0.05). Drug groups most frequently involved were oral anticoagulants, antibiotics and theophylline. Conclusion: During the two-year study period, about one-third of the residents were exposed to at least one drug interaction considered clinically relevant. Adequate surveillance systems are needed to enable better identifications of these interactions with a view to preventing potential problems. Using the prescribing indicators developed in this study, such surveillance could focus on detection and clinical aspects of potential DDIs and possible alternative treat- ments. Introduction as the number of patients with DDIs per total number of patients [29]. Consequently, the use of a more uniform way of expressing the incidence or prevalence of DDIs has been recommended Elderly people are at an increased risk of drug-related problems such as drug-induced [29]. The duration of concomitant drug use also needs to be taken into account: long-term con- adverse effects, drug-drug interactions and drug-disease interactions [1-5]. This is particularly comitant use may indicate that in daily clinical practice no problems have occurred. the case for nursing home residents because of the often complicated and multiple co-morbi- This study aimed to use computerised pharmacy prescription data to develop prescribing dity that occurs in these people [5-9]. To address this problem, several approaches have been indicators for DDIs and measure their occurrence, nature and duration in a sample of Dutch made towards rational and appropriate prescribing of drugs in the institutionalised elderly. nursing home residents. Such prescribing indicators could subsequently be used to audit pre- 62 Prescribing indicators have been developed or applied with the aim of systematically assessing scribing practices in the elderly and to monitor potential adverse drug reactions arising from 63 medication appropriateness and thus providing a starting point for improvement of prescribing DDIs. [10-23]. One of the prescribing indicators used is the occurrence of potentially inappropriate drug combinations [15,20-23]. A drug-drug interaction (DDI) is defined as ‘a pharmacological or Methods clinical response to the administration of a drug combination different from that anticipated from the known effects of the two agents when given alone’ [24]. DDIs can lead to unintended Potential drug-drug interactions responses such as enhanced or reduced drug effects and these effects vary between individu- Information on the relevance of potential DDIs was obtained from the Dutch National Drug als. Drug-drug interactions are commonly divided into pharmacokinetic and pharmacodynamic Interaction Database [35]. Where available, the DDI information in this database is derived DDIs [25,26]. Elderly people may be at a higher risk of the adverse effects of a DDI due to phar- from international reference books, such as Hansten and Stockley [36,37]. Based on these macokinetic, pharmacodynamic, and disease-related changes that occur with advanced age books, in the database DDIs are divided into ‘clinically relevant’ DDIs (n=175) and ‘clinically less [2,3,5]. Risk factors associated with the occurrence of potential DDIs are age, number of medi- relevant’ DDIs (n=74). A ‘clinically relevant’ DDI indicates that immediate action should be cations prescribed, the number of physicians involved, and the presence of increased frailty [2]. taken, such as adjustment of dosage regimes, or suggesting an alternative drug to the prescri- The impact of DDIs in nursing homes is reported to be high: DDIs may account for 22% of all ber. For a DDI that is ‘clinically less relevant’ no immediate action is necessary. Only the 175 cli- adverse drug reactions reported, or adversely affect 23% to 53% of all residents [5]. The inci- nically relevant DDIs were studied. DDIs were classified into three categories according to dence of hospital admissions caused by DDIs has been reported to range from 0% to 11.5% pharmacological mechanism: (1) pharmacokinetic DDIs at the level of gastrointestinal absorp- [27,28]. These percentages vary due to differences between study populations, use of different tion, (2) pharmacokinetic DDIs at the level of metabolism and excretion, and (3) pharmacody- definitions of a DDI, different ways of establishing cause-and-effect relationships, and diffe- namic DDIs. The classification is shown in table 2. rences in study design. Several studies have been published on frequencies of potential DDIs in different popula- Data collection tions [28-34]. In a review of 7 studies, the frequency of potential DDIs was found to range from The study was conducted among residents aged 65 and over in six nursing homes, each 9.2% to 70% in ambulatory patients [29]. In hospitalised patients, reports of frequencies of with a 90 to 225-bed capacity. The study population consisted of 2,355 residents present at any potential DDIs ranged from 2.2% to 60% [28,29]. In nursing home residents, the proportion of time during the two-year study period (1 October 1993 to 1 October 1995). In this study, phar- residents exposed to a potential DDIs has been reported to range from 23.4% to 49% [29]. macy records of the nursing home residents were linked with a national information system on These large variations in reported frequencies are mainly due to methodological considera- nursing homes (SIVIS), which contains patient-specific information on morbidity and type of tions, such as the use of different definitions of a clinically significant DDI and use of different nursing (psychogeriatric or somatic) of virtually every nursing home resident in the reference lists for DDIs (sometimes no references are given), differences in study design, and Netherlands. The databases and drug use in this population have been described in detail differences in the way of measuring the frequency or incidence of DDIs. For example, the fre- [38,39]. The drug dispensing system in the nursing homes results in medication prescribing quency of DDIs can be expressed as the total number of DDIs per total number of patients or being recorded in the pharmacy computer system and updated with medication changes on a daily basis. Nurses dispense medication to individual nursing home residents on the basis of ses it was found that the following variables were associated with the occurrence of a DDI: the information (drug, dosage, route and time of administration) in this computer system. As a number of medications prescribed, the type of nursing psychogeriatric or somatic) and consequence, the recording of actual drug use can be considered very accurate. At the time of Parkinson’s disease. the study there was no automatic signal generation by the system when potential DDIs occurred, but nursing home physicians and hospital pharmacists checked medication files on a daily In Table 2 detailed information is presented on the potential DDIs. The DDIs to which most basis for medication changes. residents were exposed comprised the interaction between loop diuretics and non-steroidal anti-inflammatory drugs (NSAIDs), and the interaction between oral anticoagulants and 64 Data analysis NSAIDs (9.7% and 9.6% respectively). All other DDIs found in this study occurred in less than 65 A retrospective cohort study was performed to estimate the prevalence of potential DDIs 5% of the study population. The percentage of index drug users most frequently exposed to a and the possible risk factors associated with the occurrence of potential DDIs. We developed potential DDI were users of ACE-inhibitors, fluoride, oral anticoagulants, acetazolamide, phe- prescribing indicators based on the frequency, nature and duration of DDIs. For each DDI, an nytoin, and loop diuretics. index drug and an interacting drug were defined. The index drug was defined as a drug of which Table 3 provides an overview of the drugs most commonly involved in prescribing of inter- the pharmacological or clinical response is altered by the interference of a second drug (the acting drugs. The index drugs used most often were oral anticoagulant drugs (involved in ten interacting drug). The outcome of interest was the occurrence of a potential DDI, defined as the DDIs), antibiotics (involved in four DDIs), and theophylline (involved in three DDIs). Interacting concomitant use of both index drug and interacting drug for at least one day. The number of drugs most frequently involved were those with metallic ions (iron salts, antacids; involved in residents exposed to each individual DDI was calculated. The prevalence of the DDIs was five DDIs), NSAIDs (involved in three DDIs), diuretics, enzyme inducers (such as carbamazepi- expressed as the number of residents exposed to a DDI divided by the number of index drug ne and phenytion), and enzyme inhibitors (such as verapamil and fluoxetine) (all involved in users. We also calculated the percentage of all residents (n=2,355) affected. For all patients on two DDIs). The number of days that drug combinations were prescribed concomitantly is rela- a specific DDI, the number of days that the interacting drugs were prescribed concomitantly per tively high. Nineteen out of 32 DDIs were prescribed for an average of 50 days or more per 100 100 days of index drug use was calculated. A stepwise logistic regression was performed to days of index drug use. determine predictive variables of the prescribing of interacting drugs likely to cause adverse clinical effects. The statistical software program SPSS 9.0 for Windows (SPSS Inc., Chicago, IL) was used.

Results

Thirty-two per cent (n=748) of all residents were exposed to one or more combinations of drugs that could potentially lead to adverse clinical outcomes. Out of 175 clinically relevant DDIs from the interaction database, 32 drug combinations (18%) were prescribed; the other 143 did not occur in this population. Most DDIs found were based on pharmacodynamic mechanisms. The number and percentage of all residents that received a drug combination from category 1 (level of GI-absorption), 2 (level of metabolism and excretion) or 3 (pharmacodynamic level) was 73 (3%), 164 (7%) and 612 (26%), respectively. Table 1 presents differences between residents with and without DDIs with regard to age, gender, type of nursing, morbidity, and number of different medications prescribed. From the multivariable logistic regression analy- tion.

66 67 ¶ adjusted hepatic metabolism. leading to digoxin intoxication. of Risk subtherapeutic antimicrobial serum concentration. tagmus, diplopia and dizziness. hepatic metabolism. of Risk prolonged bleeding time. of Risk toxic effects nausea. such as drowsiness, hepatic P450 1A2) (cytochrome metabolism. inhibition and protein displacement. of Risk prolonged bleeding time. for for DDI OR § crude 6 (7) 0.3 51 Increased effect of carbamazepine due to reduced clearance. 32 (5) 1.424 (7) 60 1.0 Decreased effect of oral anticoagulant due to induction of 95 due Decreased effect to of enzyme doxycycline induction. index drugusers with population of conco- DDI (%) (n=2355) mitant drug use ¶ (group) Number of % of study % of days Clinical effect of DDI £ £ † with DDI (%)(N=748) without DDI (%) (N=1607) (95% CI) (95% CI) (number of users) Interacting drug ‡ Characteristics of potentialCharacteristics DDIs, listed per category of interaction Characteristics of the Characteristics study population (n=2,355) Category Category 1 (reduced GI-absorption) Category Category 2 (metabolism and excretion) FemaleMalePsychogeriatricSomaticNot known 549 142 199 diseaseParkinson’s (73.4) (19.0) 29 mellitusDiabetes 14 592 (28.9)Dementia 74Depression (3.9) (79.1) (1.9)0-4 (9.9)5-9 144 1010-14 15 or more (19.3) (1.3) 1117 558 490 33 (69.5) (34.7) 200 264 251 (30.5) 122 1017 (4.4) (26.7) 32 (35.3) 102 (33.6) (63.2) (7.6) (2.0) (6.3) 545 1 (reference) 30 1 (reference) (33.9) 0.82 (0.68-1.00) (1.9) 2.29 (1.85-2.82) 0.49 (0.32-0.74) 99 388 744 1 (reference) 376 0.81 (0.65-1.00) 1 (reference) 1.62 (1.19-2.22) (24.1) (46.3) (6.2) (23.4) 2.34 (1.87-2.94) 0.47 (0.38-0.57) 0.29 (0.18-0.46) 0.71 (0.35-1.47) 1.19 (0.84-1.68) 0.72 (0.52-1.00) 1 (reference) 4.17 (2.85-6.11) 23.75 (15.46-36.49) (5.32-11.59) 7.85 0.53 (0.24-1.17) (17.48-42.35) 27.21 4.29 (2.92-6.30) 8.58 (5.78-12.73) 1 (reference) adjusted for type of nursing, Parkinson’s disease, adjusted for and type number of of nursing, different medications Parkinson’s prescribed Total number Total of residents with category 1 DDI: 73 (3% of study population) Index drug Table 2: Table Digoxin (306) (349)Doxycycline Phenytoin (74) Verapamil Enzyme inducers Oral anticoagulants (646) Tamoxifen (87)Carbamazepine Co-trimoxazole (70)Theophylline Enzyme inhibitors Fluoroquinolones 25 (8) 1.1 21 (28) 8 (1.2) 0.9 0.3 62 2 7 (10) 100 inhibits non-renal and of renal Verapamil excretion digoxin, 0.3 Increased effect of Increased effect oral anticoagulantof phenytoin. due of Risk to toxic effects such inhibition as of nys- 8 Increased risk of toxicity due theophylline to inhibition of Doxycycline (349)Doxycycline (121)Fluoroquinolones Metallic ions (antacids and iron salts) Metallic ions (iron salts) 18 (15) 0.8 27 (8) 95 1.1 of Risk subtherapeutic fluoroquinolone serum concentra 88 serum concentration. of Risk subtherapeutic doxycycline Thyroid hormones (81)Thyroid (48)Bisphosphonates Fluoride (18) Metallic ions (iron salts) Oral anticoagulants (646) Metallic ions (antacids, calcium salts and iron) 7 (15) (8)Cefuroxime Bile acids sequestrants 0.3 Metallic ions (antacids and calcium salts) 18 (22) Drugs for the 7 treatment of (39)peptic ulcer 34 0.8 0.3 1 (<1) 1 (13) of Risk of inadequate prevention osteoporosis. 42 <0.1 <0.1 95 of Risk inadequate control of hypothyroidism. 100 100 of Risk of inadequate prevention osteoporosis. effect Reduced of oral anticoagulant. of Risk serum subtherapeutic concentration. cefuroxime Oral Oral anticoagulants (646) Enzyme inducers Oral Oral anticoagulants (646) Co-trimoxazole 42 (6.5) 1.8 4.4 Increased effect of oral anticoagulant due to enzymatic Type of nursingType Morbidity Number of different medications duringprescribed study period Age (years)Gender 82 (sd 7) 82 (sd 7) 0.99 (0.98-1.00) 0.99 (0.98-1.00) ¶ Variable Number of residents Number of residents OR Table 1: Table Table 3: Drug groups most commonly involved in prescribing of interacting drugs

Drug (group) Number of Number of patients % of days of DDIs implicated (n=2355) concomitant drug use§ Index drug (group)‡ Oral anticoagulants 10 304 61 Antibacterial drugs 4 64 93 Theophylline 3 11 10

68 Interacting drug group† 69 Metallic ions 5 71 53 NSAIDs¥ 3397 41 Diuretics 2 199 56 Enzyme inducers£ 25279 Enzyme inhibitors¶ 28 44 and glomerular filtration. and risk of risk peptic ulcer. leads to system increased vasodilatation and strong effects. hypotensive increased bleeding and risk of risk peptic ulcer. anticoagulant. of contractility the heart. (cytochrome P450 2D6) (cytochrome metabolism excretion. hepatic metabolism hepatic metabolism. of Risk prolonged bleeding time. hepatic metabolism. of Risk prolonged bleeding time. hepatic metabolism. hepatic metabolism. of Risk prolonged bleeding time. Legend to Table 3: § expressed as the number of days of concomitant drug use per 100 days of index drug use ‡ defined as the drug of which the pharmacological or clinical response is altered by the interference of a second drug, the interacting drug † defined as the drug that influences the pharmacological or clinical response of the index drug ¥ non-steroidal anti-inflammatory drugs £ carbamazepine, phenobarbitone, phenytoin, rifampicin ¶ fluoxetine, fluvoxamine, verapamil, diltiazem 229 229 (34) 9.7 225 (35) 9.6 41 41 Decreased effect of diuretics due to reduction in renal perfusion Inhibition of aggregationplatelet leading to increased bleeding 4 (1)3 (21) 0.2 0.1 73 48 Increased of risk TCA toxicity due to inhibition of hepatic 2 (3) Increased of risk lithium toxicity due to decreased lithium <0.1 18 Increased of risk toxicity due theophylline to inhibition of ¶ ¥ ¥ ¥ #

Legend to Table 2: ‡ defined as the drug of which the pharmacological or clinical response is altered by the interference of a second drug, the interacting drug † defined as the drug that influences the pharmacological or clinical response of the index drug § expressed as the number of days of concomitant drug use per 100 days of index drug use £ carbamazepine, phenobarbitone, phenytoin, rifampicin ¶ fluoxetine, fluvoxamine, verapamil, diltiazem Category Category 3 (pharmacodynamic interaction) # selective serotonin reuptake inhibitors ¥ Tricyclic antidepressants (283)antidepressants Tricyclic SSRIs Oral Oral anticoagulants (646) NSAIDs (208)ACE-inhibitors NSAIDs (883) Diuretics Oral anticoagulants (646) (low dose) Salicylates Oral anticoagulants (646) Corticosteroids hormones Thyreoid agentsBeta-blocking (167) Verapamil/diltiazem diuretics Potassium-sparing (364) (salts) Potassium Hypoglycaemic agents (356) 34 (5.3) (95) 197 Acetazolamide (8) Beta-blocking agents 1.4 8.4 number Total of residents with category 3 DDI: 612 (26% of total study population) 21 (3.3) 78 (9) 16 (10) 0.9 Diuretics 65 89 3.3 0.7 14 (4) 87 7 (2) inhibition of aggregationplatelet Irreversible leading to Blocking the renine-angiotensione-aldosterone- activated 55 0.6 94 0.3 function Increased leading thyroid to increased response to oral 38 Increased of risk peptic ulcer. of Risk diminished conductance atrioventricular and reduced 50 3 (38) Increased of risk hyperkalaemia. of hypoglycaemia. awareness Reduced 0.1 4 Increased of risk hypokalaemia. Loop diuretics (668)Loop NSAIDs Lithium (14)Lithium (70)Theophylline Oral anticoagulants (646) NSAIDs Erythromycin Amiodarone Oral anticoagulants (646) Cimetidine (70)Theophylline Oral anticoagulants (646) Enzyme inhibitors Metronidazole number Total of residents with category 2 DDI: 164 (7% of total study population) 2 (3) 2 (<1) <0.1 <0.1 1 (<1) 4 <0.1 100 1 (<1) 100 Increased effect of oral anticoagulant due to inhibition of <0.1 Increased of risk toxicity due theophylline to inhibition of Increased effect of oral anticoagulant due to inhibition of 4 Increased effect of oral anticoagulant due to inhibition of non-steroidal anti-inflammatory drugs Discussion For individual DDIs the percentage of residents affected was 1% or less. Interactions in this category are almost always clinically relevant because complex formation leads to subthera- In this study we developed prescribing indicators, based on the occurrence, frequency and peutic concentrations of drugs. Sometimes an alternative drug for the interacting drug can be

duration of drug-drug interactions, to describe DDIs in a cohort of nursing home residents. chosen (for example an H2-antagonist instead of an antacid), and sometimes the interacting Although the prescribing indicators were descriptive in nature, they allowed us to identify the drug can be discontinued temporarily during index drug administration (for example iron salts drug groups most frequently involved and residents who were most at risk for being exposed during doxycycline therapy). to a DDI. Thirty-two percent of the nursing home residents were exposed to at least one DDI Practical implications 70 classified as potentially clinically relevant. Of all residents, 26% were exposed to a DDI from The DDIs of this category should be avoided by separating the administration times of the 71 category 3 (pharmacodynamic interaction), which could be relevant especially in this popula- two interacting drugs by a two- to four-hour interval. In practice, this measure is taken fre- tion because of reduced homeostatic mechanisms. For each individual DDI classified as clini- quently, however exact data on the administration times of the drugs in the study population cally relevant, no more than 10% of the residents were affected. This means that although one- were not available. A computerised adjustment of dosage schedules could support appropria- third of the population was exposed to a DDI, there was no specific DDI that could be identified te timing of administration. as potentially harmful to many residents. The more drugs residents were prescribed, the higher became their risk of having a DDI. This is in line with other studies [28,30]. Residents who Pharmacokinetic DDIs at the level of metabolism and excretion were nursed in psychogeriatric wards and residents who were diagnosed with Parkinson’s dis- The DDIs due to metabolism or excretion (category 2) are often considered clinically rele- ease showed a decreased risk for the occurrence of a DDI. Other risk factors were not identified vant, in particular those involving inhibition of cytochrome P450 (CYP450) isoenzymes. Overall, in this study. 7% of the residents in our study were exposed to one or more of the DDIs from category 2. For Other studies have reported the frequency and nature of potential DDIs in nursing home individual DDIs the percentage of residents affected was 3.4% or less. The highest prevalences residents [29-34], although the only study published after 1990 was that of Bergendal [30]. In were found for the potentially increased anticoagulant effect of acenocoumarol or phenpro- their study, potential DDIs were investigated in 5125 mainly elderly patients in nursing homes coumen by the concomitant use of co-trimoxazole and enzyme-inducers, respectively. For these and homes for the elderly in Sweden. They found that 31% of the patients had at least one DDI DDIs, monitoring of the bleeding time (International Normalised Ratio, INR) is warranted, and and that these patients were prescribed significantly more drugs than those without DDIs. The this is common practice in Dutch nursing homes. Among the index drug users, the DDIs most prescribing indicators we present are descriptive in nature and can be used with prescription frequently observed were the interaction between phenytoin and co-trimoxazole (28% of phe- databases. Williams and colleagues [20] developed an index of quality prescribing in general nytoin users) and the interaction between lithium and NSAIDs (21% of lithium users). The lat- practice by investigating the incidence of potential DDIs. They determined an odds ratio as a ter may be clinically important, since renal function deteriorates with age and puts elderly at measure of potential DDIs avoided, comparing the use of cimetidine (which interacts with an increased risk of lithium toxicity. Alternative drugs could be advised, such as paracetamol

many other drugs) with that of non-interacting H2-antagonists in users and non-users of inter- instead of NSAIDs and doxycycline instead of co-trimoxazole. Eight out of 15 DDIs from cate- acting drugs (warfarine, theophylline, phenytoin). Although this is an elegant method of audi- gory 2 had 50 days or more of concomitant drug use per 100 days of index drug use. This could

ting H2-antagonists prescribing, it is not by definition applicable to all other drug groups. mean that, in practice, these DDIs do not lead to clinical problems. Further investigation is nee- Furthermore, drug formularies in nursing homes usually restrict the choice of drugs from a spe- ded to find out if more intense monitoring of drug therapy by means of therapeutic drug moni- cific drug class. toring is necessary. Practical implications Implications for clinical practice The DDIs of this category can be monitored by measuring serum (index) drug levels, for Pharmacokinetic DDIs at the level of gastrointestinal absorption example digoxine, theophylline, and lithium levels. For the DDIs in which oral anticoagulants Overall, 3% of all residents were exposed to DDIs at the level of GI-absorption (category 1). are involved, measuring bleeding time (INR) is warranted. profile, staff pharmacists detected only 20% of the DDIs. The authors recommended compute- Pharmacodynamic DDIs rised drug interaction profiles to be used by pharmacists to ensure recognition of all potential Pharmacodynamic interactions are of particular relevance to the elderly [2]. In this study DDIs. In another study, the value of electronic prescribing for elderly was highlighted [41]. In 26% of all residents were exposed to one or more pharmacodynamic DDIs (category 3). The particular, on-line detection of DDIs during prescribing and suggestion of non-interacting drugs highest prevalence was found for the interaction between loop diuretics and NSAIDs. This could be useful. Recently, national attention has been given to pharmaceutical activities in interaction may be clinically relevant to the elderly, in view of the reduced effectiveness of the Dutch nursing homes. To assess the quality of the medication distribution process and other diuretics. Furthermore, the NSAID-induced reduced renal function may influence other drug pharmaceutical activities, in 1997 the Dutch Health Care Inspectorate carried out a survey 72 therapies. The next interaction seen most often was that between oral anticoagulants and among 33 Dutch nursing homes [42]. A computerised medication surveillance system was ope- 73 NSAIDs, which could lead to an increased risk of bleeding and risk of peptic ulcer. Choosing an rational in only 9 out of 33 nursing homes. Together with the results of our study this indicates alternative analgesic is an option to avoid this interaction. Among the index drug users, the that computerised detection of DDIs in nursing homes is warranted. Furthermore, more insight DDIs most frequently observed were the combination between ACE-inhibitors and diuretics is needed into the clinical relevance of those DDIs classified as ‘clinically relevant’. The fact that (95% of ACE-inhibitor users) and again the combination of oral anticoagulants and NSAIDs in this study long-term concomitant use of interacting drugs was found, raises the question of (35% of oral anticoagulant drug users). The combination of ACE-inhibitors with diuretics is whether clinically relevant side effects are actually seen in the elderly. The prescribing indica- only relevant when ACE-inhibitor use is initiated without a temporary discontinuation of the tors developed in this study provide the tools to audit DDI occurrence in nursing homes syste- diuretic (or the use of a low first dosage of ACE-inhibitor). Feedback on this should be given to matically. prescribers. Practical implications. Acknowledgements The clinical relevance of DDIs of this category can be assessed by monitoring the clinical effects of index drugs, e.g. the decreased effect of loop diurectics that (possibly) results in We wish to thank R. Fijn, pharmacist, for his comments on the manuscript. We express our symptoms of heart failure. Measuring serum potassium levels is warranted in view of the gratitude to D.A. Bloemhof, hospital pharmacist, for supplying pharmacy data, SIG Informatics hyper- or hypokalaemic effects of some DDIs of this category. on Health and Welfare, Utrecht, for supplying morbidity data; and nursing, medical and pharmacy staff from all participating nursing homes for their co-operation. The Wetenschappelijk Clinical relevance Instituut Nederlandse Apothekers (WINAp) financially supported this study. Tamai and colleagues [31] found that half of the 24 suspected interactions in a group of 138 nursing home residents had potential clinical relevance. However only two residents were exposed to a substantial degree of risk. Foxall [34] reported 67 potential DDIs in a group of 106 nursing home patients, of which 25 DDIs were potentially life-threatening. Doucet [28] found that in 14.5% of hospital patients older than 70 years who were exposed to a potential DDI, a documented side effect was found. Although data on the clinical relevance of DDIs are scarce, it is estimated that 10% of potential DDIs result in clinically significant events [2]. This would imply that 3% of our study population, i.e. 71 residents, would be at risk of a clinically significant event. Several methods can be used to alert prescribers and pharmacists to the occurrence of potential DDIs. Electronic or computer-aided prescribing can be a useful tool in the recognition and handling of DDIs. Recently, Weideman and colleagues [40] showed that in an eight-drug Drug Saf 1993; 9: 51-9. References 28 Doucet J, Chassagne P, Trivalle C, et al. Drug-drug interactions related to hospital admissions in older adults: a prospective study of 1000 patients. J Am Geriatr Soc 1996; 44: 944-8. 1 Hughes SG. Prescribing for the elderly: why do we need to exercise caution? 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Epidemiology of drug-drug interactions as a cause of hospital admissions. 2.5 Prescribing indicators as a tool to Abstract evaluate drug use in nursing homes: a pilot study Objective: We aimed to evaluate drug use in 2 Dutch nursing homes (254 residents) by developing and evaluating indicators based on pharmacy prescription data. Methods: We evaluated the prescribing of benzodiazepines, NSAIDs, ulcer-healing drugs, and diuretics. Prescribing indicators were used to identify prescribing that was potentially not K.N. van Dijk 1,2, L.G. Pont 3, C.S. de Vries4, M. Franken1, according to recommendations in national and regional prescribing guidelines. We used both 76 J.R.B.J. Brouwers1,2, L.T.W. de Jong-van den Berg1 descriptive indicators, such as the number and percentage of users, and indicators reflecting 77 potentially suboptimal prescribing, such as use of drugs outside the regional drug formulary, use of more than one drug from the same drug class and prescription of drug dosages above 1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen recommended values. When potentially suboptimal prescribing was found, we verified the fin- University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, dings by means of an interview with one of the prescribers. Groningen, the Netherlands Results: The prescribing indicators we assessed were generally in agreement with national and 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands regional guidelines. However, use of benzodiazepines for more than 30 days and prescribing of 3 Department of Clinical Pharmacology, Groningen University Institute for Drug Exploration NSAIDs without concomitant prescribing of gastroprotective drugs was found in a relatively (GUIDE), Groningen, the Netherlands high percentage of patients. After prescriber interview and patient chart review it was found 4 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, that some prescribing indicators, such as dosages above recommended values, were not always Guildford, United Kingdom indicative for suboptimal prescribing. Conclusion: We found the majority of prescribing to be in line with recommendations upon which we based our prescribing indicators. The prescribing indicators could be used to evalu- Submitted ate prescribing practices, however appropriateness of prescribing was more difficult to assess. For this, clinical information from the prescriber was necessary to be able to fully assess prescribing appropriateness. Introduction teria. Although the remaining criteria could be applied using solely pharmacy data, we perceived them as potentially insensitive measurement instruments, which do not always reflect Appropriateness of prescribing has gained much attention in studies of the quality of health inappropriate prescribing. For example, the use of multiple antipsychotic drugs that was inap- care [1-5]. This is particularly true for elderly and nursing home patients. In view of the high propriate according to these criteria, may be clinically beneficial. Also, the fact that a prescri- rate of drug use, age-related pharmacokinetic and pharmacodynamic changes and multiple co- bing indication is not documented, another indication of suboptimal prescribing according to morbidity, elderly patients are at a higher risk of adverse drug effects (ADEs) [1,2,6,7]. Schmader this study, does not necessarily mean that the drug is being prescribed inappropriately. The fact and colleagues defined appropriate prescribing as the selection of a medication and instruc- that in the Swedish studies more than a quarter of the residents received prescriptions that 78 tions for its use that agree with accepted medical standards [2]. These standards are based on were classified as potentially inappropriate suggests these criteria may have been too unspe- 79 efficacy, adverse drug effects and cost-effectiveness and they are derived from national and cific. The Medication Appropriateness Index (MAI), developed by Hanlon in 1992 [13], was found international guidelines, clinical trials and expert opinion [2]. Today, the concept of evidence- to be the closest to a reliable, standardised and valid instrument for assessing medication based medicine is included in daily medical practice. Evidence-based medicine is not only appropriateness in elderly outpatients [1]. To our knowledge, the MAI has not been used to based on external clinical evidence, but also on individual clinical expertise [8]. We sought to assess medication appropriateness in nursing homes. In view of the differences in drug use and evaluate prescribing practices in Dutch nursing homes by assessing tools that could be used living circumstances between elderly outpatients and nursing home residents, criteria for with pharmacy prescription data only. medication appropriateness are not necessarily the same for both populations. The MAI con- Several tools have been developed to assess the appropriateness of prescribing in the sists of 10 questions assessing the appropriateness of a prescribed medication. For 4 questions, elderly [1,5]. Many of these were developed for assessing medication appropriateness in elder- information on diagnoses is necessary. The other 6 questions might be suitable for use with ly outpatients, rather than nursing home residents. Prescribing indicators used in one health pharmacy prescription data only, such as ‘are there clinically significant drug-drug interactions’ care system are not automatically applicable to other health care systems due to differences in and ‘is there unnecessary duplication with other drug(s)’. However, we considered aspects con- national pharmacotherapy guidelines and drug formularies. Furthermore, for many prescribing cerning directions of use, such as patient leaflets, not to be as relevant to the appropriateness indicators information on clinical status such as laboratory results or diagnoses is necessary, of nursing home prescribing, as nurses ensure adequate administration of the drugs. Recently, making them unsuitable for use with pharmacy prescription data only. Appropriateness crite- Knight and Avorn [5] published a list of 12 quality indicators, based on literature review and ria developed by Beers and colleagues [9] were based on expert consensus. They consisted of expert panel consideration. For 5 quality indicators, clinical information such as drug indica- a list of 23 medications that should be avoided and 13 medication doses, frequencies, or pre- tion, response to therapy or renal function was needed. One indicator concerned a drug not scription duration that generally should not be exceeded. An update, including clinical infor- available on the Dutch market. Another indicator concerned patient education, an item that mation such as information on the prescribing indication and on potassium level monitoring, could be relevant in view of monitoring side effects by caregivers. The quality indicators that was published in 1997 [10]. As Beers’ criteria list several medications that are not available in could be used with pharmacy prescription data only included the availability of a medication the Netherlands or are not in accordance with Dutch pharmacotherapy standards, some of list, periodic drug regimen review, avoidance of drugs with strong anticholinergic properties these criteria cannot be applied to Dutch nursing homes. In 1997, Lunn and co-workers [7] deve- and avoidance of barbiturates, although we consider the latter a less clinically relevant problem loped a set of 18 explicit criteria, based on expert opinion, to identify inappropriate prescribing in view of the limited use of barbiturates in the Netherlands. To assess medication appropria- in 101 nursing home residents in the UK. For 7 of the 18 criteria, information on clinical status teness in nursing homes, indicators that reflect deviations from national pharmacotherapy gui- or diagnoses of the residents was necessary, again making them unsuitable for use with phar- delines and drug formularies should be used [14]. The development of pharmacotherapy gui- macy prescription data only although some of them could be incorporated. Two Swedish stu- delines specifically for the elderly is limited so far. In the Netherlands, initiatives for Dutch nur- dies used criteria that were based on Swedish guidelines for measuring excessive use of psy- sing home patients are currently being developed [15]. chotropic drug use in the elderly [11,12]. In one study [11] the availability of clinical information Our aim was to evaluate drug use in 2 Dutch nursing homes using different prescribing for 4 out of 13 criteria was required, in the other study [12] this was the case for 1 out of 10 cri- indicators based on pharmacy prescription data. In our earlier study among nursing home patients [16], we identified signals that the prescribing and use of benzodiazepines, loop diu- group of diuretics, as the combination of a loop diuretic and a thiazide diuretic may be someti- retics, ulcer-healing drugs and non-steroidal anti-inflammatory drugs (NSAIDs) could poten- mes therapeutically useful in heart failure and hypertension. The appropriateness of drug tially be improved. Therefore, we focused on these drug groups. To assess the utility of the pre- dosage was assessed by comparing the actual prescribed daily dose (PDD) with the recom- scribing indicators we verified the cases of potentially suboptimal prescribing by means of an mended dose for the elderly, expressed as the defined daily dose (DDD [20]). For benzodiaze- interview with one of the prescribers. pines, the recommended dosage for elderly people is 0.5 DDD [21]. For the other drug groups the recommended dosage was set on 1 DDD as no specific recommendation for elderly patients Methods exists. Prescribing of hypnotic benzodiazepines is recommended not to exceed 30 days [18]. 80 This prescribing indicator was assessed for the benzodiazepines only, as for the other drug 81 Setting groups there were no guidelines concerning the duration of therapy. Furthermore, two drug The study was carried out in two nursing homes, one for somatic care (home A; 134 resi- combinations were studied, both concerning NSAIDs. First, the co-prescribing of NSAIDs and dents) and one for psychogeriatric care (home B; 120 residents). Five nursing home physicians loop-diuretics was studied because NSAIDs may decrease the efficacy of diuretics and induce (three in nursing home A and two in nursing home B) provided medical care on a daily basis. congestive heart failure [22]. Second, the co-prescribing of gastroprotective drugs (proton pump Each ward was visited twice a week, and a nursing home physician was on call 24 hours a day. inhibitors) during NSAID therapy was studied. In view of the risks of NSAID therapy in the Both nursing homes were served by the same hospital pharmacy. All drugs dispensed to the elderly [23], not to prescribe a gastroprotective drug concomitantly could be regarded as sub- nursing home residents were registered in the hospital computer system. Any changes in medi- optimal prescribing. cation were updated routinely on a daily basis in the hospital pharmacy computer system and a complete medication history was kept for each individual resident. Medication was administered to individual nursing home residents based on information recorded in the computer sys- Table 1: Drugs listed in the regional drug formulary tem, such as drug, dosage, route and time of administration. Hospital pharmacists carried out Formulary drugs medication surveillance. At the moment of the study there was no computerised medication NSAIDs surveillance available. Ibuprofen Diclofenac Evaluation of drug prescribing by prescribing indicators Diclofenac + misoprostol (fixed combination) Meloxicam We evaluated the prescribing of benzodiazepines, NSAIDs, ulcer-healing drugs, and diure- Naproxen tics and compared them with recommendations in national guidelines and a regional drug for- Ulcer-healing drugs mulary [17-19]. The drug formulary was based on the International Classification of Primary Histamine H2-receptor antagonists Care. We evaluated drug use against this drug formulary [19]. Table 1 presents the drugs listed - Cimetidine in the regional drug formulary. - Ranitidine The prescribing indicators we used fell into two groups, as is shown in table 2. Indicators in Proton pump inhibitors - Omeprazole group (a) were descriptive in nature and as a consequence no optimal value was defined. We used the number and the percentage of users, related to the total number of residents present Benzodiazepines Hypnotics in the nursing home. Group (b) indicators reflected potentially suboptimal prescribing. - Temazepam Examples of these indicators that were applied to all four drug groups were use of drugs out- - Nitrazepam side the formulary and use of more than one drug from the same therapeutic drug class (e.g. Anxiolytics two benzodiazepines or two ulcer-healing drugs). The latter indicator was not applied to the - Oxazepam - Diazepam

Diuretics Furosemide Hydrochlorothiazide Verification of prescribing indicators In a sample (n=25) of patients, reflecting the range of patients in whom the indicators suggested potentially suboptimal prescribing, the medical charts were reviewed together with information from the prescribers to ascertain if prescribing for these patients was indeed suboptimal. The information was collected during an open-structured 3-hour interview.

Results

82 # 83 [5] Evaluation of drug prescribing by prescribing indicators The results are summarised in table 2 and are reported below. Benzodiazepines. Of the residents in nursing home A and B, the percentage of benzodiazepine users was 31% and 28% respectively. Of the benzodiazepine users in nursing home A and B the percentage of hypnotic users was 28% and 16% respectively. The percentage of anxiolytic users was 5% and 13%. The percentage of users that were prescribed daily dosages above 0.5 DDD was 27% and 24% respectively. Two patients were prescribed a non-formulary #

benzodiazepine. Fifteen and 3% of the benzodiazepine users in nursing home A and B respec- [5] tively received more than one benzodiazepine at the same time. The number of benzodiazepine users who were prescribed hypnotic benzodiazepines for more than 30 days was 38 (93%) and 29 (88%). ) NSAIDs. Of the residents in nursing home A and B, the percentage of NSAID users was 10% ¶ and 5%, respectively. The percentage of users that were prescribed dosages above 1 PDD was 50% and 17%, respectively. All NSAIDs prescribed were formulary drugs. There were no # patients with concomitant use of more than 1 NSAID. Twenty-one and 17% of the NSAID users # [7] were prescribed a loop diuretic simultaneously. Seventy-nine (home A) and 100% (home B) of [8] the NSAID users were not prescribed a gastroprotective drug. Diuretics. Of the residents in nursing home A and B, the percentage of diuretic users was 31% and 13%, respectively. The percentage of users that were prescribed dosages above 1 PDD was 17% and 19% respectively. All diuretics prescribed were formulary drugs. Ulcer-healing drugs. Of the residents in nursing home A and B, the percentage of users of ulcer-healing drugs was 25% and 13% respectively. The percentage of users that were prescribed dosages above 1 PDD was 24% and 25% respectively. All ulcer-healing drugs prescribed hypnotics: 37 hypnotics: (27.6) 19 hypnotics: anxiolytics: 7 (5.2) anxiolytics: 15 (15.8) (12.5) 38 (92.7) 29 (87.9) ------were formulary drugs. There were no patients prescribed more than 1 ulcer-healing drug. Home A Home B Home A Home B 11 (26.8) Home A 8 (24.2) Home B Home A Home B ) 41 (30.6) 33 (27.5) 14 (10.4) 6 (5.0) 41 (30.6) 16 (13.3) 34 (25.3) 16 (13.3) 18 | ¥ 18 18 21 Results of Results the of evaluation drug use by means of prescribing indicators in two Dutch nursing homes [ ]= number of patients included in the for verifyinginterview prescribing indicators nursing home A mainly provides somatic care, nursing home B mainly provides psychogeriatric care. defined as the number of patients divided by the number of in residents the nursing home*100 defined as the number of patients divided by the number of users of the drug group*100 b. Indicators potentialassessing suboptimal prescribing (number and percentage of users Combination withCombination loop-diuretic - - 3 (21.4) 1 (16.7) - - - - (number of residents)a. Descriptive prescribing indicators (n=134)Number (% of users (n=120) (n=134)PDD > 1 (n=120) (n=134) - (n=120) (n=134) - (n=120) 7 (50.0) 1 (16.7) 7 (17.1) 3 (18.8) 8 (23.5) 4 (25.0) PDD > 0.5 ¥ ¶ # No combination with gastroprotective drug - - 11 (78.6) 6 (100) - - - - Use of drugs outside formulary Use of > 1 drug from 1 (2.4)same drug class Use > 30 days 6 (14.6) 2 (6.1) 1 (3.0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) - 0 (0) - 0 (0) 0 (0) 0 (0) 0 (0) Table 2: Table Indicator of nursingType home Benzodiazepines NSAIDs Diuretics drugs Ulcer-healing | Verification of prescribing indicators Discussion The medication of 25 patients (all from nursing home A) with potentially suboptimal prescribing was reviewed using the medical charts and subsequently discussed with one of the In this study prescribing indicators based on pharmacy prescription data were used to iden- prescribing nursing home physicians. We selected eight patients who were prescribed an tify prescribing that was not in line with regional or national guidelines. We found that pre- NSAID and a proton pump inhibitor (PPI) concomitantly. We inquired whether the PPI was prescribing practices in 2 Dutch nursing homes were generally in agreement with national prescribed to counteract the gastrotoxicity of the NSAID. Indeed, in two patients the PPI was prescribing guidelines and the regional drug formulary. A discussion of the findings is given below. scribed to treat gastro-intestinal adverse effects of the NSAID. For the other six patients other 84 reasons for prescribing a PPI existed. Two patients had a hernia diaphragmatica and were pre- Evaluation of drug use prescribing by prescribing indicators 85 scribed a PPI to prevent erosive damage due to reflux oesophagitis, and one was diagnosed Number and percentage of users of drug groups with an ulcus duodeni. One patient was diagnosed with reflux oesophagitis, and therapy with In the nursing home for somatic care, approximately twice as many hypnotics, NSAIDs,

an H2-antagonist was insufficiently effective. One patient experienced nausea and vomiting as ulcer-healing drugs and diuretics were prescribed compared with the nursing home for psy- a result of anti-Parkinson drug therapy (levodopa/carbidopa), and was subsequently prescri- chogeriatric care. This may reflect the somatic disorders these residents are suffering from. This bed a PPI. One patient was bedridden due to spinal-cord injury and was prescribed the PPI to descriptive indicator reflects overall prescribing practice, and can be used to monitor changes prevent erosive damage due to reflux oesophagitis. Five patients were prescribed an ulcer- in prescribing in-house over time. Comparison of prescribing practices between these homes is healing drug (proton pump inhibitor) in dosages higher than 1 PDD (equivalent to 40 mg ome- difficult in view of the differences in co-morbidity. prazole). According to the nursing home physician, this might have been due to the fact that Dosage of drug groups some prescribers tend to start with a high dosage to effectively heal the symptoms and taper The percentage of the residents receiving dosages higher than recommended (for benzo- the dosage when acute symptoms have diminished. Three patients were diagnosed with ulcus diazepines 0.5 DDD and for NSAIDs, ulcer-healing drugs and diuretics 1 DDD) varied among the ventriculi or ulcus duodeni and were therefore prescribed ulcer-healing drugs in these dosa- nursing homes, with a minimum of 17% and a maximum of 50% of the residents affected. From

ges. One of these patients was first prescribed an H2-receptor antagonist, but experienced cen- the interview data it was found that often the high dosages were the result of titration of the tral adverse effects. Of the other 2 patients, one patient was diagnosed with reflux oesophagi- dosage based on the clinical effect. This was the case in particular for NSAIDs, diuretics and tis and hiatus hernia and was prescribed a proton-pump inhibitor in high dosage by a medical ulcer-healing drugs. This indicator does not necessarily reflect suboptimal prescribing regar- specialist. This therapy was subsequently continued. The other patient was prescribed metho- ding these drug groups. Insight in the indication for which the drug is prescribed is needed to trexate and experienced nausea that responded well to proton-pump inhibitor therapy. evaluate whether a dosage is too high. In general, monitoring side effects of dosages above 1 According to the prescriber, side effects were not seen with these high dosages of proton-pump DDD is recommended in view of the increased susceptibility of elderly patients to adverse drug inhibitors. Seven patients were prescribed NSAIDs above the recommended dosage. According effects. to the nursing home physician, this was the result of careful dose adjustments that ultimately Use of non-formulary drugs led to these relatively high dosages. Three of these patients were prescribed paracetamol in Overall, 3 patients (1% of the study population) were prescribed non-formulary drugs for dosages of 2-4 g before the NSAID was started. Severe rheumatoid arthritis and severe pain the drug groups studied. Three patients received non-formulary benzodiazepines (flurazepam were reasons for prescribing NSAIDs in such high dosages. The necessity for these high dosa- and midazolam). For these drugs alternative formulary drugs were available and recommen- ges was re-evaluated periodically as well as the occurrence of potential gastro-intestinal and dations with regard to substitution could be made. renal side effects. Five patients were prescribed loop diuretics in a dosage higher than recom- Duplication of drugs mended. These patients all had a diagnosis of heart failure. The high dosages were the result More than one drug from the same drug class was prescribed to 0%-13% of the residents of careful dose adjustments that had ultimately led to these relatively high dosages. Metabolic and it concerned benzodiazepines and diuretics. In case of benzodiazepines, it may be worth- disorders such a hypokalaemia were frequently monitored by measuring plasma potassium while to limit prescribing to one benzodiazepine. levels. Combination of drugs because we also reviewed medical charts, most information on prescribing and medical diag- Two indicators assessed the combination of drugs. One indicator identified prescribing of noses could be traced. Another limitation of our study was that we did not verify all prescribing an NSAID and a loop diuretic, which was the case in 17% to 21% of the NSAID users were affec- indicators used in the drug evaluation, such as whether use of more than one drug from the ted, and prescribing practices may be improved on this point in view of the increased risk of same drug class was justified. Indicators that are to reflect suboptimal prescribing should be renal failure due to this drug-drug interaction. The other indicator assessed potential subopti- sensitive and specific. It is often difficult to derive prescribing indicators solely from guidelines mal prescribing when no gastroprotective drug was prescribed together with an NSAID. and drug formularies. This is particularly true for elderly patients, in view of the complex co- Seventy-nine percent to 100% of the NSAID users were not prescribed a gastroprotective drug morbidity and often tailor-made pharmacotherapy on the basis of clinical parameters. Efforts 86 concomitantly. These results indicate that prescribing practices can be improved. should therefore be directed towards the development of indicators that take into account 87 Duration of drug use these issues. For benzodiazepine users, one indicator assessed the duration of drug use. Nearly 100% of the benzodiazepine users used hypnotic benzodiazepines for more than 30 days, which is In conclusion against Dutch guidelines [18]. Although this indicator reflects suboptimal prescribing, it is often This pilot study showed that in two Dutch nursing homes, drugs were prescribed according difficult to withdraw benzodiazepines from patients [24,25]. However, in view of the disadvan- to regional and national prescribing guidelines. Prescribing indicators were used to evaluate tageous risk-benefit ratio of the benzodiazepines, tapering of benzodiazepine use should be drug prescribing and may reflect potentially suboptimal prescribing. However, clinical infor- attempted. Furthermore, restricting prescription of benzodiazepines for a maximum duration of mation from the prescriber was necessary to get insight into the appropriateness of prescribing. 2-4 weeks, and regularly assessing the necessity of benzodiazepine prescribing can improve The prescribing indicators used were a useful tool to evaluate prescribing practices. Because prescribing practice [26]. we studied only two nursing homes, that were not necessarily representative of the Dutch nursing home population, generalised conclusion can not be made. Verification of prescribing indicators From the interview and chart review data it was found that the prescribing indicators we Acknowledgements investigated did not always reflect suboptimal prescribing. This has also been found by others [27,28]. An indicator that performed well was the combination of gastroprotective drugs and We express our gratitude to J. Tideman, for his valuable help in collecting clinical data and NSAIDs. This indicator may reflect suboptimal prescribing in view of the risks of gastrotoxicity his contribution to the interview. A. Van den Brand, is thanked for his co-operation in carrying of NSAIDs in the elderly [23]. Recently, the nursing homes under study have changed their pre- out this study. Furthermore, we are grateful to the nursing home staff of the nursing homes and scribing policies on this point. Currently, guidelines recommend prescribing gastroprotective the pharmacy staff of the hospital pharmacy for their co-operation in collecting prescription medication to all elderly people who chronically use NSAIDs. Indicators that assessed drug data. dosages above recommended values for NSAIDs, ulcer-healing drugs and loop diuretics, did not perform well. Often good reasons for prescribing these high dosages existed, the main reason being that lower dosages were insufficiently effective. Potential side effects were known to the prescribers and monitored periodically. Furthermore, drug doses are often dependent on the indication, and several ‘ideal’ dosages per drug may exist depending on the indication. DDD values have been developed for other purposes than monitoring prescription appropriateness and therefore are unsuitable to assess appropriateness of drug dosages of these drug groups. We interviewed only one nursing home physician, and therefore it was not always possible to find out the exact reasons for prescribing by colleague-nursing home physicians. However, 23 Fries JF. NSAID gastropathy: the second most deadly rheumatic disease? Epidemiology and risk appraisal. References J Rheumatolog 1991; 18 (suppl 28): 6-10. 24 Busto U, Sellers EM, Naranjo CA, Capell H, Sanchez-Craig M, Sykora K. Withdrawal reaction after long-term use 1 Shelton PS, Fritsch MA, Scott MA. Assessing the medication appropriateness in the elderly. A review of available of benzodiazepines. N Engl J Med 1986; 315: 854-9. measures. Drugs Aging 2000; 16: 437-50. 25 Van Hulten R. Blue Boy- why not? Studies of benzodiazepine use in a Dutch community [Thesis]. University of 2 Schmader K, Hanlon JT, Weinberger M, Landsman PB, Samsa GP, Lewis I, et al. Appropriateness of medication Utrecht, 1998. prescribing in ambulatory elderly patients. J Am Geriatr Soc 1994; 42: 1241-7. 26 Eide E, Schjøt J. Assessing the effects of an intervention by a pharmacist on prescribing and administration of 3 Coste J, Venot A. An epidemiologic approach to drug prescribing quality assessment. Med Care 1999; 37: 1294-1307. hypnotics in nursing homes. Pharm World Sci 2001; 23: 227-31. 4 Buetow SA, Sibbald B, Cantrill JA, Halliwell S. Prevalence of potentially inappropriate long term prescribing in 27 Avery AJ. Appropriate prescibing in general practice: development of the indicators. Qual Health Care 1998; 7: 123. general practice in the United Kingdom, 1980-95: systematic literature review. BMJ 1996; 313: 1371-74. 28 Brook RH, McGlynn EA, Cleary PD. Quality of health care. Part 2: Measuring quality of care. New Engl J Med 88 5 Knight EL, Avorn J. Quality indicators for appropriate medication use in vulnerable elders. 1996; 335: 966-70. 89 Ann Intern Med 2001: 135; 703-10. 6 Lindley CM, Tulley MP, Paramsothy V, Tallis RC. Inappropriate medication use is a major cause of adverse drug reactions in elderly patients. Age Ageing 1992; 21: 294-300. 7 Lunn J, Chan K, Donoghue J, Riley B, Walley T. A study of the appropriateness of prescribing in nursing homes. Int J Pharm Pract 1997; 5: 6-10. 8 Sackett DL, Scott Richardson W, Rosenberg W, Brian Haynes R. Evidence-based medicine: how to practice and teach EBM. London: Churchill Livingstone, 1998. 9 Beers MH, Ouslander JG, Rollingher I, Reuben DB, Brooks J, Beck J. Explicit criteria for determining inappropriate medication use in nursing homes. Arch Intern Med 1991; 151: 1825-32. 10 Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. Arch Intern Med 1997; 157: 1531-6. 11 Schmidt IK, Claesson CB, Westerholm B, Svarstad BL. Resident characteristics and organizational factors influencing the quality of drug use in Swedish nursing homes. Soc Sci Med 1998; 47: 961-71. 12 Schmidt IK, Fastbom J. Quality of drug use in Swedish nursing homes. A follow-up study. Clin Drug Invest 2000; 20: 433-46. 13 Hanlon JT, Schmader KE, Samsa GP, Weinberger M, Uttech KM, Lewis IK, et al. A method for assessing drug therapy appropriateness. J Clin Epidemiol 1992; 45: 1045-51. 14 Veninga CCM, Denig P, Pont LG, Haaijer-Ruskamp FM. Comparison of indicators assessing the quality of drug prescribing for asthma. Health Services Research 2001; 36: Part 1: 143-61. 15 Rohling R, Berman M, Froeling PGAM, Van de Gronde ThW, Van Leen MWF, Pessers RWAM, et al. Richtlijn Hartfalen [Guideline on heart failure of the Dutch Association of Nursing Home Physicians (NVVA)]. Tijdschr Verpleeghuisgeneeskd 1999; 23: 3-19. 16 Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Drug utilisation in Dutch nursing homes. Eur J Clin Pharmacol 2000; 55: 765-71. 17 Thomas S, Geijer RMM, van der Laan JR, Wiersma T.[Guidelines for the physician II] (in Dutch). Bunge, Utrecht, 1996. 18 Van der Kuy A, editor. Farmacotherapeutisch Kompas 2000-2001 (in Dutch). 17th ed. Amstelveen: Commissie Farmaceutische Hulp (CFH), 2000. 19 Van der Graaf CJ, Hospes W (Ed). Formularium uitgave Assen (in Dutch), 1998. 20 Anonymous. Anatomical therapeutical chemical (ATC) classification index including defined daily dosages (DDDs) for plain substances. World Health Organisation Collaborating Centre for Drug Statistics Methodology, Oslo, 2000. 21 Knuistingh Neven A, Graaff de WJ, Lucassen PLBJ et al. [Dutch College of General Practitioners-guideline ‘Insomnia and hypnotics’] (in Dutch) Huisarts Wet 1992; 35: 212-9. 22 Heerdink ER, Leufkens HG, Herings RM, Ottervanger JP, Stricker BH, Bakker A. NSAIDs associated with increased risk of congestive heart failure in elderly patients taking diuretics. Arch Intern Med 1998; 158: 1108-12. 2.6 Concomitant prescribing of benzo- Abstract diazepines during antidepressant therapy in the elderly Objective: Concomitant prescribing of benzodiazepines may occur more frequently with selective serotonin reuptake inhibitors (SSRIs) than with tricyclic antidepressants (TCAs), partly due to the milder sedating effects of SSRIs. However, drug utilisation studies in this area show con- flicting results. K.N. van Dijk 1,2, C.S. de Vries 3, K. ter Huurne 1, P.B. van den Berg 1, Methods: To investigate whether prevalence and incidence of benzodiazepine drug prescribing 90 J.R.B.J. Brouwers1,2, L.T.W. de Jong-van den Berg1 is comparable between users of SSRIs and users of TCAs, a follow-up study was performed in 91 two different cohorts: an ambulatory and a nursing home cohort both aged ≥ 65 years. In each cohort the incidence and prevalence of benzodiazepine use during antidepressant therapy was 1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen estimated. TCAs and SSRIs were subsequently compared. University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, Groningen, Results: The ambulatory population consisted of 14,336 people (58% female), mean age 74 (± the Netherlands 7) years. Co-prescribing of benzodiazepines occurred in 53% of the TCA users and 57% of the 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands SSRI users (prevalence RR 1.1; CI95 0.9-1.2). Concomitant drug therapy was >65 days per 100 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, days of antidepressant drug use. During SSRI therapy, significantly more people started with Guildford, United Kingdom benzodiazepine drug therapy than during TCA therapy (incidence RR 1.7; CI95 1.2-2.4). Analyses repeated 5 years later yielded similar results (overall incidence RR 1.6 (CI95 1.3-2.0). The nursing home population consisted of 2,355 residents (73% female), mean age 82 (± 7) years. Co-pre- A modified version is accepted for publication in the Journal of Clinical Epidemiology scribing of benzodiazepines was slightly higher than in the ambulatory population: 59% in TCA users and 57% in SSRI users (prevalence RR 1.0; CI95 0.8-1.2). No difference was found in the incidence of benzodiazepine starts between SSRI and TCA therapy (incidence RR 0.8; CI95 0.4-2.0). Conclusion: More than 50% of antidepressant users receive a benzodiazepine at the same time. In the ambulatory population, it was found that SSRI use is associated with a significantly higher chance of initiating benzodiazepine therapy compared with TCA use. In the nursing home population, no such difference was found. Introduction study in an ambulatory cohort as well as a nursing home cohort, both aged 65 and over.

Choosing appropriate antidepressant therapy in the elderly has been subject of debate in Methods clinical practice [1-4]. Particular attention has been given to the adverse effects of these drugs, as elderly subjects may be more sensitive to adverse drug effects due to pharmacokinetic, phar- Design macodynamic and disease-related changes that occur with advanced age. In elderly patients, Using computerised pharmacy records a prospective follow-up study was performed to adverse effects associated with the use of tricyclic antidepressants (TCAs) include postural estimate the prevalence rate ratio (RR) as well as the incidence RR of benzodiazepines pre- 92 hypotension, anticholinergic effects, and extrapyramidal symptoms [5]. Adverse effects of scribed during antidepressant therapy. Differences in benzodiazepine drug use were compared 93 selective serotonin reuptake inhibotors (SSRIs) include syndrome of inappropriate antidiuretic between SSRI users (index group) and TCA users (reference group). hormone secretion, gastrointestinal disturbances and insomnia [5]. As a result of the unwanted anticholinergic adverse effects of TCAs in the elderly, the use of SSRIs in the elderly is incre- Study population asing [3]. However, the preferential use of the more expensive SSRIs in the elderly is still under Ambulatory cohort. Pharmacy dispensing data from the InterAction database were used for debate [6-8]. For example, an increased risk of falls and fractures as a consequence of antide- this study. This database is a collaboration between community pharmacists in the northern pressant drug use has been reported for both TCAs and SSRIs [9,10]. In addition, the need for part of the Netherlands and the University of Groningen [20]. The database contains complete concomitant benzodiazepines during antidepressant therapy has been debated [11-15]. These medication profiles of individual patients from a number of pharmacies from 1994 onwards. drugs decrease the non-specific symptoms of depression, such as insomnia, agitation and Since Dutch patients are generally registered to only one pharmacy and community pharma- anxiety, and are often used during the initiation of antidepressant treatment. After 4-6 weeks cies in the Netherlands are completely automated, complete individual medication histories of treatment the benzodiazepine is usually discontinued [16]. From two drug utilisation studies, are available in community pharmacies. Community pharmacy records are reported to be a it has been suggested that concomitant prescribing of benzodiazepines may occur more fre- reliable source of drug exposure [21]. Two 2-year cohorts were defined: one cohort included quently in users of SSRIs than in users of TCAs, and this may be partly due to the less sedative those registered in the InterAction database during the years 1994-1995 and one cohort inclu- effects of SSRIs [12-13]. However, a more recent study in Sweden, using a cross-sectional design, ded those registered during the years 1998-1999. The second cohort was selected to investiga- demonstrated that among TCA users the frequency of concomitant benzodiazepine prescribing te whether changes over time led to different outcomes. During 1994-1995, the source popula- was higher than among SSRI users [14]. In view of the adverse effects of benzodiazepines in tion consisted of 14,067 people aged ≥ 65 for whom a complete medication history was availa- the elderly, such as drowsiness, excess sedation, memory impairment and risk of falls [17-19], it ble. During the years 1998-1999, the source population consisted of 17,060 people aged ≥ 65. is worthwile to know whether use of these drugs differs between TCA and SSRI users in the The increase in source population was due to an increased number of pharmacies participating elderly. Furthermore, a difference in co-prescribing of benzodiazepines between users of TCAs in the database. During 1994-1995 10 pharmacies participated and this increased to 12 pharma- and SSRIs could constitute an additional selection criterion for choosing antidepressant thera- cies in 1998-1999. py in the elderly. A limitation of the cross-sectional study [14] was that no time sequence could be studied Nursing home cohort. The study was conducted among residents aged 65 years and over in and the benzodiazepines could well have been prescribed before initiation of antidepressant six nursing homes with a 90 to 225-bed capacity each. The nursing home study population con- therapy. To investigate changes in anxiolytic/ hypnotic benzodiazepine drug prescribing during sisted of 2,355 residents residing at any time during the two-year study period (1 October 1993 antidepressant therapy (SSRI or TCA) in more detail, we performed a follow-up study among to 1 October 1995). The databases and drug use in this population have been previously descri- elderly subjects. The aim of this study was to investigate whether the prevalence and inciden- bed in detail [22,23]. ce of benzodiazepine drug prescribing differed between SSRI and TCA users. To determine whether differences exist between ambulatory and institutionalised elderly, we performed this Prevalences son-days both during SSRI time and TCA time at risk. The incidence rate ratio with correspon-

The 2-year prevalence of benzodiazepine (Anatomical Therapeutic Chemical (ATC) [24] ding 95% confidence intervals was determined as IRSSRI / IRTCA. To investigate whether chan- codes N05BA (anxiolytics; benzodiazepine derivates), N05CD (hypnotics; benzodiazepine deri- ges over time led to different outcomes, the incidence rates of concomitant prescribing during vates) and N05CF (benzodiazepine-related hypnotics (zolpidem and zoplicone)) prescribing TCA use, during SSRI use and during use of both drug groups of the 1998-1999 cohort (cohort among SSRI and TCA users (ATC code N06AB and N06AA respectively) was estimated by divi- II) were compared with the incidence rates of concomitant prescribing of the 1994-1995 cohort ding the number of SSRI users and TCA users who were prescribed a benzodiazepine for at (cohort I). The incidence rate ratio with corresponding 95% confidence intervals was determi-

least 7 days by the total number of SSRI users and TCA users respectively. Each patient was ned as IRcohort II/IRcohort I. To investigate differences between the ambulatory cohort (1994-1995) 94 included only once in these analyses. The prevalence rate ratio with the corresponding 95% and the nursing home cohort, the incidence rates of both cohorts were compared. The statisti- 95 confidence intervals was calculated by prevalence (SSRI) / prevalence (TCA). Furthermore, the cal software program SPSS 9.0 for Windows (SPSS Inc., Chicago, IL) was used for all analyses. average duration of concomitant drug use was calculated as the number of days of drug use divided by the total number of days of antidepressant use (SSRIs and TCAs respectively), for Results those residents who used the combination for at least 7 days. To investigate whether changes over time led to different outcomes, the prevalence of concomitant prescribing during TCA use, Population characteristics during SSRI use and during use of both drug classes in the 1998-1999 cohort (cohort II) was In table 1 characteristics of the study populations are given. More elderly people and more compared with the prevalence of concomitant prescribing in the 1994-1995 cohort (cohort I). women were present in the nursing home cohort, compared with both ambulatory cohorts. In The prevalence rate ratio with corresponding 95% confidence intervals was determined as pre- the 1998-1999 cohort, a higher percentage of benzodiazepine users was found, compared with valence (cohort II) / prevalence (cohort I). To investigate differences between the ambulatory the 1994-1995 ambulatory cohort. cohort (1994-1995) and the nursing home cohort, the prevalences in both were compared.

Table 1: Patient characteristics and use of benzodiazepines and antidepressants in both study populations Incidence rates Patients were considered to be ‘at risk’ for initiation of a benzodiazepines during the time Variable Ambulatory cohort Ambulatory cohort Nursing home ’94-’95 ’98-’99 cohort ‘94-’95 period of antidepressant therapy in which no benzodiazepines were used. The start of a ben- (n=14,067) (%) (n=17,060)(%) (n=2,355) (%) zodiazepine during SSRI or TCA use, and subsequent concomitant use of at least 7 days, was Age (yrs ± SD) 75.2 (±7.1) 76.5 (± 7.1) 82.0 (± 7.3) considered an event. When the start of a benzodiazepine coincided with the start of an antide- Gender pressant, or with the first day of the study period, the start was not considered an event. In this Female 8220 (58.4) 9996 (58.6) 1666 (70.7) Male 5847 (41.6) 7064 (41.4) 689 (29.3) way, only incident cases of benzodiazepine drug therapy during antidepressant drug therapy Drug use were included in the analyses. We performed a sensitivity analysis in which we included starts Anxiolytics/ 4063 (28.9) 6105 (35.8) 1530 (65.0) of benzodiazepines that coincided with the start of an antidepressant, to see whether this led Hypnotics¶ to different outcomes. For each patient, only the first episode of antidepressant drug use in the TCAs¥ 600 (4.3) 832 (4.9) 283 (12.0) SSRIs# 298 (2.1) 658 (3.9) 91 (3.9) study period was considered. We investigated incidence rates in two 2-year study periods: in 1994-1995 (cohort I) and 1998-1999 (cohort II). We blinded ourselves to drug use prior to the 98- ¶ ATC-codes [22] N05BA, N05CD and N05CF ¥ ATC-code [22] N06AA 99 study period for better comparison with the earlier cohort. Thus, incidence rates were cal- # ATC-code [22] N06AB culated in exactly the same way for both cohorts. For each patient, only the first episode of antidepressant drug use in the study period was considered. We investigated incidence rates (IRs) by dividing the number of events (start of benzodiazepine) by the total number of per- Prevalence ratios benzodiazepine drug therapy (incidence RR 1.72; CI95 1.23-2.42). In the second ambulatory In table 2 the prevalence rate ratios for concomitant use of benzodiazepines during antide- cohort, a similar result was found: SSRI users were at a 57% higher risk for the start of a ben- pressant therapy for both ambulatory cohorts and the nursing home cohort are given. zodiazepine compared with TCA users. In the nursing home cohort, no association was found: Furthermore, the average duration of concomitant drug use is given. There was no difference the incidence RR of benzodiazepine drug therapy during SSRI use compared to TCA use was in prescribing of benzodiazepines for SSRI users and TCA users in the first ambulatory cohort. 0.84 (CI95 0.36-1.96). There were no statistically significant differences between the nursing In the second ambulatory cohort the concomitant prescribing of benzodiazepines was slightly home cohort and the first ambulatory cohort in the incidence of concomitant prescribing of higher among SSRI users. In the nursing home cohort, there was no difference in concomitant benzodiazepines among among TCA users, among SSRI users, or among both drug classes. No 96 prescribing of benzodiazepines between SSRI users and TCA users. There were no statistically statistically significant differences were found between the second and the first cohort in the 97 significant differences between the nursing home cohort and the 1994-1995 ambulatory cohort incidence of concomitant prescribing of benzodiazepines among TCA users, or among SSRI in concomitant drug use among TCA users, among SSRI users or among both drug classes com- users. However, when the concomitant use of benzodiazepines during both SSRIs and TCAs in

bined. Table 2 shows that in all cohorts the number of days of concomitant drug use per 100 the 1998-1999 cohort was compared with the 1994-1995 cohort, the overall incidence RRMH was days of antidepressant drug use was more than 67. There were no statistically significant diffe- 0.82 (CI95 0.67-1.00), indicating 18% less concomitant drug use in the more recent years. In the rences between the second and the first ambulatory cohort in concomitant drug use among TCA results presented above, when the start of a benzodiazepine coincided with the start of an anti- users, among SSRI users or among both drug classes. depressant, the start was not considered an event. A sensitivity analysis in which we included these events (‘prophylactic starts’) led to an incidence rate ratio of 1.60 (CI95 1.23-2.09) for the

Table 2: Prevalence rate ratios for concomitant benzodiazepine drug use during TCA and SSRI use first cohort (1994-1995) and 1.34 (CI95 1.12-1.61) for the second cohort (1998-1999). In particular in the second cohort, the point estimate was slightly lower than the IRR without inclusion of pro- Drug use Number Number of % of days Prevalence CI 95 phylactic starts (IRR 1.57 (CI95 1.24-1.98)), however the difference between SSRI users and TCA of users concomitant of concomitant RR users was still statistically significant. (%a) benzodiazepine drug usec users (%b) Cohort I TCA 600 (4.3) 319 (53.2) 76.2 1.0 Table 3: Incidence rate ratios for the start of benzodiazepine drug prescribing during antidepressant therapy: 1994-1995 SSRIs compared to TCAs (n=14,067) SSRI 298 (2.1) 169 (56.7) 67.2 1.07 0.94-1.21

-3 a Cohort II TCA 832 (4.9) 437 (52.5) 73.2 1.0 Drug use Number Number of IR (x 10 ) Incidence CI95 1998-1999 of events days at risk RR (n=17,060) SSRI 658 (3.9) 414 (62.9) 70.3 1.20 1.10-1.31 Nursing TCA 286 (12.1) 170 (59.4) 83.7 1.0 Cohort I TCA 102 48,237 2.11 1.0 home cohort 1994-1995 1994-1995 SSRI 93 (3.9) 53 (57.0) 82.9 0.96 0.78-1.17 (n=14,067) SSRI 49 13,449 3.64 1.72 1.23-2.42 (n=2,355) Cohort II TCA 143 80,187 1.78 1.0 a % of total study population 1998-1999 b % of TCA and SSRI users, respectively (n=17,060) SSRI 136 48,613 2.80 1.57 1.24-1.98 c defined as the number of days of concomitant drug use per 100 days of antidepressant drug use Overall incidence rate ratio 1.61 1.33-1.96 Nursing TCA 23 10,855 2.12 1.0 Incidence rate ratios home cohort In table 3, the incidence rate ratios for all cohorts are presented. In the first ambulatory 1994-1995 SSRI 7 3,932 1.78 0.84 0.36-1.96 cohort, use of SSRIs, compared with TCAs, was associated with a significantly increased risk of (n=2,355)

a number of events divided by the number of days at risk Discussion diately. After 4-6 weeks when the antidepressant drug has reached its effect, the benzodiazepine should be tapered and discontinued [16]. The results of our analyses indicate that the In this study we found that in ambulatory elderly the risk for initiating benzodiazepines simultaneous use is long-term, and most probably not used as a temporary measure associa- during antidepressant therapy was higher for users of SSRIs than for users of TCAs (overall ted with initiation of antidepressant treatment. The difference of nearly 7% in the percentage incidence RR 1.6; CI95 1.3-2.0). In the second cohort (1998-1999), slightly fewer antidepressant of users of benzodiazepines between the two ambulatory cohorts (table 1) could be the conse- users started benzodiazepine drugs compared with the first cohort (1994-1995), indicating that quence of a higher prevalence of psycho-somatic disorders or sleep disorders in the second the rate of concomitant prescribing decreased over the years. In both cohorts there was a higher cohort. However, as we do not have information on the indication for which the drugs were pre- 98 frequency of concomitant prescribing among SSRI users compared with TCA users. Several scribed, we cannot prove this assumption. In a Dutch report on the appropriate use of benzo- 99 explanations for this finding can be given. The most likely reason for the increased risk among diazepines issued in 1998 [25], it was stated that in certain cases it is appropriate to treat elder- SSRI users compared with TCA users, also suggested in other studies [12,13], is that the less ly people suffering from psychosomatic disorders with benzodiazepines. This may further sedating effects of SSRIs may contribute to the increased prescribing of benzodiazepines. explain the higher frequency of benzodiazepine users in the second cohort. Furthermore, elderly people may be more sensitive to the sedative adverse effects of TCAs, the- Bingefors and colleagues [14] found a difference in the concomitant prescribing of anxioly- refore diminishing the need for benzodiazepine drug prescribing during TCA use. In the nursing tic/hypnotic drugs between TCA and SSRI users: concomitant prescribing occurred more fre-

home cohort, no difference in starting a benzodiazepine was found between users of SSRIs quently in TCA users than in SSRI users (ORadj 1.3 (CI95 1.0-1.6). They concluded that the concern compared with users of TCAs. Partly this may be due to the fact that hypnotic use in this popu- about increased anxiolytic/hypnotic drug use among SSRI users seems to be unfounded in lation is high already: in a previous study, it was found that 65% of the nursing home popula- Sweden. A limitation of their study was they could only study concomitant prescribing of drugs tion used a benzodiazepine during the study period [22]. It can be argued that starting on an that were dispensed on the same day [14]. By using a follow-up design, we were able to esti- antidepressant together with a benzodiazepine may be due to anticipation of insufficient effi- mate the incidence rate ratios for initiating benzodiazepine drug therapy during antidepressant cacy of the antidepressant, possibly in view of prior use of the combination (which was un- therapy. In this way, differences between SSRI and TCA users can be measured more accurate- known to us because it was outside the study window). We checked for the impact of excluding ly. Several other studies have reported on concomitant prescribing of these two drug groups, these ‘prophylactic starts’ and found that inclusion of these events marginally altered the although differences in study design and setting make comparison difficult. Gregor [13] studied results, and it did not change our conclusion. concomitant use of anxiolytics and hypnotics with SSRIs in patients younger than 65 years. The prevalence of concomitant prescribing was considerable: in both ambulatory and insti- Concomitant anxiolytic and hypnotic use occurred in 9.8% and 2.8% of the patients, respecti- tutionalised elderly more than 50% of TCA and SSRI users were prescribed a benzodiazepine vely, and was more common among patients treated with paroxetine than among patients tre- concomitantly. In the ambulatory cohort, concomitant benzodiazepine prescribing among SSRI ated with sertraline or fluoxetine. Rascati [12] showed that 35% of patients receiving SSRIs or users was slightly higher when we studied prevalence (57-63% versus 53% in TCAs). The fact clomipramine used anxiolytic/hypnotic drugs concomitantly. Parkes [11] suggested that the use that we did not find any difference between the nursing home cohort and the ambulatory of newer antidepressants, mainly SSRIs, in a group of veterans resulted in a 48% increase in cohort suggests that the extent of the problem is the same in ambulatory and institutionalised prescriptions for benzodiazepines, presumably to manage associated insomnia. The prevalen- elderly. The duration of concomitant drug use was also relatively high: on average, concomitant ces in our study are higher than in the above mentioned studies. These differences might be drug use lasted for greater than 67 days or more per 100 days of antidepressant drug use. The explained by the differences in study design, such as the setting and age limits chosen. Also, we high rate of concomitant prescribing seems of concern. In particular, the combination of TCAs studied prevalence during a 2-year period, while most studies used a shorter study period, and benzodiazepines may lead to cumulation of adverse effects in the elderly, such as excess giving lower prevalences. sedation and muscle relaxation leading to an increased risk of falls [18]. In psychiatry, it is common practice to initiate antidepressant and benzodiazepine drug therapy simultaneously, with the aim to treat non-specific symptoms of depression such as agitation and insomnia imme- Limitations References Information for each subject in the study population was obtained from one of the two 1 Avorn J, Gurwitz JH. Drug use in the nursing home. Ann Intern Med 1995; 123: 203-11. datasets: the InterAction dataset and the nursing home dataset. Both databases are pharmacy 2 Flint AJ. Choosing appropriate antidepressant therapy in the elderly. A risk-benefit assessment of available prescription databases and contain complete medication profiles of individual patients. We do agents. Drugs Aging 1998; 13: 269-80. not know whether people actually used the drugs that were dispensed. In the nursing home, 3 Mamdani MM, Parikh SV, Austin PC, Upshur RE. Use of antidepressants among elderly subjects: trends and contributing factors. Am J Psychiatry 2000; 157: 360-7. nursing staff ensure everyone takes their medication [22]. However, in the ambulatory cohort, 4 Salzman C. Practical considerations for the treatment of depression in elderly and very elderly long-term care people who collect their prescriptions at the pharmacy, need not necessarily use these drugs. patients. J Clin Psychiatry 1999; 60 (suppl): 30-3. 100 An overestimation of drug use due to non-adherence could be a consequence of using phar- 5 Pollock BG. Adverse reactions of antidepressants in elderly patients. J Clin Psychiatry 1999; 60 (suppl): 4-8. 101 macy prescription data. In our study this may lead to an overestimation of drug use in the 6 Mittmann N, Herrmann N, Einarson TR et al. The efficacy, safety and tolerability of antidepressants in late life depression: a meta-analysis. J Affect Disord 1997; 46: 191-217. ambulatory cohort, thus leading to a greater difference between the ambulatory and nursing 7 Williams JW, Mulrow CD, Chiquette E, Hitchcock Noël P, Aguilar C, Cornell J. A systematic review of newer home cohort. Non-adherence may be greater with TCAs than with SSRIs (due to more severe pharmacotherapies for depression in adults: evidence report summary. Ann Intern Med 2000; 132: 743-56. adverse effects [26]), leading to greater differences between TCAs and SSRIs, which would not 8 Steffens DC, Krishnan KB, Helms MJ. Are SSRIs better than TCAs? Comparison of SSRIs and TCAs: a meta-analysis. Depress Anxiety 1997; 6: 10-18. change our conclusions. Antidepressants may be used for other conditions than depression, for 9 Thapa PB, Gideon P, Cost TW, Milam AB, Ray WA. Antidepressants and risk of falls among nursing home example panic disorder (mainly SSRIs), obsessive-compulsive disorder (mainly SSRIs), and residents. N Engl J Med 1998; 339: 875-82. neuropathic pain conditions (mainly TCAs). This may influence co-prescribing of other drugs. 10 Liu B, Anderson G, Mittman N, To T, Axcell T, Shear N. Use of selective serotonin-reuptake inhibitors or tricyclic antidepressants and risk of hip fractures in elderly people. Lancet 1998; 351: 1303-7. Since we did not have information on indications for prescribing of antidepressant drugs, we 11 Parkes A. Starting SSRI antidepressant therapy: its effect on tricyclic antidepressant and benzodiazepine can not adjust for this possibly confounding effect. Furthermore, we do not know whether the prescribing (letter). Med J Aust 1996; 164: 509. choice of antidepressant is influenced by the mental state of the patients. For example, TCAs 12 Rascati K. Drug utilization review of concomitant use of specific serotonin reuptake inhibitors or clomipramine may be prescribed more frequently to agitated patients. with anxiety/sleep medications. Clin Ther 1995; 17: 786-90. 13 Gregor K, Riley J, Downing D. Concomitant use of anxiolytics and hypnotics with selective serotonin reuptake In summary, in this follow-up study of the elderly we could not confirm an increased risk inhibitors. Clin Ther 1996; 18: 521-7. for concomitant prescribing of benzodiazepines among TCA users found in an earlier, cross- 14 Bingefors K, Isacson DGL. Concomitant prescribing of tranquilizers and hypnotics among patients receiving sectional study [14]. In fact, we found a higher incidence of benzodizapine drug prescribing antidepressant prescriptions. Ann Pharmacother 1998; 32: 531-5. 15 Pathiyal A, Hylan TR, Jones JK, Davtian D, Sverdlov L, Keyser M. Prescribing of selective serotonin reuptake among SSRI users compared with TCA users. In the nursing home cohort, no difference in ini- inhibitors, anxiolytics, and sedative-hypnotics by general practitioners in The Netherlands: a multivariate tiating benzodiazepine drug therapy was found between users of SSRIs compared with users analysis. Clin Ther 1997; 19: 798-810. of TCAs. We also found a 2-year prevalence of benzodiazepine drug prescribing during both 16 Joffe RT, Levitt AJ, Sokolov STH. Augmentation strategies: focus on anxiolytics. J Clin Psychiatry 1996; 57 (suppl): 25-31. SSRI and TCA use of more than 50% and that the duration of concomitant drug use was rela- 17 Holbrook AM, Crowther R, Lotter A, Cheng C, King D. Meta-analysis of benzodiazepine use in the treatment of tively long-term (>65 days per 100 days of antidepressant drug use) in both ambulatory and insomnia. CMAJ 2000; 162: 225-33. institutionalised elderly. In view of cumulation of adverse sedative effects, and questionable 18 Ray WA, Thapa PB, Gideon P. Benzodiazepines and the risk of falling in nursing home residents. J Am Geriatr Soc 2000; 48: 682-5. therapeutic benefits of concomitant prescribing of these two drug groups, physicians may bene- 19 Hanlon JT, Horner RD, Schmader KE, Fillenbaum GG, Lewis IK, Wall WE, et al. Benzodiazepine use and fit from feedback on their prescribing habits. cognitive function among community-dwelling elderly. Clin Pharmacol Ther 1998; 64: 684-92. 20 Tobi H, Van den Berg PB, De Jong-van den Berg LTW. The InterAction database: synergy of science and practice Acknowledgement in pharmacy. In: Medical data analysis: first international symposium; proceedings/ISMDA (RW Brause, E Hanisch, eds). Berlin: Springer, 2000: 206-11. 21 Lau HS, de Boer A, Beuning KS, Porsius A. Validation of pharmacy records in drug exposure assessment. We express our gratitude to D.A. Bloemhof, hospital pharmacist, for supplying nursing J Clin Epidemiol 1997; 50: 619-2. home pharmacy data. 22 Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Drug utilisation in Dutch nursing homes. Eur J Clin Pharmacol 2000; 55: 765-71. 23 Van Dijk KN, De Vries CS, Van den Berg PB, Dijkema AM, Brouwers JRBJ, De Jong-van den Berg LTW. 2.7 Prescribing of gastroprotective drugs Constipation as an adverse effect of drug use in nursing home patients: an overestimated risk. Br J Clin Pharmacol 1998; 46: 255-61. among elderly NSAID users in the 24 Anonymous. Anatomical therapeutical chemical (ATC) classification index including defined daily dosages (DDDs) for plain substances. World Health Organisation Collaborating Centre for Drug Statistics Methodology, Netherlands Oslo, 2000. 25 Dutch Health Council: Towards a more appropriate use of benzodiazepines. Publication number 1998/20. The Hague: Health Council; 1998. 26 Anderson IM. Selective serotonin reuptake inhibitors versus tricyclic antidepressants: a meta-analysis of K.N. van Dijk 1,2, K. ter Huurne1, C.S. de Vries 3, P.B. van den Berg1, efficacy and tolerability. J Affect Disord 2000; 58: 19-36. 102 J.R.B.J. Brouwers1,2, L.T.W. de Jong-van den Berg1 103

1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, Groningen, the Netherlands 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, Guildford, United Kingdom

Pharmacy World and Science (in press) Abstract Introduction

Objective: Use of non-steroidal anti-inflammatory drugs (NSAIDs) is associated with an in- The use of non-selective non-steroidal anti-inflammatory drugs (NSAIDs) is associated creased risk of gastrointestinal toxicity, in particular when risk factors are present. We investi- with a wide range of gastrointestinal (GI) toxicity, including mild dyspepsia (prevalence 20%), gated whether recommendations, suggesting concomitant therapy with gastroprotective development of (asymptomatic) duodenal or ventricular ulcera (prevalence of 10-20% within 3 agents for patients at risk of developing NSAID-induced gastropathy, are being followed in months of NSAID-use) and serious complications such as perforation, ulceration, obstruction daily clinical practice. and/or bleeding [1-4]. The risk for serious GI complications increases with advanced age: 104 Methods: A study was performed to investigate concomitant prescribing of gastroprotective NSAID users aged over 60 years are at up to 5 times greater risk of developing serious GI com- 105

agents (H2-receptor antagonists, proton pump inhibitors, or misoprostol) in an ambulatory plications (e.g. bleeding, perforation) than those not taking NSAIDs [2]. Other risk factors inclu- cohort of NSAID users aged 65 years and over. The prevalence of concomitant prescribing was de previous NSAID-related GI adverse effects, previous history of gastrointestinal events, con- studied, as well as the prophylactic prescribing of gastroprotective drugs. A stepwise logistic comitant corticosteroid use, concomitant use of anticoagulant drugs, chronic use of NSAIDs and regression was performed to determine predictive variables of prophylactic and concomitant use of high dosages of NSAIDs [3-7]. gastroprotective drug prescribing. To prevent the occurrence of NSAID-induced GI-toxicity, several strategies exist. Prescribing

Results: Co-prescribing of gastroprotective drugs occurred in 1,522 (23%) (of which 944 con- a gastroprotective agent such as an antacid or an H2-receptor antagonist usually can prevent

cerned prophylactic prescribing) of the NSAID users (n=6,557), with an average duration of 67 mild dyspepsia. Asymptomatic ulcers can be prevented by concurrent administration of H2- days per 100 days of NSAID use. Co-prescribing of gastroprotective drugs varied among indivi- receptor antagonists or proton pump inhibitors. To prevent serious GI toxicity, the prostagland-

dual NSAIDs. Concomitant use of oral corticosteroids (ORadj 2.4; CI95 2.0-2.9), coumarins (ORadj in analogue misoprostol [8,9], proton pump inhibitors [9,10] and H2-receptor antagonists in

1.6; CI95 1.3-2.0), and low dose aspirin (ORadj 1.6; CI95 1.4-1.9) were significantly associated with high dosage [10] are reported to be effective, although a beneficial effect on perforation, both prophylactic and concomitant prescribing of gastroprotective agents during NSAID thera- obstruction and bleeding has been shown only for misoprostol [8,11]. In a randomised control- py. led trial (n=935) it was found that omeprazole 20 mg and 40 mg daily and misoprostol 800 µg Discussion: Despite current guidelines recommending gastroprotective drug prescribing among daily produced similar reductions of endoscopically diagnosed ulceration [12]. Misoprostol high risk groups, the rate of concomitant prescribing of gastroprotective agents in NSAID users generally causes more adverse effects (diarrhoea and abdominal pain) [12]. It was shown that aged 65 years and over is low. Feedback to prescribers should be given to improve prescribing misoprostol (used in the combined formulation of diclofenac/misoprostol) was more cost- practices in this high risk group. effective than proton pump inhibitors [13]. Selective cyclo-oxygenase-2 (COX-2) inhibitors, such as rofecoxib and celecoxib, are reported to result in 50% less perforation, obstruction and bleeding than classic NSAIDs (such as diclofenac, naproxen and ibuprofen) [14,15]. These drugs might be alternatives to classic NSAIDs combined with gastroprotective drugs [11], however to our knowledge cost-effectiveness studies have not been performed yet. In most countries guidelines exist to minimise the risk of NSAID-induced GI toxicity, mainly recommending concurrent administration of gastroprotective agents [11]. The American College of Rheumatology recommends that patients with a risk of developing NSAID-induced gastropathy should receive concomitant therapy with gastroprotective agents, such as misoprostol [2]. In the Netherlands, similar recommendations exist [16]. To investigate whether these recommendations are being followed in daily clinical practice, we studied the prescribing

of H2-receptor antagonists, proton pump inhibitors and misoprostol in a cohort of NSAID users aged 65 years and over. Methods tors were the drugs most frequently used among NSAID users, followed by H2-receptor antagonists and misoprostol (p<0.05). Study population The study was performed with pharmacy dispensing data form the InterAction database, Table 1: Use of drugs under study in the study populations which is part of a collaboration between community pharmacists in the Northern part of the

Netherlands and the University of Groningen. This database contains complete medication Drug use Cohort 1998-1999¶ NSAID users¥ Non-NSAID users profiles of 135,000 individual patients from a number of pharmacies from 1994 onwards and (n=17,060) (%) (n=6,557) (%) (n=10,503) (%)

106 has been described in detail elsewhere [17]. The study population included all patients aged 65 Proton pump 2530 (14.8) 1262 (19.2) 1268 (12.1) 107 and over who were registered within the InterAction database and who were prescribed an inhibitors NSAID at any time during the study period of January 1998 until December 1999. H2-antagonists 1998 (11.7) 977 (14.9) 1021 (10.3)

Drug utilisation Misoprostol14 (<0.1) 13 (0.2) 1 (<0.1) Concomitant use of NSAIDs (Anatomical Chemical Therapeutic (ATC) [18] code M01A) and ¶ Cohort of patients aged > 64 yrs registered in the InterAction database at any time during 1998-1999 the following gastroprotective agents was studied: misoprostol (ATC code A02BB01), H2-recep- ¥ Defined as person who uses NSAID at any time during study period. tor antagonists (ATC code A02BA), and proton pump inhibitors (ATC code A02BC). The 2-year prevalence of concomitant prescribing of these gastroprotective agents during NSAID therapy was calculated by dividing the number of NSAID users who were prescribed a gastroprotective Co-prescribing of gastroprotective drugs occurred in 1,522 (23%) (of which 944 concerned agent concomitantly for at least 1 day by the total number of NSAID users. Each patient was prophylactic prescribing) of the NSAID users (n=6,557), with an average duration of 67 days per included in these analyses only once. The average duration of concomitant drug use was cal- 100 days of NSAID use. In table 2, the results of the analyses on concomitant drug use of gastro- culated as the number of days of concomitant drug use divided by the total number of days of protective agents during use of NSAIDs are given for each NSAID that was used in the study NSAID use. These analyses were performed for each NSAID individually. NSAIDs that were population. The NSAIDs in table 2 are given in order of the GI toxicity ranking of Henry and co- prescribed to less than 50 people were excluded from the analyses. We investigated the pro- workers [19], with ibuprofen being the NSAID with the lowest toxicity profile, and ketoprofen phylactic prescribing of gastroprotective drugs separately, defined as the number of patients the NSAID with the highest toxicity profile. Meloxicam, nabumetone and the fixed combination who started with an NSAID and a gastroprotective agent, prescribed by the same physician, on of diclofenac plus misoprostol have been on the market since 1996, and therefore were not clas- the same day. Relative risks for both prophylactic and concomitant prescribing of gastroprotec- sified by Henry [19]. Prophylactic prescribing of gastroprotective drugs occurred most frequent- tive drugs during NSAID therapy were calculated for each NSAID individually. A stepwise logis- ly among users of ketoprofen (26%), compared to other NSAID users. Ibuprofen users were tic regression was performed to determine predictive variables of prophylactic and concomitant prescribed the fewest prophylactic GI-protective drugs (9%). In table 2 it is shown that the rela- gastroprotective drug prescribing. tive risk for prescribing gastroprotective drugs prophylactically was 3.6 times higher for ketoprofen users compared to ibuprofen users. Meloxicam users were 2.3 times more likely to recei- Results ve a gastroprotective drug prophylactically. The prevalence of concomitant GI-protective drug 17,060 patients aged 65 and over were registered in the InterAction database during 1998 prescribing was highest among users of meloxicam (34%), followed by ketoprofen (31%). and 1999. Of these, 6,557 (38.4%) used an NSAID at any time during the study period. In table Otherwise stated, meloxicam users and ketoprofen users were respectively 2.4 times and 2 1, the numbers of users of gastroprotective medications among NSAID users and non-NSAID times more likely to receive a gastroprotective drug concomitantly (table 2). The lowest preva-

users are given. Proton pump inhibitors, H2-receptor antagonists and misoprostol were used lence of concomitant GI-protective drug prescribing was found among ibuprofen users (18%). more frequently in NSAID users compared to non-NSAID users (p<0.05). Proton pump inhibi- The duration of concomitant drug use ranged between 58 days per 100 days of indomethacin drug use and 82 days per 100 days of ketoprofen drugs use. Table 3 shows the results of the multivariate analyses. It was found that use of NSAIDs for more than 90 days, concomitant use of oral corticosteroids, concomitant use of low dose aspirin and concomitant use of oral anticoagulants (coumarins) all were significantly associated with both prophylactic and concomitant prescribing of gastroprotective agents during NSAID therapy.

108 109 (95% (95% CI) Duration of en) crude (95% (95% CI) Number of patients RR crude ¶ Number of patients RR ¥ (% of cohort ofNSAID users (n=6,557)) on prophylactic2556 (38.9)3579 GI-drug use (%) (54.6)793196 (12.1)136 (3)104 229 (2.1) (9) 475 (1.6) (13.3)509 103 (13)340 (7.8) 33279 (5.2) 18 (16.8) 27 (4.3) (13.2) on concomitant 1 (reference) 1.56 (1.32-1.84) (26) GI-drug use (%) 50 1.52 (1.18-1.94) 63 (9.8) 2.06 (1.38-3.06) 807 461 34 (18.5) ns 1.55 (0.93-2.59) (22.5) (18) (12.1) 3.56 (2.25-5.64) 176 33 (22.2) 53 ns 1.11 (0.80-1.53) (24.3) (27.0) 32 2.31 (1.70-3.14) 1.32 (1.16-1.50) 1 (30.8)(reference) ns 1.41 (0.96-2.07) 121 concomitant 1.30 (1.07-1.58) (23.8) drug use (%) ns 1.46 (0.97-2.18) 116 65.3 1.68 (1.21-2.35) 72 (34.1) (25.8) 66.3 2.02 (1.32-3.10) 72.3 68.7 1.42 (1.13-1.78) 57.7 81.8 2.35 (1.84-3.01) 1.58 (1.19-2.11) 65 71.3 73.0 Use of drugs concomitant duringGI-protective NSAID use NSAIDs are listed in ranging order highfrom low of (ibuprofen) toxicity to toxicity, comparative (ketoprof toxicity relatively total number of patients is more than 6,557 because patients may use NSAIDs several (adapted from [11]), except for diclofenac+misoprostol, meloxicam, nabumeton (adapted meloxicam, from [11]), for diclofenac+misoprostol, except ns non significant ¶ ¥ Ibuprofen Diclofenac Naproxen Indomethacin Piroxicam Ketoprofen Diclofenac+ Misoprostol Meloxicam Nabumeton Table 2: Table NSAID Number of patients Discussion

We found that 23% of a cohort of NSAID users aged 65 and over were prescribed a gastroprotective agent concomitantly. Among two-third of these patients the gastroprotective drugs )

95 were prescribed prophylactically. In view of current prescribing guidelines, these findings indi- (CI cate low concomitant and prophylactic prescribing of gastroprotective agents among NSAID

adjusted users aged over 64 year in daily clinical practice. 110 The frequency of concomitant prescribing varied between individual NSAIDs. According to 111 the classification of Henry and co-workers [19], ibuprofen is the NSAID with the lowest GI toxicity profile. We found that concomitant and prophylactic prescribing was the lowest among ibuprofen users, which is in line with Henry’s classification. Ketoprofen (a high GI toxicity NSAID [19]) users were almost 4 times more likely to receive a gastroprotective drug prophylactically, )OR 95 compared with ibuprofen users. Also, the prevalence of concomitant gastroprotective drug use (CI among ketoprofen users was higher than for the other NSAIDs, with the exception of meloxi- crude

OR cam. However, percentages of concomitant (31%) and prophylactical (26%) prescribing among ketoprofen users were still very low. The fact that nearly 75% of the ketoprofen users did not use any gastroprotective agent raises the question whether these patients are optimally treated or whether the guidelines need adjusting. Prophylactic and concomitant use of gastropro-

¥ tective drugs among meloxicam users was relatively high (19% and 34% respectively). An ) 95

(CI explanation for this finding could be that meloxicam, which is reported to have milder GI side effects due to preferential inhibition of cyclooxygenase 2 [20], is prescribed to high-risk adjusted

OR patients (‘channelling’). This phenomenon has recently been described in a report by Lanes and co-workers [21].

Strengths and limitations Because we used dispensed prescribing data from pharmacies, we eliminated primary non- ¶ ) compliance. Furthermore, the detail and completeness of information present in the 95

(CI InterAction database enables the accurate estimation of duration of drug use and the specific

crude drugs dispensed, for each individual patient. A limitation of our study is that we do not know Prophylactic gastroprotective Prophylactic drug use gastroprotective Concomitant drug use whether patients who do not use gastroprotective drugs concomitantly suffer from more severe GI toxicity, such as perforation and bleeding, than patients who are prescribed gastroprotective drugs. Because we performed a retrospective study on prospectively collected data, several biases could occur. Information bias could occur when drugs are not taken as dispensed. Selection bias in this study is not very likely to occur, because this study is based on a population-based cohort. Confounding by lifestyle-factors such as smoking and alcohol could have Variables associated with prophylactic and with concomitant associated prophylactic gastroprotective drug prescribing Variables odds ratio with corresponding 95% adjusted intervals, confidence for listed variables in column 1 odds ratio with corresponding 95% unadjusted intervals, confidence for listed variables in column 1 Gender (male vs female)Age (+5 years) Duration of NSAID use (+30 days)Use of oral corticosteroids 0.66 (0.57-0.77) 1.12 (1.10-1.13)Use of low dose aspirinUse of coumarins 2.93 (2.42-3.56) 1.10 (1.04-1.15) (0.63-0.87) 0.74 2.09 (1.78-2.45) 1.10 (1.09-1.11) 2.39 (1.92-2.96) 2.18 (1.78-2.68) 1.0 (0.95-1.05) 0.77 (0.68-0.88) 1.81 (1.52-2.15) 1.08 (1.07-1.09) 1.91 (1.51-2.41) 2.97 (2.49-3.54) 1.09 (1.05-1.14) 0.83 (0.73-0.94) 1.83 (1.59-2.11) 1.06 (1.05-1.07) 1.94 (1.59-2.36) 2.44 (2.03-2.93) 1.03 (0.99-1.08) 1.62 (1.40-1.88) 1.64 (1.33-2.01) ¥ ¶ Variable OR Table 3: Table occurred in this study; this information is not present in the prescription database and is likely References to affect concomitant prescribing. In this study, we defined misoprostol (combinations), proton 1 Griffin MR, Piper JM, Daugherty JR, Snowdon M, Ray WA. Nonsteroidal anti-inflammatory drug use and pump inhibitors and H -receptor antagonists as gastroprotective agents. Of these misoprostol 2 increased risk for peptic ulcer disease in elderly persons. Ann Intern Med 1991; 114: 257-63. is the only drug with proven effectiveness on perforation, obstruction and bleeding [8]. H 2- 2 Plosker GL, Lamb HM. Diclofenac/misoprostol: pharmacoeconomic implications for therapy. receptor antagonists have been reported to be effective in double dosage (2 times the licensed Pharmacoeconomics 1999; 16: 85-98. 3 Fries JF. NSAID gastropathy: the second most deadly rheumatic disease? Epidemiology and risk appraisal. daily dosage for ulcer healing). Limiting our analyses to misoprostol would have shown lower J Rheumatol 1991; suppl.28: 6-10. percentages of concomitant and prophylactic gastroprotective drug use during NSAID therapy. 4 Wolfe MM, Lichenstein DR, Singh G. Gastrointestinal toxicity of nonsteroidal anti-inflammatory drugs. N Engl J Med 1999; 24: 1888-99. 112 We found that H2-receptor antagonists were prescribed in normal dosages (data not shown). 113 From this study, in daily clinical practice the prescription of double dosage of H -receptor anta- 5 Gabriel SE, Jaakkimainen L, Bombardier C. Risk for serious gastrointestinal complications related to use of 2 non-steroidal anti-inflammatory drugs. A meta-analysis. Ann Intern Med 1991; 115: 787-96. gonists does not seem to take place. 6 Griffin MR. Epidemiology of nonsteroidal anti-inflammatory drug-associated gastrointestinal injury. Am J Med 1998; 104: 23S-29S. Other studies 7 Shorr RI, Ray WA, Daugherty JR, Griffin MR. Concurrent use of nonsteroidal anti-inflammatory drugs and oral anticoagulants places elderly persons at high risk for hemorrhagic peptic ulcer disease. Arch Intern Med 1993; In a Canadian cohort of NSAID users > 65 years (n= 61,601), 26% were prescribed an anti- 153: 1665-70. ulcer medication, compared with 11% of the non-NSAID users (n=168,944) [22]. Schubert and 8 Silverstein FE, Graham DY, Senior JR, Davies HW, Struthers BJ, Bittman RM, et al. Misoprostol reduces serious colleagues [23] found that 8.9%-12.2% of patients treated with NSAIDs (n=460) were prescri- gastrointestinal complications in patients with rheumatoid arthritis receiving nonsteroidal anti-inflammatory drugs: a randomized double-blind, placebo-controlled trial. Ann Intern Med 1995; 123: 241-249. bed an antacid or a drug for the treatment of peptic ulcer. LeLorier [24] found that in a cohort 9 Rostom A, Wells G, Tugwell P, Welch V, Dube C, McGowan J. The prevention of chronic NSAID induced upper of elderly aged over 65 (n=773,654) ibuprofen users were prescribed less systemic antiulcer gastrointestinal toxicity: a Cochrane collaboration meta-analysis of randomized controlled trials. J Rheumatol agents than other NSAIDs, probably due to a channelling of low risk patients towards this drug. 2000; 27: 2203-14. Pertusi and colleagues [25] held a survey among geriatric practitioners (n=229) to investigate 10 Agrawal NM, Aziz K. Prevention of gastrointestinal complications associated with nonsteroidal antiinflammatory drugs. J Rheumatol 1998; 25: S51: 17-20. the extent of gastroprotective prescribing among elderly NSAID users and the influence of risk 11 Boers M. NSAIDs and selective COX-2 inhibitors: competition between gastroprotection and cardioprotection factors (age, previous peptic ulcer, previous gastro-intestinal bleeding, and heart disease) on (commentary). Lancet 2001; 357: 1222-3. their choices. It was found that 64% of the respondents would not prescribe gastroprotective 12 Hawkey CJ, Karrasch JA, Szczepanski L, Walker DG, Barkun A, Swannell AJ et al. Omeprazole compared with misoprostol for ulcers associated with nonsteroidal antiinflammatory drugs. N Engl J Med 1998; 338: 727-34. agents to elderly patients who use NSAIDs. This was different for nursing home residents using 13 Brouwers JRBJ, Van Roon EN, Postma M, Al M. Altijd gastroprotectie? Kosten-effectiviteit van NSAIDs NSAIDs: only 32% would not prescribe gastroprotective agents for this population. (in Dutch). Pharm Weekbl 2000; 135: 172-5. Furthermore, age and heart disease were risk factors that physicians did not take into account 14 Silverstein FE, Faich G, Goldstein JL, Shapiro D, Burgos-Vargas R, Davis B, et al. Gastrointestinal toxicity with celecoxib vs nonsteroidal anti-inflammatory drugs for osteoarthritis and rheumatoid arthritis: the CLASS study: when choosing gastroprotective agents. Further research is needed into the reasons for not a randomized controlled trial. Celecoxib Long-term Arthritis Safety Study. JAMA 2000; 284: 1247-55. prescribing gastroprotective agents for high-risk patients. The results of our study are in line 15 Bombardier C, Laine L, Reicin A, Shapiro D, Burgos-Vargas R, Davis B, et al. Comparison of upper gastro- with these findings and raise the question why gastroprotective agents are not prescribed more intestinal toxicity of rofecoxib and naproxen in patients with rheumatoid arthritis. VIGOR Study Group. N Engl J Med 2000; 343: 1520-8. frequently among high-risk patients. 16 Van der Kuy, A (Ed). Farmacotherapeutisch Kompas (in Dutch). Amstelveen, The Netherlands: CMPC Ziekenfondsraad, 2001: 940. Conclusion 17 Tobi H, Van den Berg PB, De Jong-van den Berg LTW. The InterAction database: synergy of science and practice Our study shows that gastroprotective drugs are prescribed to only a minority (23%) of in pharmacy. In: Brause RW, Hanisch E (ed) Medical data analysis: first international symposium; proceedings/ISMDA. Berlin: Springer, 2000: 206-11. NSAID users aged 64 and over. This might suggest that physicians do not consider age as a risk 18 Anonymous. Anatomical therapeutical chemical (ATC) classification index including defined daily dosages factor for gastrointestinal adverse effects of NSAIDs. In view of the known gastrointestinal side (DDDs) for plain substances. Oslo: World Health Organisation Collaborating Centre for Drug Statistics effects of non-selective NSAIDs, we think it is necessary to give feedback to physicians with the Methodology, 2000. 19 Henry D, Lim LLY, Garcia Rodriguez LA, Perez Gutthann S, Carson JL, Griffin M, et al. Variability in risk of aim to increase the rate of concomitant gastroprotective drug use in elderly NSAID users. gastrointestinal complications with individual non-steroidal anti-inflammatory drugs: results of a collaborative meta-analysis. BMJ 1996; 312: 1563-6. 20 Hawkey C, Kahan A, Steinbrück K, Alegre C, Baumelou E, Bégaud B, et al. Gastrointestinal tolerability of meloxicam compared to diclofenac in osteoarthritis patients. Br J Rheumatol 1998; 37: 937-45. 21 Lanes SF, Garcia Rodriguez LA, Hwang E. Baseline risk of gastrointestinal disorders among new users of meloxicam, ibuprofen, diclofenac, naproxen and indomethacin. Pharmacoepidemiol Drug Saf 2000; 9: 113-7. 22 Hogan DB, Campbell NRC, Crutcher R, Jennett P, MacLeod N. Prescription of nonsteroidal anti-inflammatory drugs for elderly in Alberta. CMAJ 1994; 151: 315-22. 23 Schubert I, Ihle P, Köster I, Ferber von L. Markers to analyse the prescribing of non-steroidal anti-inflammatory drugs in ambulatory care. Eur J Clin Pharmacol 1999; 55: 479-86. Chapter 3 114 24 LeLorier J. Patterns of prescription of nonsteroidal antiinflammatory drugs and gastroprotective agents. 115 J Rheumatol 1995; (suppl 43): 22: 26-7. 25 Pertusi RM, Godwin KS, House KJ, Knebl JA, Alexander JH, Rubin BR, et al. Gastropathy induced by nonsteroidal anti-inflammatory drugs: pescribing patterns among geriatric practitioners. J Am Osteopath Assoc 1999; 99: 305-10. Risk assessment studies in the elderly Outline 3.1 Constipation as an adverse effect of drug use in nursing home patients: This chapter focuses on the clinical implications and potential risks associated with drug an overestimated risk use, with reference to two particular issues identified in chapter 2. Section 3.1 presents a study among a cohort of nursing home residents, in which the association between drug use and constipation was investigated. As was shown in section 2.3, laxative use was high in nursing home patients and we investigated whether this might be the consequence of use of drugs that have K.N. van Dijk 1,2, C.S. de Vries3, P.B. van den Berg1, A.M. Dijkema1, 116 been associated with an increased frequency of constipation, such as anticholinergic drugs. In J.R.B.J. Brouwers1,2, L.T.W. de Jong-van den Berg1 117 section 3.2, a study is presented in which the clinical effect of a drug-drug interaction was investigated. The drug-drug interaction studied was between NSAIDs and acenocoumarol, an interaction that was frequently encountered in nursing home patients as was shown in section 1 Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen 2.4. This study was performed in a cohort of elderly outpatients, using data from the Groningen University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, Outpatient Thrombosis Service. Genotyping of cytochrome P450 2C9 was performed to deter- Groningen, the Netherlands mine whether genotype was a predictive variable for the occurrence of this drug interaction. 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands 3 Department of Pharmacoepidemiology, Postgraduate Medical School, University of Surrey, Guildford, United Kingdom

British Journal of Clinical Pharmacology 1998; 46: 255-61 Abstract Introduction

Objective: To investigate whether results from case control and cross sectional studies, which Many studies have reported laxative use in the elderly to be disturbingly high and it has suggest an association between laxative use and other drug use, could be confirmed in a cohort been suggested that improved pharmacotherapy might reduce the prevalence of constipation study of nursing home patients. [1]. The prevalence of constipation in ambulatory elderly over age 65 years varies from 16% to Methods: A prospective cohort study of 2,355 nursing home patients aged 65 years and over 41% [2,3]. Chronic constipation may lead to complications such as faecal impaction, stercoral was performed to estimate the incidence relative risk of constipation associated with drug use. ulceration, bowel obstruction, sigmoid volvulus and even syncope [2]. The prevalence of con- 118 The study was conducted with prescription sequence analysis of each resident’s detailed phar- stipation among institutionalised elderly has been reported to be even higher [4,5]. In a popu- 119 macy records and data on morbidity and mobility. lation of 784 nursing home patients in the Netherlands, 53% were prescribed one or more Results: Use of drugs, which according to the summaries of product characteristics and the lite- laxatives daily [5]. Long-term use of stimulant laxatives may lead to abdominal cramps, fluid rature on adverse drug effects have moderately to strongly constipating properties, was asso- and electrolyte disturbances, malabsorption and cathartic colon [6]. In view of these unwanted ciated with a relative risk of 1.59 (CI95 1.24–2.04) for the occurrence of constipation during effects and to improve the quality of life of the elderly it is worthwhile to study whether laxa- exposure time. Use of drugs with mildly to moderately constipating effects was not associated tive use can be reduced in this population. Polypharmacy is an important risk factor for consti- with laxative use (RR 1.13; CI95 0.93–1.38). Stratification on the level of age, gender, type of nur- pation, especially in nursing homes where levels of medication use are high [7]. Drugs that are sing (psychogeriatric or somatic), morbidity, number of medications taken and mobility showed commonly associated with constipation are opioids, iron salts, calcium channel blockers and no confounding effects of these variables on outcome measurements. These variables all acted drugs with anticholinergic/antimuscarinic effects [5]. The last group is also responsible for as effect modifiers. Effect of age and number of medications taken on the relative risk was non- other potentially dangerous adverse effects in the elderly such as urinary retention, memory linear. problems, delirium and acute glaucoma [8,9]. In pharmacoepidemiological studies, laxative Conclusions: Although an association between drugs that exhibit moderately to strongly con- administration is used as a proxy for constipation because laxative use has been shown to cor- stipating effects and occurrence of constipation was found, the risk was not as high as seen in relate well with constipation [1]. The association between laxative use and other drug use has previous studies. The high prevalence of constipation in nursing home patients is only partly been assessed in several studies [1–3,10,11]. In most of these studies, only some subgroups of due to adverse drug effects. drugs were considered and the majority of these studies used cross-sectional study designs. To investigate whether the suggested causal association between laxative use and co-medication could be confirmed in a cohort of nursing home residents in the Netherlands we carried out a prospective study using prescription sequence analysis. If any such causal association exists, recommendations can subsequently be given for alternative pharmacotherapy in order to reduce laxative use in the elderly.

Methods

Design A prospective cohort study was performed to estimate the incidence relative risk of constipation as an adverse effect of drug use. The study was conducted with prescription sequence analysis of computerised pharmacy records. Prescription sequence analysis is a method to determine side effects of drugs through individual medication histories. It is based on the observation that a side effect of drug A is followed by the prescription of drug B (a ‘proxy’ drug) Exposure definition if drug B is used to counteract the side effect caused by drug A [12]. In this study, laxative drugs Drugs were classified into three categories: category 2: drugs that exhibit moderately to (all drugs in the Anatomical Therapeutic Chemical (ATC) classification A06 and A02AA02 [13]) strongly constipating effects (see Appendix A), category 1: drugs that exhibit mildly to modera- were considered proxy drugs for constipation. tely constipating effects (see Appendix B) and a reference category which contained all other drugs. For each drug the summary of product characteristics (SPC), edited and approved by the Setting Dutch Medicines Evaluation Board [15], provided the main source for the classification of the The study was undertaken in six nursing homes for long-term care with a 1030-bed capaci- constipating effects of the drugs used by the study population, together with specific informa- 120 ty in the northern part of the Netherlands. In these nursing homes medical care is provided by tion on adverse drug effects from the literature [16,17]. Each resident’s exposure time was defi- 121 nursing home physicians, who give medical care on a daily basis. Specialists’ medical input is ned as the duration of drug use from category 1 or 2, respectively. To control for residual effects obtained on demand. A distinction is made between care for psychogeriatric residents and care we performed both a study in which we defined exposure time as the duration of drug use plus for somatic residents. Nursing-, physician- and pharmacist care is comparable between the the first 14 days after every exposure period and a study in which we excluded the first 14 days nursing homes. In each nursing home nursing staff defined constipation as not having defeca- after every exposure period from both exposure time and nonexposure time. To investigate if ted for more than 3–5 days. Fluid- and fibre intake was comparable between the nursing any differences in constipating properties exist between certain of the subgroups of drugs from homes. category 2, we performed subgroup analyses on pharmacological subgroups (see table 4). Non- exposure time was defined as the remainder of the period of stay during the study period. Data collection Exposure days to category 2 drugs, to category 1 drugs and nonexposure days were aggregated For each resident, pharmacy records of a two-year period and individual morbidity and over the study population. mobility data were collected. Pharmacy data included the generic name, strength, dosage, the frequency of use and the route of administration of the drugs, the prescription length (in days) Case definition and the following patient characteristics: age, gender, date of admission and date of discharge. The occurrence of constipation was identified by the start of a laxative, which is considered Drugs were classified according to the ATC classification system [13]. Dermatological prepara- a proxy drug. When the start of a laxative coincided with the start of a drug from category 2 or tions were excluded from the analyses. Pharmacy records were linked with a national infor- 1, the start was considered as a prophylactic start; these starts were not considered as cases. mation system on nursing homes (SIVIS) [14], to collect the following data: type of nursing When the start of a laxative coincided with the date of admission to the nursing home or with (psychogeriatric or somatic), morbidity and mobility. the first day of the study period, the start was not considered as a case either. Patients were considered to be ‘at risk’ for constipation during the period of stay in which they did not use a Study population laxative. All nursing home residents from six nursing homes were initially included in the cohort. The study population consisted of 2,772 residents aged 65 years and over who were present at Analysis any time during the two-year study period from 1 October 1993–1 October 1995. We excluded Incidence rates during exposure and nonexposure time, respectively, were calculated by patients who could not be linked to data from the SIVIS-system (14.2%), and subsequently dividing the number of starts of laxative use by the total number of person-days at risk both patients whose period of residence could not be defined as a result of missing data (1%). This during exposure time and during nonexposure time at risk. The incidence relative risk is deter-

resulted in a final study population of 2,355 patients. Of these patients 65% were newly admit- mined as Iexp /Inonexp. Mantel-Haenszel relative risks were calculated to control for potential ted during the study period. confounding effects of age, gender, morbidity (Parkinson’s disease, diabetes mellitus, depression and dementia), type of nursing (psychogeriatric or somatic), number of medications taken and mobility. All statistical analyses were performed in SPSS for Windows [18]. Incidence relative risks were calculated with corresponding 95% confidence intervals (CI95). Results Laxative use Fifty-six percent of the study population used a laxative at some time during stay at the Population characteristics nursing home. An overview of the laxatives used by the study population is given in table 2. The mean age of the study population was 82 years (SD 7.3). The average residence time Seventy-four percent of the residents with Parkinson’s disease used a laxative. At the entry of during the study period was 257 days (SD 260). The average number of different medicines the study period, 416 (18%) of the patients used a laxative. After the study entry date 1109 (based on ATC-codes) per person was 8.9 during residence in the nursing home (SD 4.9; der- (47%) patients started a laxative for one or more periods. Of these patients 233 (21%) used a matological preparations excluded). The average number of different medicines per patient per laxative for a period of less than 30 days, and 876 (79%) used a laxative for a period of 30 days 122 day was 4.9. Most drugs were used for more than 50% of the duration of stay in the nursing or more. The average duration of laxative use was 154 days (SD 192). On average, people who 123 home. In table 1, characteristics of the study population are given. Of the mobile residents 35% were on a laxative drug used it for more than 77% of their nursing home stay. Relatively high were diagnosed with dementia, while 22% of the immobile residents were diagnosed with dosages of laxatives were used. dementia. Forty-six percent of the study population used a drug from category 2; 57% of the study population used a drug from category 1. Table 2: Laxatives used by the study population (n=2355)

Laxative Number of of patients¶ (%) Table 1: Characteristics of the study population (n=2355) Lactitol871 (37%) Lactulose 346 (15%) Variable Number of residents (percentage of total) Bisacodyl336 (14%) Age (years) Magnesium oxide 140 (6%) 65-74 415 (18%) Docusate sodium 91 (4%) 75-84 1012 (43%) Triticum 90 (4%) ≥ 85 928 (39%) Ispaghula (psylla seeds) 70 (3%) Gender Male 689 (29%) ¶ Note: patients may use more than one laxative Female 1666 (71%) Type of nursing Psychogeriatric 700 (30%) Incidence rate ratios Somatic 1609 (68%) Not known 46 (2%) The results from the cohort study are presented in table 3. Use of drugs from category 2 Morbidity (moderately to strongly constipating drugs) was associated with a relative risk of 1.59 (CI 95 Parkinson's disease 151 (6%) 1.24–2.04) for the occurrence of constipation and the incidence relative risk of exposure to cate- Diabetes mellitus 176 (7%) gory 1 drugs (mildly to moderately constipating drugs) was 1.13 (CI95 0.93–1.38) compared with Depression 40 (2%) Dementia 689 (29%) nonexposure. To control for residual effects we performed both a study in which we defined Number of different medicines exposure time as the duration of drug a use plus the first 14 days after every exposure period 0-5 626 (27%) and astudy in which we excluded the first 14 days from both exposure time and nonexposure 6-10 969 (41%) time. When exposure time was defined as the duration of category 2 drug use plus the first 14 > 10 760 (32%) Mobility days after this period, the incidence relative risk was slightly higher (RR 1.69; CI95 1.33–2.15), Mobile 1370 (58%) indicating a carry-over effect from category 2 drug exposure in the nonexposure period. To Immobile 985 (42%) exclude this carry-over effect, we deleted the first 14 days after exposure time from both exposure and nonexposure time, which resulted in an incidence relative risk of 1.60 (CI95 1.25–2.06). Table 5: Relative risks for the occurrence of constipation associated with exposure to category 2 drugs, stratified for Results of the subgroup analyses are given in table 4. Point estimates varied from 1.01 (opiates) age, gender, type of nursing, morbidity, number of medications and mobility to 1.92 (verapamil) but the differences were not all statistically significant. Ninety-six percent Diseased (n) Time at risk (days) Relative risk RRMantel-Haenzsel of the people who received opiates received a laxative drug prior to the initiation of opiate use. Variable exposed unexposed exposed unexposed (CI95) (CI95) Statistical analysis of possible confounding effects of the variables given in table 1 showed no Age (years) confounding effects from these variables as shown in table 5. Gender, morbidity and mobility 65-74 17 46 5089 23300 1.69 (0.97-2.95) 75-84 38 95 13820 49055 1.42 (0.98-2.07) acted as effect modifiers. There was a non-linear association with age and with the number of ≥ 85 29 95 12022 65480 1.66 (1.10-2.52) 124 medications taken. Residents with depression and residents with diabetes mellitus were more overall 84 236 30931 137835 1.59 (1.24-2.04) 1.55 (1.21-1.99) 125 at risk for the occurrence of constipation as an adverse drug effect while residents with Gender Parkinson’s disease showed a markedly lower risk. Residents who were relatively mobile Male 31 69 7428 37380 2.26 (1.48-3.45) Female 53 167 23503 100455 1.36 (1.00-1.85) showed a higher risk for the occurrence of drug-induced constipation. overall 84 236 30931 137835 1.59 (1.24-2.04) 1.60 (1.25-2.05) Type of nursing Psychogeriatric 17 66 8614 60166 1.79 (1.05-3.06) Table 3: Relative risks for the occurrence of constipation with different drug categories Somatic 64 163 20438 69275 1.33 (1.00-1.78) Not known 3 7 1852 8394 1.94 (0.50-7.51) Drug category Events* Time at risk (days) Relative risk (RR) CI95 overall 84 236 30931 137835 1.59 (1.24-2.04) 1.47 (1.15-1.89) 2: moderately to strongly constipating 84 30931 1.59 1.24-2.04 Morbidity 1: mildly to moderately constipating 179 92339 1.13 0.93-1.38 Parkinson's disease 5 20 2486 5976 0.60 (0.23-1.60) Reference drug category 236 137835 1.00 Diabetes mellitus 7 12 2276 10790 2.77 (1.09-7.02) Depression 3 5 355 3077 5.20 (1.24-21.76) * Events: number of starts of a laxative. This was considered a marker for constipation Dementia 17 66 11410 61387 1.39 (0.81-2.36) overall 32 103 16527 81240 1.53 (1.03-2.27) 1.40 (0.95-2.07) Number of medications Table 4: Subgroup analyses of drug groups from category 2 0-5 9 54 4992 48008 1.60 (0.79-3.25) 6-10 41 101 12721 51 1 31 1.63 (1.14-2.35) >10 34 81 13218 38696 1.23 (0.82-1.83) Drugs under study Events* Time at risk (days) Relative risk (RR) CI95 Opiates 5 2880 1.01 0.42-2.46 overall 84 236 30931 137835 1.59 (1.24-2.04) 1.45 (1.13-1.86) Morphine, nicomorphine, pethidine, Mobility dextropropoxyphene Mobile 53 137 18272 89477 1.89 (1.38-2.60) Calcium channel blockers 10 3042 1.92 1.02-3.62 Immobile 31 99 12659 48358 1.20 (0.80-1.79) Verapamil overall 84 236 30931 137835 1.59 (1.24-2.04) 1.57 (1.22-2.00) Calcium salts and ferrous salts 54 18947 1.67 1.24-2.24 Anticholinergic agents Atropine, biperiden, orphenadrine, 10 5621 1.04 0.55-1.96 oxybutynine, oxyphencyclimine, thiazinamium, trihexyphenidyl Drugs with anticholinergic side effects 58 22244 1.52 1.14-2.03 Amitryptyline, disopyramide, chlorpromazine, chlorprotixene, clozapine, clomipramine, doxepine, flavoxate, imipramine, maprotiline, nortriptyline, thioridazine Reference drug category 236 137835 1.00

* Events: number of starts of a laxative. This was considered a marker for constipation Discussion remained unclear. In a cross-sectional study Monane [1] found a strong association between laxative use and the use of highly anticholinergic antidepressants (OR 3.12; CI95 1.21–8.03) in Our study confirms earlier findings of a risk of constipation as a consequence of drug use. nursing home patients. Also in a cross-sectional study Harari [11] demonstrated that the use of However, from this cohort study the relative risk appears to be lower than has been suggested iron supplements and calcium channel blockers was significantly associated with laxative use in previous case control and cross-sectional studies. In 2,355 nursing home patients, the use of (OR 2.2 and OR 1.9, respectively) in elderly people residing in a long-term care setting. To our drugs that exhibit moderately to strongly constipating effects was slightly but significantly knowledge, our study is the first that uses a cohort design to determine the association associated with the start of a laxative (RR 1.59; CI95 1.24–2.04). When the first 14 days after between medication use and laxative administration in a nursing home population. In a cohort 126 every exposure period were added to the exposure time, the relative risk was slightly higher design, laxative use as a result of medication use (sequential use) can be properly assessed 127 (RR 1.69; CI95 1.33–2.15), which indicates residual effects of these drugs depending on the eli- with prescription sequence analysis. With cross-sectional methods, temporal sequences of pre- mination half-life. The results show that drugs, which according to the summaries of product scribing are more difficult to assess [12]. characteristics and to the literature on adverse drug effects exhibit a moderately to strongly constipating effect, in practice are only marginally associated with the occurrence of constipa- Possible bias tion. However, the fact that drugs from category 2 are used by nearly half of the study popula- Selection bias. We excluded all nursing home residents for whom data were incomplete or tion at least once during the study period suggests that this side effect could be clinically rele- invalid. Since they represented a small proportion of the population, this is not likely to have vant in daily practice because it concerns many residents. Drugs that have been reported to influenced the results. Information for each resident was obtained from the same data set. have mild to moderate constipating effects were not associated significantly with constipation Therefore it is unlikely that selection bias played a role in this study. (RR 1.13; CI95 0.93–1.38). This means that although constipation is mentioned as a possible side Information bias. Information bias might occur when a laxative is prescribed for an indica- effect in the summaries of product characteristics and in the literature, the high prevalence of tion other than constipation. This could lead to a bias away from the null in both the exposed constipation is probably not due to use of drugs from this category. Subgroup analyses demon- and nonexposed group. As the only other indication for the prescription of lactulose is hepatic strated that the use of the calcium channel blocker verapamil and the use of calcium- and fer- (pre) coma, a very rare disease, it is not likely that it leads to differential misclassification. Also rous salts, especially, were associated with a high risk for the occurrence of constipation. The a laxative could be withheld from a patient suffering from constipation. This could lead to a bias fact that laxatives are given prophylactically with this drug category explains why use of opia- towards the null. This kind of bias is not likely to occur often because residents are frequently tes was not associated with a higher risk. Several reports support our results. Mikus and colle- monitored by nurses or carers, so constipation will be noticed at an early stage. However, this agues recently showed that the constipating effect of codeine is only seen in extensive meta- kind of bias could be relevant when the problem of constipation is considered (more constipa- bolizers (CYP2D6 phenotype) [20]. In a literature search (1965–94) concerning adverse events ted residents), but probably is not relevant when drug-induced constipation is considered (bias associated with antidepressant drugs, constipation did not belong to one of the 27 most fre- will occur in both exposed and nonexposed groups). Medication use of the individual nursing quently reported adverse events [21]. In a community based study no significant association home resident is recorded centrally in one of the three computerised hospital pharmacies was found between antidepressant drug use and use of laxatives [22]. involved in our study. Dispensing of drugs takes place when the registration of medication is complete. Therefore information bias is not likely to occur. Previous studies Confounding bias. We tried to control for possible confounding patient characteristics such In the study of Stewart [2], a positive correlation was demonstrated between self-reported as age, gender, type of nursing, number of medications taken, morbidity and mobility. None of constipation and the total number of drugs used in an ambulatory elderly population, but no these variables was considered a confounder although some of the variables were considered specific drug groups were correlated with constipation. Talley [3] demonstrated that use of non- effect modifiers (see below). No marked differences were seen in overall fluid and fibre intake steroidal anti-inflammatory drugs was a significant risk factor in elderly subjects with both among the different nursing homes. Because we could not collect data on fluid and fibre inta- functional constipation and outlet delay. However, whether this was a causal association ke at individual patient level, this may still confound our results. The influence of fluid and fibre intake on constipation has been assessed in only few studies. Although dietary fibre is often use of newer antidepressants (such as selective serotonin reuptake inhibitors) and antipsy- diminished in the elderly, no clear association has been made with true clinical constipation [7]. chotics with minor or no anticholinergic activity could be considered as alternatives to antide- There are no data on dehydration as a risk factor for constipation in the elderly although the pressants and antipsychotics with anticholinergic side effects. beneficial effect of fluid intake has been proven in young male volunteers [7]. A community In conclusion, this study demonstrates that medication, which according to their SPCs and based cohort study by Towers showed that constipation was related to caloric intake rather the literature on adverse drug effects exhibit moderately to strongly constipating effects, is than fibre consumption or fluid intake [19]. In our study a resident may develop constipation as associated with the occurrence of constipation in a cohort of nursing home patients. However, a consequence of low fluid and fibre intake. When this patient is using drugs from category 1 the risk is not as high as previous studies suggest. Drugs that were classified as mildly to mode- 128 or 2, this patient would be wrongly considered as a ‘case’. This might lead to a overestimation rately constipating showed no increased risk for the occurrence of constipation. The high pre- 129 of the relative risk but it does not change our conclusion. Other possible confounders such as valence of laxative use in nursing home patients is only partly due to adverse drug effects. To age and co-morbidity did not play a role in our study. Obviously, we can never rule out confou- minimize the risk for constipation, alternative pharmacotherapy could be considered for certain ding effects of factors that we are not aware. subgroups of drugs.

Effect modifiers Acknowledgements Several other factors have been reported to be associated with constipation in the elderly. Bowel frequency is decreased with certain neurological and endocrine disorders such as We express our gratitude to D.A. Bloemhof, hospital pharmacist, for supplying pharmacy Parkinson’s disease and diabetes mellitus. Older people and women are reported to be more at data; SIG Informatics on Health and Welfare, Utrecht, for supplying patient morbidity and risk for constipation. The type of nursing, psychogeriatric or somatic, can influence outcome. In mobility data; and nursing, medical and pharmacy staff from all participating nursing homes several studies, inactivity and immobility have been identified as risk factors for constipation. for their co-operation. Although data in the elderly are scarce, Towers [19] showed that constipated elderly tend to report less regular activity and exercise. Therefore we stratified for the variables age, gender, type of nursing, morbidity, number of medications taken and mobility to control for possible confounding effects. Gender, morbidity and mobility acted as effect modifiers. The non-linear association with age and number of medications taken suggests a combined effect of effect modification and confounding by these variables. Men were at a higher risk for the occurrence of constipation during category 2 drug exposure in comparison with women. Residents suffering from Parkinson’s disease showed a markedly lower relative risk, probably because these residents are already constipated. Patients with depression and diabetes mellitus showed a higher risk for the occurrence of constipation as an adverse drug effect. Finally, residents who were relatively mobile were more at risk for the occurrence of constipation during category 2 exposure. When pharmacotherapy is needed, the possible constipating effects of category 2 drugs should be taken into account with special reference to the patients’ gender, co-morbidity, number of medications taken and mobility. In these risk groups in particular the use of category 2 drugs is associated with the occurrence of constipation. Furthermore, alternative pharmacotherapy could be considered with certain subgroups of category 2 drugs. For example, the necessity of verapamil, calcium salts and ferrous salts should be (re-)evaluated carefully. The References Appendix A: Drugs classified as moderately to strongly constipating [15–17]

1 Monane M, Avorn J, Beers MH, Everitt DE. Anticholinergic drug use and bowel function in nursing home ATC-code [13] Generic name patients. Arch Intern Med 1993; 153: 633–8. A02BX02 Sucralfate 2 Stewart RB, Moore MT, Marks RG, Hale WE. Correlates of constipation in an ambulatory elderly population. A03AA01 Oxyphencyclimine Am J Gastroenterol 1992; 87: 859–64. A03BA01 Atropine 3 Talley NJ, Fleming KC, Evans JM, O’Keefe EA, Weaver AL, Zinsmeister AR, et al. Constipation in an elderly A07DA03 Loperamide community: a study of prevalence and potential risk factors. Am J Gastroenterol 1996; 1: 19–25. A12AA03 Calcium gluconate 4 Harari D, Gurwitz JH, Avorn J, Choodnovskiy I, Minaker KL. Constipation: assessment and management in an A12AA04 Calcium carbonate 130 institutionalized elderly population. J Am Geriatr Soc 1994; 42: 947–52. 131 A12AA05 Calcium lactate 5 Brouwers JRBJ, Tytgat G. Laxatives for elderly people with constipation. Formulary criteria, precautions and A12AA20 Calcium, combinations complications (in Dutch). Pharm Weekbl 1993; 128: 1483–87. B03AA02 Ferrous fumarate 6 Wald A. Constipation in elderly patients. Pathogenesis management. Drugs Aging 1993; 3: 220–31. B03AA07 Ferrous sulphate 7 Harari D, Gurwitz JH, Minaker KL. Constipation in the elderly. J Am Geriatr Soc 1993; 41: 1130–40. B04AD01 Colestyramine 8 Feinberg M. The problems of anticholinergic adverse effects in older patients. Drugs Aging 1993; 3: 335–48. 9 Riedel WJ, Van Praag HM. Avoiding and managing anticholinergic effects of antidepressants. C01BA03 Disopyramide CNS Drugs 1995; 3: 245–59. C08DA01 Verapamil 10 Jones RH, Tait CL. Gastrointestinal side-effects of NSAIDs in the community. Br J Clin Pract 1995; 49: 67–70. G04BD02 Flavoxate 11 Harari D, Gurwitz JH, Avorn J, Choodnovskiy I, Minaker KL. Correlates of regular laxative use by frail elderly G04BD04 Oxybutynin persons. Am J Med 1995; 99: 513–8. N02AA01 Morphine 12 Petri JL, De Vet HCW, Naus J, Urquhart J. Prescription sequence analysis: a new and fast method for assessing N02AA04 Nicomorphine certain adverse reactions of prescription drugs in large populations. Statis Med 1988; 7: 1171–5. N02AB02 Pethidine 13 Anonymous. Anatomical Therapeutic Chemical (ATC) classification index. Oslo: WHO collaborating centre for N02AC04 Dextropropoxyphene drug statistics methodology, 1994. N04AA01 Trihexyphenidyl 14 SIG. Informatics in Health and Welfare, Utrecht, the Netherlands. N04AA02 Biperiden 15 Dutch Medicines Evaluation Board, Rijswijk, the Netherlands. N04AB02 Orphenadrine 16 Informatorium Medicamentorum. Royal Dutch Society for the Advancement of Pharmacy, The Hague, N05AA01 Chlorpromazine the Netherlands 1994. N05AC02 Thioridazine 17 Dukes MNG (ed). Meyler’s side effects of drugs, twelfth edition, Amsterdam: Elsevier Science Publishers 1992. N05AF03 Chlorprothixene 18 Norusis MJ SPSS. 6.1. Guide to data analysis. New Jersey: Prentice-Hall Inc. Englewood Cliffs. N05AH02 Clozapine 19 Towers AL, Burgio KL, Locher JL, Merkel IS, Safaeian M, Wald A. Constipation in the elderly: influence of dietary, N06AA02 Imipramine psychological, and physiological factors. J Am Geriatr Soc 1994; 42: 701–6. N06AA04 Clomipramine 20 Mikus G, Trausch B, Rodewald C, Hofmann U, Richter K, Gramatte T, et al. Effect of codeine on gastrointestinal N06AA09 Amitriptyline motility in relation to CYP2D6 phenotype. Clin Pharmacol Ther 1997; 61: 459–66. N06AA10 Nortriptyline 21 Egberts ACG, Koning de GHP, Bakker A, Leufkens HGM. Adverse events associated with antidepressant drugs N06AA12 Doxepin published in the medical literature. In Egberts ACG Pharmacoepidemiologic approaches to the evaluation of N06AA21 Maprotiline antidepressant drugs [Thesis]. University of Utrecht, 1997. NO6CA01 Amitriptyline plus neuroleptic 22 Egberts ACG, Leufkens HGM, Launer LJ, Grobbee DE, Hofman A, Hoes AW. Characteristics of older subjects R06AD06 Thiazinamium using antidepressant drugs. In Egberts ACG. Pharmacoepidemiologic approaches to the evaluation of antidepressant drugs [Thesis]. University of Utrecht, 1997. 3.2 Potential interaction between Appendix B: Drugs classified as mildly to moderately constipating [15–17] acenocoumarol and diclofenac, ATC code [13] Generic name naproxen and ibuprofen and A03AB03 Oxyphenonium A03BB01 Scopolamine the role of CYP2C9 genotype A04AA01 Ondansetron C02AC01 Clonidine C03CA01 Furosemide 132 C03CA02 Bumetanide K.N. van Dijk1,2, A.W. Plat1, A.A.C. van Dijk1, G. Piersma-Wichers3, 133 G02CB02 Lisuride 4 5 1 N02AD01 Pentazocine A.M.B. de Vries-Bots , J. Slomp , L.T.W. de Jong-van den Berg , N02AE01 Buprenorphine J.R.B.J. Brouwers1,4 N02AX02 Tramadol N03AB02 Phenytoin N03AE01 Clonazepam 1 N04BC01 Bromocriptine Department of Social Pharmacy, Pharmacoepidemiology and Pharmacotherapy, Groningen N05AA02 Methotrimeprazine University Institute for Drug Exploration (GUIDE), University Centre for Pharmacy, N05AB03 Perphenazine Groningen, the Netherlands N05AD05 Pipamperone 2 Department of Clinical Pharmacy, Medical Centre Leeuwarden, Leeuwarden, the Netherlands N05AF01 Flupenthixol 3 N05AF05 Zuclopenthixol Groningen Outpatient Thrombosis Service, Groningen, the Netherlands N05AG02 Pimozide 4 Community Pharmacy ‘t Hooge Zand, Hoogezand, the Netherlands N05AL01 Sulpiride 5 Department of Clinical Chemistry, Stichting Klinisch Chemisch Laboratorium, Leeuwarden, N05AX08 Risperidone the Netherlands N05BX01 Mephenoxalone N06AA01 Desipramine N06AX03 Mianserin N06AX05 Trazodone Submitted N06AX11 Mirtazepine R05DA04 Codeine R06AB02 Dexchlorpheniramine R06AD02 Promethazine Abstract Introduction

Objective: To investigate the influence of diclofenac, naproxen and ibuprofen on the Inter- Oral anticoagulation with coumarin derivatives is widely used in the treatment and pro- national Normalised Ratio (INR) of outpatients stabilised on acenocoumarol therapy. To deter- phylaxis of patients with thromboembolic diseases [1]. In Europe, acenocoumarol and phen- mine the role of cytochrome P450 2C9 (CYP2C9) polymorphism on coumarin dosage and INR in procoumon are the drugs most commonly used. In view of the narrow therapeutic range and NSAID users. the marked inter- and intra-individual variability, the intensity of anticoagulation is monitored Methods: The study was carried out at the Groningen Outpatient Thrombosis Service. A retro- by measuring the prothrombin time [2]. The result of prothrombin time monitoring is expres- 134 spective study among patients who received both acenocoumarol and one of the NSAIDs under sed as the International Normalised Ratio (INR). The anticoagulant effect of coumarins is in- 135 study was performed. Patients whose INR rose above the upper level of the therapeutic range fluenced by many drug-food and drug-drug interactions [3]. Among the non-steroidal anti- (> 3.5) after adding an NSAID under study to the acenocoumarol therapy, were compared with inflammatory drugs (NSAIDs), azapropazon and phenylbutazon are contraindicated in patients patients who did not show such an elevation. A two-sample t-test (average acenocoumarol treated with coumarins, because they strongly increase the INR as a result of a pharmacokine- dosage, age), and chi-square tests (sex, therapeutic range, type of NSAID) were used to test for tic interaction [4]. The inhibition of the cytochrome P450 2C9-(CYP2C9) mediated metabolism differences. Genotyping was carried out by analysing blood samples for the relevant CYP2C9 of coumarins probably plays a role. Also, displacement of protein binding sites may lead to ele- alleles. vated coumarin levels. Other NSAIDs such as diclofenac, ibuprofen and naproxen have until Results: The study population consisted of 112 patients on stable acenocoumarol therapy, of now not reported to result in an increase of the INR of patients treated with coumarins. which 52 (46%) showed an elevation of the INR above the desired therapeutic level (INR 3.5 However, as a result of a pharmacodynamic interaction the risk of bleeding may also be incre- and 4.0 respectively). In 12 patients, the INR increased above 6. The INR of the other 60 patients ased because of the inhibition of thrombocyte aggregation [4]. Furthermore damage of the gas- (54%) remained constant after the start of one of the NSAIDs under study. There were no sta- trointestinal mucosa may lead to subsequent risk of gastrointestinal bleeding. In view of these tistically significant differences between patients with increased INR and patients without adverse effects, these NSAIDs should only be used in combination with coumarins when no increased INR with regard to age, sex, therapeutic range and average acenocoumarol dosage. alternatives are available and patients are advised to monitor an increased bleeding sensitivity. Eighty patients, of whom 36 showed an increased INR as a result of a potential acenocouma- In the Netherlands, the monitoring of outpatients on oral anticoagulant treatment is con- rol-NSAID drug interaction, were included in the genotyping study. No association between ducted by Thrombosis Services [5]. At the Groningen Outpatient Thrombosis Service, physi- CYP2C9 genotype and an increased INR as a result of the drug-drug interaction was found. cians occasionally noticed an increase in INR when NSAIDs such as dicofenac, naproxen and Conclusion: In nearly half of a cohort of elderly patients, the INR increased beyond the thera- ibuprofen were added to coumarin therapy. In view of the risks of an increased INR, such as peutic range (INR 3.5 or 4.0) as a result of a potential pharmacokinetic drug-drug interaction haemorrhage, we investigated the influence of NSAID therapy on the INR in more detail. between acenocoumarol and diclofenac, naproxen and ibuprofen. The average increase in INR Furthermore, we studied the influence of several patient characteristics. It has been suggested was between 1 and 4. Risk factors identifying patients most likely to be at risk for this potential that drug-drug interactions may be partly due to genetic variability [6]. The role of pharmaco- drug-drug interaction, such as polymorphism of CYP2C9, could not be found. genomics, defined as the individualisation of drug therapies based on genetic information, in the prevention of adverse drug reactions has been highlighted in several reviews [6-8]. It was found that 59% of the drugs cited in studies on adverse drug reactions are metabolised by at least one enzyme with a variant allele known to cause poor metabolism [6]. Recently it has been demonstrated that (R)-acenocoumarol, the enantiomer that contributes mainly to the pharmacological effect is metabolised by CYP2C9 [9]. Diclofenac, naproxen and ibuprofen are also metabolised by CYP2C9 [10-13]. Furthermore, it has been described that the age-related decrease in the content and function of CYP2C9 [14] could contribute to drug-drug interactions, which could be relevant in an elderly population. Polymorphism of CYP2C9 could therefore be Data collection a risk factor for developing a clinical relevant drug-drug interaction between acenocoumarol All report forms that were issued during the period 01-10-1999 and 01-05-2000 and concer- and NSAIDs. ned one of the three NSAIDs under study, were studied. For each patient, the following data The aim of our study was to investigate whether diclofenac, naproxen or ibuprofen influ- were collected: age and sex, type of NSAID (diclofenac, naproxen or ibuprofen), dosage of ace- enced the INR of acenocoumarol users. Furthermore, we determined whether polymorphism of nocoumarol, INR values before and after the administration of the NSAIDs under study, and the CYP2C9 is associated with this potential drug-drug interaction. therapeutic range in which the patient was maintained (low (2.5-3.5) or normal (3.0-4.0)).

136 Methods Data analysis 137 For each patient a time-profile of the INR was constructed. Patients whose INR increased Setting above the upper level of the therapeutic range (3.5 and 4.0 respectively, depending on the the- The study was carried out at the Groningen Outpatient Thrombosis Service, which serves rapeutic range) after starting diclofenac, naproxen or ibuprofen in addition to the acenocou- about 11,000 patients in the province of Groningen, the Netherlands. In this anticoagulation marol therapy, were compared with patients who did not show such an increase. For each clinic, all activities with regard to monitoring and treatment of patients on coumarin therapy patient, the increase in INR was calculated as the first INR measurement after adding the are organised. For example, blood sampling is performed and laboratory determinations are NSAID minus the last INR measurement before adding the NSAID. Also, for each patient the carried out. An especially trained physician establishes the dose of the coumarin using a com- average dosage of acenocoumarol before administration of the NSAID was determined. The puter dosage program. Letters with the recommended dosages are subsequently sent to the average dosages of patients who showed an elevation in the INR and patients who did not patient. Patient and medical data are stored in a centralised database (Trombosedienst show such an elevation were subsequently calculated for each therapeutic range. Information System; TDAS). Two oral anticoagulants are available in the Netherlands: aceno- The statistical software program SPSS 10.0 for Windows (SPSS Inc., Chicago, IL) was used. coumarol and phenprocoumon. Two therapeutic ranges are distinguished: a first intensity level A two-sample t-test (acenocoumarol dosage, age) and chi-square tests (sex, therapeutic range, (INR therapeutic range 2.5-3.5), and a second intensity level (INR therapeutic range 3-4). The type of NSAID) were used to test for differences. indication and pathophysiology determines in which therapeutic range a patient is maintained. Patients with venous thromboembolic disorders, such as atrial fibrillation, are mostly maintai- Genotyping study ned in the first intensity level and patients with arterial thromboembolic diseases are mostly A genotyping study was carried out to investigate whether CYP2C9 polymorphism was maintained in the second intensity level. Patients are maintained in the therapeutic range by associated with the occurrence of the potential interaction between acenocoumarol and the regular checks of their INR. A special feature of the Groningen Outpatient Thrombosis Service NSAIDs under study. Participants were recruited from patients attending the Groningen is that all reports concerning potential coumarin-drug interactions are systematically recorded Outpatient Thrombosis Service who were initially included in the cohort study (n=112). The in a database. Medical Ethical Committee of the ‘Stichting Beoordeling Ethiek Bio-Medisch Onderzoek’ at Assen, the Netherlands, approved the study (July 06, 2001). The general practitioner (GP) of Study population each patient was contacted by telephone and by fax with details of the proposed investigation The study population consisted of outpatients on stable acenocoumarol treatment who and was asked written consent to contact their patient for inclusion in the genotyping study. received one of the NSAIDs under study. Stable acenocoumarol treatment was defined as main- Patients were included in the study after written informed consent was obtained. At their regu- tenance of the INR within limits of the therapeutic range. Patients, who used more drugs bes- lar visit for INR control, 4 ml blood was collected in EDTA tubes. DNA was isolated from blood ides the NSAID, were excluded. within 72 hours after blood was collected (High Pure PCR Template Preparation Kit, Roche). Polymerase Chain Reaction (PCR) for the CYP2C9 variants was performed with subsequent Ava II digestion (CYP2C9*2) and Nsi I and Kpn I digestion (CYP2C9*3). CYP2C9*1/*3 and CYP2C9*2 were detected by PCR-mediated site-directed mutagenesis followed by restriction analysis Table 1: Characteristics of the study population (n=112) and differences between acenocoumarol users with increased according to the methods described by Wang and colleagues (*1/*3) [15] and Steward and col- INR and acenocoumarol users without increased INR, and results of the genotyping study (n=80) leagues (*2) [16] with slight modifications. Positive controls were included for method valida- Variable Patients with increased INR (n=52) Patients without increased INR (n=60) tion. n (%) n (%) Sex# Results Male 21 (40.4) 26 (43.3) Female 31 (59.6) 34 (56.7) Age; average (± SD) # 72.2 (± 14.1) 70.9 (± 11.3) 138 The source population consisted of 244 patients. Of these patients, 132 (54%) were exclu- Age distribution 139 ded because they used more medications besides the NSAID and acenocoumarol, leading to a <60 9 (17.3) 11 (18.3) study population of 112 patients. There were no patients who used more than one NSAID. Of the 60-69 9 (17.3) 15 (25.0) 70-79 17 (32.7) 24 (40.0) 112 patients, 52 (46%) showed an elevation of the INR above the upper level of the therapeu- ≥ 80 17 (32.7) 10 (16.7) tic range after adding diclofenac, naproxen or ibuprofen to acenocoumarol therapy. The INR of Therapeutic range# the other 60 patients (54%) remained constant after the start of one of the NSAIDs under 2.5-3.5 30 (57.7) 34 (56.7) study. In table 1, patient characteristics of the study population are given. There were no statis- 3.0-4.0 22 (42.3) 26 (43.3) Type of NSAID# tically significant differences between patients with increased INR and patients without in- Diclofenac 32 (61.5) 34 (56.7) creased INR for the following variables: age, sex, type of NSAID (diclofenac, naproxen or Naproxen 8 (15.4) 16 (26.7) ibuprofen), therapeutic range, average dosage of acenocoumarol (before the NSAID was Ibuprofen 12 (23.1) 10 (16.7) added) and CYP2C9 genotype. In table 2 the average increase in INR is given, stratified for thera- Average acenocoumarol dosage (mg) before peutic range and type of NSAID. In twelve patients the INR was 6 or higher. In figure 1, a time- NSAID was added# profile is given, illustrating the elevation in INR after adding diclofenac in one patient. overall 2.7 3.1 2.5-3.5 2.8 2.9 3.0-4.0 2.6 3.2 CYP2C9 genotype¶ CYP2C9*1/*1 26 (72.2) 30 (68.2) CYP2C9*1/*2 6 (16.7) 9 (20.5) CYP2C9*2/*2 0 2 (4.5) CYP2C9*1/*3 3 (8.3) 3 (6.8) CYP2C9*2/*3 1 (2.8) 0

¶ Not all patients of the cohort (n=112) were included in the genotyping study (see also under Results): 36 patients with increased INR; and 44 patients without increased INR # None of the differences between the two groups were statistically significant (p>0.05) Table 2: Average increase of INR stratified for type of NSAID and therapeutic range in the study population (n=112) Genotyping study All GPs gave consent to contact their patients. Subsequently, 80 patients gave their written Average increase in INR (range)# informed consent to participate in the study. Thirty-one patients could not be included, due to Therapeutic range Diclofenac (n=32) Naproxen (n=8) Ibuprofen (n=12) different reasons such as hospital admission (n=5) or lost to follow-up (n=26). One patient did 2.5 –3.5 + 2.3 (0.5-8.4) + 2.8 (0.5-5.3) + 3.8 (2.0-8.6) (n=17) (n=7) (n=6) not give informed consent. In table 3, the characteristics of the patients who were included in 3.0-4.0 + 2.2 (0.3-4.8) + 1.1 + 1.5 (0.4-2.4) the genotyping study are given. The CYP2C9 genotype distribution is summarised in table 1. Ten (n=15) (n=1) (n=6) patients (27.8%) in the case group were carriers of one or two of the allelic variants of CYP2C9 140 # defined as the difference between the last INR (among patients who showed an elevation in the INR) before the compared with 14 (31.8%) of the patients in the control group (Wilson test for difference: CI95 141 start of an NSAID and the first INR after the start of an NSAID. -0.16-+0.23). Among the patients with increased INR, the allele frequencies of CYP2C9 were 84.7%, 9.7% and 5.6% for the variants CYP2C9*1, *2 and *3, respectively. Among patients without increased INR, the allele frequencies were 81.8%, 14.8% and 3.4% for the variants 7 CYP2C9*1, *2 and *3, respectively. The differences between both groups in allele frequency 6,4 were not statistically significant. For the study group as a whole (n=80), the allele frequencies 6

INR were 83.1%, 12.5% and 4.4% for the variants CYP2C9*1, *2 and *3, respectively. When we com- 5 Min.th.value pared patients having the wild-type genotype (*1/*1) with patients having one of the allelic Max.th.value 4,1 variants (*2 and/or *3), it was found that the latter group had a significantly lower dosage of 4 NSAID added² 3,8 3,9 3,8 3,7 3,6 acenocoumarol (2,3 mg versus 3,0 mg; p=0.023).

INR 3,3 3,3 3

1 Table 3: Characteristics of the patients who were included in the genotyping study (n=80)

0 Genotype CYP2C9 0 28 56 84 112 140 168 196 224 252 Variable *1/*1 *1/*2 *2/*2 *1/*3 *2/*3 Time-intervals (days) n(%) 56 (70) 15 (18.8) 2 (2.5) 6 (7.5) 1 (1.3) Sex Figure 1: Patient INR-profile showing an elevation in INR after adding diclofenac to coumarin therapy. Female 33 (58.9) 12 (80) 0 2 (33.3) 0 Male 23 (41.1) 3 (20) 2 (100) 4 (66.7) 1 (100) Age 70.8 73.7 70.0 70.8 65.0 Therapeutic range 2.5-3.5 26 (65) 9 (64.3) 1 (50) 4 (100) 0 3.0-4.0 14 (35) 5 (35.7) 1 (50) 0 1 (100) Type of NSAID Diclofenac 34 10 1 3 0 Naproxen 13 1 1 2 0 Ibuprofen 9 4 0 1 1 Acenocoumarol dosage (mg) 3.048 2.628 2.071 1.482 1.786 Discussion mentioned earlier, phenylbutazone shows a pharmacokinetic interaction with coumarins [3], resulting in an increase in INR. Other NSAIDs such as diclofenac and naproxen are reported to In this study we found that nearly half of a cohort of acenocoumarol users on average increase the risk of bleeding, but no evidence of a pharmacokinetic interaction with coumarins showed an increase in INR between 1 and 4 after diclofenac, naproxen or ibuprofen was added has been reported [20]. In an open-label study among 8 healthy volunteers no effect of piroxi- to the acenocoumarol therapy. Considering the estimation that the risk of bleeding increases cam on the pharmacokinetics of acenocoumarol enantiomers was found [21]. In a placebo- with 54% (CI95 44%-65%) for every unit increase in INR [2], these rises in INR should be con- controlled study among 56 osteoarthritis patients treatment with nabumetone for up to 4 sidered clinically relevant. Recently it was shown that patients with INRs greater than 6 have weeks did not alter INR levels compared with placebo [22]. In an open crossover study among 142 a significant short-term risk of major haemorrhage compared with patients with an in-range 6 healthy volunteers lornoxicam did not alter the pharmacokinetics of the clinically relevant 143 INR [17]. In our study, the INR of 12 patients rose above 6. This means that 11% of the study (R)-acenocoumarol or the anticoagulant activity of acenocoumarol [23]. Warfarin drug inter- population was at risk of major haemorrhage. We did not find an association between CYP2C9 actions with NSAIDs have been described more frequently, possibly due to the fact that war- genotype and the risk of an increased INR as a result of the potential pharmacokinetic interac- farin is the oral anticoagulant most widely used in the United States. One case-report descri- tion between acenocoumarol and NSAIDs. However, patients with one of the variant alleles (*2 bing a patient with a seriously prolonged INR during the combined use of warfarin and indo- or *3), had a significantly lower acenocoumarol dosage than patients without one of the variant methacin was found [24]. Recently, two case-reports [25,26] have been published showing a alleles. This could mean that acenocoumarol dosage requirements are dependent on CYP2C9 significant increase in INR after adding celecoxib, a cyclooxygenase-2 selective NSAID, to war- genotype. We are currently investigating this matter in more detail by analysing blood (R)- and farin therapy. A possible mechanism to explain this interaction could be that both medications (S)-acenocoumarol levels. are metabolised through the same cytochrome P450 pathway (namely CYP2C9). Karim and col- Thijssen and co-workers showed a strong association between acenocoumarol sensitivity legues showed no significant effect of celecoxib on pro-thrombin times or steady-state phar- and the presence of the CYP2C9*3 allele possibly due to impaired acenocoumarol clearance, in macokinetics of S- and R-warfarin in a small study with 24 healthy volunteers [27]. In an USA particular the (S)-enantiomer [18]. They stated that because of genetic polymorphism, the meta- ambulatory care anticoagulation clinic over a period of one year, 28 patients had been prescri- bolic clearance of (S)-acenocoumarol is reduced profoundly, and this enantiomer, that is nor- bed either celecoxib or rofecoxib after being stable on warfarin therapy. Thirteen of these had mally clinically inactive, may now exert main anticoagulant activity. In warfarin users, Aithal increases in INR, within this group 6 patients used only a coumarin (warfarin) with an NSAID found that patients with CYP2C9 variant alleles were found to require lower warfarin dosages (cyclo-oxygenase-2 inhibitor) [28]. These results are comparable with our results of acenocou- [19]. Our results seem to be in line with the results reported by Aithal and Thijssen. marol with NSAIDs. For celecoxib that is metabolized by CYP2C9 competitive inhibition of In this study data from patients in daily clinical practice were used, reflecting the clinical CYP2C9 metabolism could lead to this potential pharmacokinetic drug interaction. Rofecoxib is relevance of our findings. Furthermore, we restricted our analyses to patients who did not use not reported to inhibit CYP2C9. However, rofexocib is approximately 87% bound to plasma pro- any other drugs, thus making a direct cause-and-effect relationship more likely. A limitation of tein, resulting in higher free-warfarin levels and thus possibly accounting for the increasing this study is that we can not rule out confounding by indication. It is known that during episo- INRs [28]. des of fever and inflammation, the breakdown of clotting factors is increased, leading to a Different mechanisms may account for our findings. As stated earlier due to competitive greater response to coumarin therapy and thus an increased INR. The fact that we used a con- inhibition of the NSAIDs of (R)-acenocoumarol 7-hydroxylation, the plasma level of (R)-aceno- trol group that did not show an increase in INR, reduces the bias as a result of confounding by coumarol may be increased. Furthermore, inhibition of NSAIDs of the p-glycoprotein pump indication considerably. Also, we excluded patients who used other drugs simultaneously, such may account for increased acenocoumarol levels. Protein displacement processes may also play as antibiotics, further limiting confounding by indication. Finally, by stratifying patients in the- a role. CYP2C9 genotype seems to be not a risk factor for the occurrence of a potential clinical rapeutic windows, depending on the diagnosis, a further limitation of bias due to confounding relevant increase in INR as a result of the interaction between acenocoumarol and diclofenac, by indication was achieved. naproxen or ibuprofen. Although polymorphism of CYP-metabolising enzymes may play an In the literature, several reports on coumarin-NSAID interactions have been published. As important role in predicting adverse drug effects, including drug-drug interactions [6], we could not confirm this role in the case of the interaction between acenocoumarol and the NSAIDs References studied. As a result of this finding, at present we are not able to identify patients most likely to 1 Hirsch J. Oral anticoagulant drugs. New Engl J Med 1991; 324: 1865-75. be at risk for a potential clinical relevant interaction between acenocoumarol and diclofenac, 2 Van der Meer FJM, Rosendaal FR, Vandenbroucke JP, Briët E. Bleeding complications in oral anticoagulant naproxen or ibuprofen. therapy. Arch Intern Med 1993; 153: 1557-62. In conclusion, this study shows that diclofenac, naproxen and ibuprofen can lead to a clini- 3 Harder S, Thürmann P. Clinically important drug interactions with anticoagulants. An update. Clin Pharmacokinet 1996; 30: 416-44. cally relevant increase of the INR in patients treated with acencoumarol. In 11% of the study 4 Brouwers JRBJ, De Smet PAGM. Pharmacokinetic-pharmacodynamic drug interactions with nonsteroidal population, this lead to INRs above 6 with a clinically relevant risk of severe haemorrhage [17]. anti-inflammatory drugs. Clin Pharmacokinet 1994; 27: 462-85. 144 Genetic polymorphism of CYP2C9 did not contribute to the occurrence of this potential clinical 5 Breukink-Engbers WG. Monitoring therapy with anticoagulants in the Netherlands. Seminars in Trombosis 145 relevant interaction. In view of the widespread use of NSAIDs and the fact that these drugs can & Hemostasis 1999; 25: 37-42. 6 Philips KA, Veenstra DL, Oren E, Lee JK, Sadee W. Potential role of pharmacogenomics in reducing adverse drug be purchased without a doctor’s prescription, further prospective studies on this drug-drug reactions. JAMA 2001; 286: 2270-9. interaction should be initiated. In the meantime, adequate surveillance and close monitoring 7 Roland Wolf C, Smith G, Smith RL. Pharmacogenetics. BMJ 2000; 320: 987-90. of the INR of patients receiving these drugs concomitantly is warranted. 8 Meyer UA. Pharmacogenetics and adverse drug reactions. Lancet 2000; 356: 1667-71. 9 Thijssen HH, Flinois JP, Beaune PH. Cytochrome P450 2C9 is the principal catalyst of racemic acenocoumarol hydroxylation reactions in human liver microsomes. Drug Metab Dispos 2000; 28: 1284-90. Acknowledgements 10 Klose TS, Ibaenu GC, Ghanayem BI, Pedersen LG, Li L, Hall SD, et al. Identification of residues 286 and 289 as critical for conferring substrate specificity of human CYP2C9 for diclofenac and ibuprofen. Arch Biochem Biophys 1998; 357: 420-8. We are grateful to C.Th. Smit Sibenga, PhD, and his colleagues from the Bloedbank Noord 11 Bliesath H, Huber R, Steinijans VW, Koch HJ, Wurst W, Mascher H. Lack of pharmacokinetic interaction between Nederland, Groningen, the Netherlands, for their co-operation in transporting patient blood pantoprazole and diclofenac. Int J Clin Pharmacol Ther 1996; 34 (suppl 1): S76-80. samples. We thank the laboratory assistants of the Outpatient Thrombosis Service Groningen, 12 Leemann T, Transon C, Dayer P. Cytochrome P450 TB (2C9): a major monooxygenase catalyzing Groningen, the Netherlands, for their co-operation in taking blood samples. Furthermore we diclofenac 4’-hydroxylation in human liver. Life Sci 1993; 52: 29-34. 13 Miners JO, Coulter D, Tukey RH, Veronese ME, Birkett DJ. Cytochromes P450, 1A2 and 2C9 are responsible for the are grateful to the laboratory assistants of the Clinical Chemistry Laboratory at Leeuwarden for human hepatic O-demethylation of R- and S-naproxen. Biochem Pharmacol 1996; 51: 1003-8. their help in the genotyping part of the study. C.S. de Vries, PhD, RPh, is thanked for her valu- 14 Sotaniemi EA, Arranto AJ, Pelkonen O, Pasanen M. Age and cytochrome P450-linked drug metabolism in able comments on the manuscript. humans: an analysis of 226 subjects with equal histopathological conditions. Clin Pharmacol Ther 1997; 61: 331-9. 15 Wang S-L, Huang J-D, Lai M-D, Tsai J-Jl. Detection of CYP2C9 polymorphism based on polymerase chain reaction in Chinese. Pharmacogenetics 1995; 5: 37-42. 16 Steward D, Haining RL, Henne KR, Davis G, Rushmore TH, Trager WF, Rettie AE. Genetic association between sensitivity to warfarin and expression of CYP2C9*3. Pharmacogenetics 1997; 7: 361-7. 17 Hylek EM, Chang YC, Skates SJ, Hughes RA, Singer DE. Prospective study of the outcomes of ambulatory patients with excessive warfarin anticoagulation. Arch Intern Med 2000; 160: 1612-7. 18 Commissie Interacterende Medicatie Cumarines. Standaard afhandeling cumarine-interacties (in Dutch). Wetenschappelijk Instituut Nederlandse Apothekers (WINAp). The Hague, The Netherlands, 1999. 19 Thijssen HHW, Verkooyen IWC, Frank HLL. The possession of the CYP2C9*3 allele is associated with low dose requirement of acenocoumarol. Pharmacogenetics 2000; 10: 1-4. 20 Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphism in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet 1999; 353: 717-9. 21 Bonnabry P, Desmeules J, Rudaz S, Leemann T, Veuthey JL, Dayer P. Stereoselective interaction beween piroxicam and acenocoumarol. Br J Clin Pharmacol 1996; 41: 525-30. 22 Pardo A, Garcia-Losa M, Fernandez-Pavon A, Castillo del S, Pacual-Garcia T, Garcia-Mendez E, et al. A placebo-controlled study of interaction between nabumetone and acenocoumarol. Br J Clin Pharmacol 1999; 47: 441-4. 23 Masche UP, Rentsch KM, von Felten A, Meier PJ, Fattinger KE. No clinically relevant effect of lornoxicam intake on acenocoumarol pharmacokinetics and pharmacokinetics. Eur J Clin Pharmacol 1999; 54: 865-8. 24 Chan TY. Prolongation of prothrombin time with the use of indomethacin and warfarin. Br J Clin Pract 1997; 51: 177-8. 25 Haasse KK, Rojas-Fernandez CH, Lane L, Frank DA. Potential interaction between celecoxib and warfarin (letter). Ann Pharmacother 2000; 34: 666-7. 26 Mersfelder TL, Stewart LR. Warfarin and celecoxib interaction. Ann Pharmacother 2000; 34: 325-7. 27 Karim A. Tolber D, Piergies A, Hubbard RC, Harper K, Wallemark CB, Slater M, Geis GS. Celecoxib does not significantly alter the pharmacokinetics or hypoprothrombinemic effect of warfarin in healthy subjects. J Clin Pharmacol 2000; 40: 655-63. Chapter 4 28 Stading JA, Skrabal MZ, Faulkner MA. Seven cases of interaction between warfarin and cyclooxygenase-2 146 inhibitors. Am J Health-Syst Pharm 2001; 58: 2076-80. 147

General discussion and perspectives Pharmacotherapy in frail elderly the potential risks associated with drug use in these nursing homes. Pharmacy dispensing data for 2,355 residents were retrieved. It was found that the hospital pharmacy data were, in gener- People residing in Dutch nursing homes are mostly frail, elderly people who are dependent al, accurate, although completeness of discharge and admission date recording could be impro- on continuous nursing and medical attention. Pharmacotherapy in this elderly group is an ved. With these data, the duration of stay in the nursing home could be calculated, as well as important aspect of medical care. Drugs obviously have beneficial effects in the very old. For the duration of drug use. Hospital pharmacy data proved to be an important data source, ena- example, the use of statins should not be limited to people younger than 70 years, as statins bling the performance of drug utilisation and drug safety studies. We demonstrated the impor- can reduce the risk of myocardial infarction even in the very old [1,2]. In addition, the benefits tance of accurate and precise recording in the hospital pharmacy, of prescription data for indi- 148 of oral anticoagulant therapy in patients suffering from atrial fibrillation, have been well ack- vidual nursing home patients in order to reliably determine drug exposure. The main findings 149 nowledged. For some therapies, such as hormone-replacement therapy in elderly women for and implications of these studies are described below. First, a drug utilisation study was per- reducing the risk of osteoporosis [3], it is not yet clear who will receive the most benefit. formed. We found high numbers of drug users and the chronic use of many drugs. This study However, the impact of adverse effects of pharmacotherapy in the frail elderly is generally higher revealed several potential problem areas regarding the prescribing of drugs in the nursing than in other populations. Non-steroidal anti-inflammatory drugs (NSAIDs) may lead to renal home setting. Prescribing of loop diuretics, laxatives, psychotropic drugs and ulcer-healing dysfunction [4], anticholinergic drugs to confusion and delirium [5], and psychotropic drugs to drugs deserved attention, in view of high dosages, long-term use and a high proportion of falls and fractures [6], often with significant impact on the quality of life. Therefore, the risks of users. Prescribing practices in individual nursing homes regarding these drug groups may sub- drug therapy should be carefully weighed against the potential beneficial effects, especially in sequently be evaluated in pharmacotherapeutic discussion meetings or, on the level of an indi- this vulnerable group of elderly persons. Pharmacoepidemiologic studies can provide insight vidual patient in a one-to-one discussion with the prescriber. Hospital pharmacists can play a into this delicate balance. The benefits of drug use are mainly studied in randomised control- key role in these evaluations since they have the tools to analyse individual prescription data. led clinical trials (RCTs). Observational studies are less suitable for evaluating the benefits of From the drug utilisation studies, several determinants of drug use were found. Sex was found drug use in view of biases and confounding issues such as selection by disease severity. to be a determinant of drug use in several cases, as was the type of care. It was shown that in However, observational studies are often used to study adverse drug effects. This is due to drug utilisation studies it is important to distinguish between nursing home residents residing various considerations. These include differences between the experimental RCT setting and in psychogeriatric nursing homes, and those residing in somatic nursing homes as drug use prescribing in daily clinical practice such as co-morbidity and comedication profiles and diffe- substantially differs between these populations. As expected, nursing home residents residing rences in patient age. This thesis is largely based on observational studies. in psychogeriatric nursing homes use more psycholeptic drugs (psychotropics and anxiolytics) and less antithrombotic drugs, diuretic drugs and antacids than residents residing in somatic Pharmacoepidemiology in frail elderly nursing homes. Also, somatic residents showed a higher risk for the occurrence of potential drug-drug interactions (DDIs). Female residents were more likely than male residents to expe- Organisational differences between nursing homes in the Netherlands and in other coun- rience a potential DDI and were more likely to receive NSAIDs, antirheumatic drugs and psy- tries, in particular the United States, will have an impact on drug utilisation. Consequently, fin- choanaleptic drugs. Male residents were more likely to receive psychotropic drugs. Other deter- dings from one health care setting cannot automatically be considered true for another setting. minants of drug use found were the number of medications prescribed. Residents with a hig- Therefore, to gain insight into local drug use, it is important that drug utilisation studies are her number of medications were more at risk for the occurrence of potential DDIs than resi- performed within the applicable health care system. This thesis reports on an investigation of dents with fewer drugs. Patients with Parkinson’s disease were less likely to be exposed to drug use and drug-related problems in the elderly in the Netherlands, in particular those resi- potential DDIs. ding in nursing homes. To draw conclusions regarding drug use and safety, a sufficiently large In view of the high frequency of drug use, we studied the potential risks of polypharmacy number of subjects is needed. We collected pharmacy dispensing data from 6 nursing homes. by carrying out a descriptive study on the extent and occurrence of potential DDIs. Several pre- In this way, we were able to study the extent of drug use, problem areas in drug prescribing and scribing indicators were used to assess the occurrence and nature of DDIs, such as the number of residents exposed to a DDI, the prevalence of a DDI, the percentage of days of concomitant feasible to perform a prescription-sequence analysis using pharmacy data in the nursing home drug use, and the drugs most frequently involved in a DDI. Approximately one-third of the nur- setting. Although the constipating effects of certain drugs should be taken into account, this sing home residents was exposed to at least one clinically relevant DDI. However, for each may not necessarily explain the high rate of laxative use found in the nursing homes we stu- clinically relevant DDI registered, no more than 10% of the residents were affected. This indi- died. Effects of dietary factors and physical activity on laxative use needs further investigation. cates that not one DDI was identified that could be considered potentially harmful to many The studies discussed above were carried out to identify problem areas in drug prescribing in residents. The interaction between NSAIDs and loop diuretics, and between NSAIDs and oral the elderly, especially those residing in nursing homes. Results of these studies may help to anticoagulants were the potential DDIs most frequently encountered (9.7% and 9.6% of the identify patients at increased risk of drug-related problems. 150 study population respectively). It is important to know whether these potential DDIs actually 151 lead to clinically adverse outcomes. At present, the perceived clinical relevance of DDIs is often How to identify patients at risk? based on theoretical considerations and case-reports [7]. However, the actual clinical relevance is unknown. Studies should be undertaken investigating the clinical effects of DDIs in order To enable the identification of patients at risk of drug-related problems, more information to identify both DDIs that are likely to cause problems and people at a higher risk of developing than pharmacy data alone is needed. Clinical data and information from prescribers can provi- these problems [8]. In particular the frail elderly have a high risk of potential DDIs and drug- de insight into clinical outcomes, as well as into any preventive measures that have already disease interactions as a result of polypharmacy and co-morbidity, and knowledge on the been undertaken and how these patients are currently being monitored. One way to identify clinical relevance of DDIs could contribute to a safer use of drugs. At present, it is often difficult patients at risk of unwanted pharmacotherapy effects, is to use prescribing indicators to signal to collect data on individual clinical outcomes, such as laboratory test results, on a large scale potentially suboptimal prescribing. Although many prescribing indicators have been developed because these data are often not stored in easily accessible files. Subsequently, we investiga- and used internationally [9], few of these can be used with pharmacy prescription data and few ted in more detail the co-prescribing of several drug groups frequently used in the nursing are specific for drug-related problems common in nursing homes. In a pilot study [10], we found home population. We evaluated co-prescribing of benzodiazepines and antidepressant thera- that a set of prescribing indicators developed on the basis of current pharmacotherapy guide- py to investigate previously reported differences in co-prescribing between tricyclic antide- lines, could be used to evaluate prescribing practices in nursing homes and to identify patients pressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs). We found that in elderly at risk of potential suboptimal prescribing. However, information from the prescriber on clini- outpatients the risk for initiating benzodiazepines during antidepressant therapy was higher cal data was needed to identify patients who were actually at risk for drug-related problems. In for SSRI users than for TCA users. However, in the nursing homes patients no such difference some cases, deviation from national guidelines and drug formularies may not mean that the was found. This study also illustrated the need to perform drug utilisation studies in different patient is treated suboptimally. This discrepancy between potential and actual inappropriate elderly populations as the results may differ depending on which population is studied. In prescribing has been reported earlier [11] and stresses the importance of taking the patient’s another study we investigated co-prescribing of NSAIDs and gastroprotective drugs in elderly clinical response and the prescribers’ rationale into consideration. Furthermore, it is often dif- outpatients. It was found that 23% of NSAID users aged 65 and over were co-prescribed gastro- ficult to define prescribing indicators that actually reflect potential suboptimal prescribing. protective drugs. Given this finding, initiatives should be taken to increase gastroprotective Although evidence-based practice guidelines may serve as a basis, these sometimes differ from drug use in elderly NSAID users. Also, more insight is needed into the reasons concerning why expert opinions [12]. In nursing home practice, evidence-based guidelines are just beginning to prescribing gastroprotective drugs were not more frequently prescribed to this high-risk group. emerge, and the lack of specific nursing home guidelines hampers the development of good Finally, to investigate the determinants of the high frequency of laxative use in the nursing prescribing indicators in this setting. In many cases, however, prescribing indicators can be homes in more detail, a study was carried out to see whether laxative use was the consequen- used to signal potentially suboptimal prescribing, as was also found in recent studies [12,13]. ce of prescribing constipating drugs, such as anticholinergics. It was shown that drugs classi- Together with clinical data, such as laboratory values or clinical outcomes, the risks for the fied as moderately to severely constipating were associated with laxative use. However, the patient can be adequately perceived and preventive measures taken on both an individual association was not as strong as previous studies have suggested. This study showed that it is patient and population-based level. In our view, the pharmacological knowledge of the hospital pharmacist together with the clinical knowledge of the nursing home physician may act pital pharmacy computer systems. synergistically in detecting drug-related problems in the elderly. Also other caregivers, such as • Clinical status of the patient: this includes diagnoses, data from the nursing home physi- nurses, may play an important role in signalling adverse drug effects in clinical nursing home cians and medical specialists visits, and clinical outcomes. In Dutch nursing homes, these practice. data are manually recorded in the patients’ medical chart. Sometimes electronic patient The ultimate question, however, is whether potentially suboptimal prescribing leads to records are available. actual clinical problems [14]. We investigated this with respect to a frequently occurring, potential DDI. The potential DDI between acenocoumarol and NSAIDs constitutes one of the most Quality of life 152 frequently encountered DDIs in the nursing home study population and to date its clinical rele- 153 vance remains unknown. The study presented in this thesis found that this interaction led to a It could be argued, that together with clinical outcomes such as the frequency of adverse events clinically relevant outcome in about half of all elderly outpatients exposed, namely the increa- another issue that needs to be taken into account is the quality of life (QoL) in the frail elderly se of the prothrombin ratio expressed as the international normalised ratio (INR) above the population. For instance, in clinical practice the impact of side effects from ACE-inhibitors in therapeutic window. To be able to identify patients at risk for this drug-drug interaction, sever- this population, is higher than in the general population. This may lead to a more adverse risk al patient characteristics were investigated as potential determinants. One of the determinants - benefit balance. The impact of various drug-related problems on this populations’ quality of we included was genetic polymorphism of cytochrome P450 2C9 (CYP2C9). This enzyme is life, will therefore be different to that in the general population. Measuring QoL, however, is not involved in the metabolism of numerous drugs including acenocoumarol and NSAIDs, such as something that is routinely done in nursing home patients and such data are not readily avai- diclofenac, naproxen and ibuprofen. We hypothesized that patients with a variant allele on lable. In the elderly, the ‘Short Form-36’ (SF36) is regarded as a suitable, reliable and valid CYP2C9 (CYP2C9*2 and CYP2C9*3) would be more likely to experience the increase in pro- questionnaire and outcome tool [16,17]. However to our knowledge, this questionnaire has thrombin time due to the DDI. We found that none of the determinants investigated was asso- been used only in community-dwelling elderly and not in Dutch nursing home residents. A high ciated with the occurrence of increase in prothrombin time. However, patients with one of the incidence of non-completion on SF36 questions relating to physical and mental function has variant alleles mentioned above, required a lower dose of acenocoumarol than patients who been reported [16]. In nursing homes the prevalence of physical and mental disorders among had the wild-type genotype and we are currently investigating this matter in more detail. In the residents is much higher and therefore the SF-36 is possibly not a suitable tool for measuring meantime, all patients who are prescribed acenocoumarol and an NSAID simultaneously QoL. It is with these considerations in mind, that we believe that routinely measuring QoL in should be monitored, in view of the increased risk for elevated INR levels. nursing home patients is probably not one of the first issues to focus on. Instead, QoL should The studies described above, show the importance of capturing data on drug use as well as be taken into account when the effects of drug use are evaluated on an individual basis where data on clinical variables to be able to identify patients at risk for drug-related problems. The relevant or when possible. following clinical variables should be included: • Laboratory test values: insight into potassium levels, creatinine levels, INR, glucose Future perspectives levels, cholesterol levels and other parameters is often necessary to identify adverse effects of drug therapy such as decreased renal function as a result of NSAID therapy. Optimal use of clinical and pharmacy data to monitor drug effects These data are often available in clinical chemistry laboratory computer systems, and Efforts should be directed towards optimal use of existing clinical, pharmacy and laborato- sometimes in the nursing home computer systems. Hard copies of the laboratory test ry records. This may lead to several advances in the pharmacotherapeutical care of the frail results are available in the medical chart of the patient. In the near future, results of elderly. First, on the basis of clinical characteristics individual patients could be monitored pro- genotyping may also be available [15]. spectively regarding potential adverse drug effects and adverse outcomes. Record-linkage of • Serum drug levels: information on serum drug levels may be needed to determine the cli- pharmacy and clinical data provides an excellent opportunity to optimally use both sources of nical relevance of certain drug-drug interactions. These data are routinely stored in hos- information. In the nursing home setting, most relevant information is available. Since not all clinical information is stored in automated databases, initiatives should be taken to stimulate have all been associated with an increased risk of falls in nursing home residents. However, computerised recording of such information. In our study, we used data from a national nursing other clinical outcomes have been studied less frequently. An example is the association home database (SIVIS) to obtain information on clinical diagnoses. Attention should be given between bowel function and anticholinergic drug use [26]. Quality of life could also be an to accurate recording of SIVIS diagnoses, as we found several discrepancies between SIVIS important outcome when the risks and benefits of drug use in the frail elderly are balanced. data and pharmacy data. For example, it is highly unlikely that an antidiabetic drug is prescri- While the number of life years gained often plays a decisive role in determining the value of a bed without a registered indication of diabetes mellitus. Data on INR were collected for inves- pharmacotherapeutic intervention, this may not be the case in the frail elderly. The impact of tigating the clinical relevance of the potential pharmacokinetic interaction between acenocou- adverse drug effects is much higher in this group, and quality of life could in some cases deter- 154 marol and NSAIDs. Such data were not readily available in computerised databases. It has been mine whether or not drug therapy should be started. For example, in the treatment of heart fai- 155 shown that computerised surveillance of adverse drug reactions (ARDs) is feasible in hospitals lure, the adverse effects of drug therapies may be more important than the number of life years [8,18]. Others have suggested that detecting adverse drug reactions would be more effective gained. and less time-consuming if electronic patient records were available [18]. Ideally, all medical information of individual patients should be available on an electronic patient record. Role of the hospital pharmacist Electronic patient records are not usually available in Dutch nursing homes but initiatives are There are various stages at which hospital pharmacists can play a key role in monitoring currently being developed to change this. In primary care, an electronic ‘care card’ is being drug-related problems in frail, elderly people. Firstly, hospital pharmacists have the opportuni- developed, on which all patient related medical information is stored. In this way, health care ty to use pharmacy data for drug utilisation research. The studies in this thesis have demon- professionals can gain insight into the patient information needed in order to carry out their strated that hospital pharmacy data are a useful tool for studying the use and effects of drugs professional duties. This is particularly advantageous when patients are admitted from home in the elderly, especially in the nursing home setting. Further use of these data for research to hospital and or from nursing home to hospital and vice versa. In this way, optimal seamless should be encouraged, which implies the development of initiatives for anonymous and conti- care can be provided. An issue that should be considered here, is patient privacy. Information nual data collection. Special export files [27] would facilitate the building of a database that can that is not needed for carrying out professional activities should be seperated from information be continuously updated with current data from pharmacies. The fact that the number of hos- that is necessary. This can easily be done once the data is in electronic format. Another advan- pital pharmacies using the same computer system is still increasing in the Netherlands contri- tage of the use of electronically available patient information, is the possibility for monitoring butes to the building of such a database and further collaboration is needed between hospital patient outcomes on real-time basis as information on drug use and clinical outcome can sto- pharmacies on this point. In particular, collaboration in the field of nursing home medicine red in the same database. In the meantime, different databases can be record-linked to provi- could contribute to the creation of large databases for adequate performance of drug utilisa- de the opportunity of real-time monitoring for drug-related problems. Internationally, it has tion and safety studies. An important prerequisite is that the prescription data cover a suffi- already been shown that it is feasible to record-link patient-specific information that is stored ciently long period, preferably several years. Initiatives concerning hospital prescription data separately into large databases to monitor and evaluate effects of drug use in large populations arising from the Stichting Farmaceutische Kengetallen (SFK), an organisation that forms part of (MEMO [19], SAGE [20]). the Royal Dutch Association for the Advancement of Pharmacy (KNMP), are currently being A second advantage of combining existing clinical, pharmacy and laboratory records, is the explored. Secondly, hospital pharmacists can play an important role in initiating and conduc- possibility to study outcomes of drug use in more detail and to establish reliable risk-benefit ting pharmacoepidemiology research in nursing homes. Special interest groups could be for- analyses of drug use. Outcomes that could be studied are hospital admissions, adverse drug med, to facilitate and carry out research projects related both to drug-related problems and effects and quality of life, although as discussed earlier, measuring the latter is difficult. other relevant clinical outcomes in the nursing home. Monitoring of ADR occurrence is also an Relatively little is known about the relationship between drug use and clinically adverse out- issue in which hospital pharmacists could play an essential role as they have the tool to gather comes in nursing homes in the Netherlands. Internationally, many studies have focussed on relevant information from prescribers and patients. falls and fractures [6,21-25]. Psychotropic drugs, such as antidepressants and benzodiazepines, Finally, the studies in this thesis show that use of existing clinical and laboratory data is important to estimate the clinical relevance of drug-related problems, such as drug-drug inter- References actions. These can be monitored and studied both on an individual and on a population based 1 Rackley CE. CME paper: elderly patients at risk for coronary heart disease or stroke: selecting an ideal product level. Co-operation with other health care organisations, such as Outpatient Thrombosis for lipid lowering. Am J Geriatr Cardiol 2001; 10: 77-82. Services and Clinical Chemistry Laboratories, can contribute to the optimal use of existing 2 Hunt D, Young P, Simes J, et al. Benefits of pravastatin on cardiovascular events and mortality in older patients experience and data. with cornonary heart disease are equal to or exceed those seen in younger patients. Ann Intern Med 2001; 134: 931-40. 3 Recker RR, Davies KM, Dowd RM, Heaney RP. The effect of low-dose continuous estrogen and progesterone therapy with calcium and vitamin D on bone in elderly women. A randomized, controlled trial. 156 Ann Intern Med 1999; 130: 897-904. 157 4 Field TS, Gurwitz JH, Glynn RJ, Salive ME, Gaziano JM, Taylor JO, Hennekes CH. The renal effects of nonsteroidal anti-inflammatory drugs in older people: findings from the established populations for epidemiologic studies in the elderly. J Am Geriatr Soc 1999; 47: 507-11. 5 Gray SL, Lai KV, Larson EB. Drug-induced cognition disorders in the elderly. Incidence, prevention and management. Drug Saf 1999, 21: 101-22. 6 Thapa PB, Gideon P, Fought RL, Ray WA. Psychotropic drugs and risk of recurrent falls in ambulatory nursing home residents. Am J Epidemiol 1995; 142: 202-11. 7 Stockley IH. Drug Interactions. 2nd Ed. Oxford: Blackwell Scientific Publications, 1991. 8 Azaz-Livshits T, Levy M, Sadan B, Shalit M, Geisslinger G, Brune K. Computerized surveillance of adverse drug reactions in hospital: pilot study. Br J Clin Pharmacol 1998; 45: 309-14. 9 Shelton PS, Fritsch MA, Scott MA. Assessing the medication appropriateness in the elderly. A review of available measures. Drugs & Aging 2000; 16: 437-50. 10 Van Dijk KN, Pont LG, Franken M, De Vries CS, Brouwers JRBJ, De Jong-Van den Berg LTW. Prescribing indicators as a tool to evaluate drug use in nursing homes: a pilot study. Submitted 11 Oborne CA, Batty GM, Maskrey V, Swift CG, Jackson SHD. Development of prescribing indicators for elderly medical inpatients. Br J Clin Pharmacol 1997; 43: 91-7. 12 Zahn C, Sangl J, Bierman AS, Miller MR, Friedman B, Wickizer SW, Meyer GS. Potentially inappropriate medication use in the community-dwelling elderly. JAMA 2001; 286: 2823-9. 13 Knight EL, Avorn J. Quality indicators for appropriate medication use in vulnerable elders. Ann Intern Med 2001; 135: 703-10. 14 Avorn J. Improving drug use in elderly patients: getting to the next level. JAMA 2001; 286: 2866-8. 15 Ensom MH, Chang TK, Patel P. Pharmacogenetics: the therapeutic drug monitoring of the future? Clin Pharmacokinet 2001; 40: 783-802. 16 Fowler RW, Congdon P, Hamilton S. Assessing health status and outcomes in a geriatric day hospital. Public Health 2000; 114: 440-5. 17 Ray WA, Stein CM, Byrd V, Shorr R, Pichert JW, Gideon P, Arnold K, Brandt KD, Pincus T, Griffin MR. Educational program for physicians to reduce use of non-steroidal anti-inflammatory drugs among community-dwelling elderly persons: a randomized controlled trial. Med Care 2001; 39: 425-35. 18 Emerson A, Martin RM, Tomlin M, Mann RD. Prospective cohort study of adverse events monitored by hospital pharmacists. Pharmacoepidemioly and Drug Safety 2001; 10: 95-103. 19 Evans JJ, MacDonald TM. Record-linkage for pharmacovigilance in Scotland. Br J Clin Pharmacol 1999; 47: 105-10. 20 Gambassi G, Landi F, Peng L, Bostrup-Jensen C, Calore K, Hiris J, Lipsitz L, Mor V, Bernabei R. Validity of diagnostic and drug data in standardised nursing home resident assessments: potential for geriatric pharmacoepidemiology. SAGE Study Group. Med Care 1998; 36: 167-79. 21 Mustard CA, Mayer T. Case-control study of exposure to medication and the risk of injurious falls requiring hospitalization among nursing home residents. Am J Epidemiol 1997; 145: 738-45. 22 Ray WA, Thapa PB, Gideon P. Benzodiazepines and the risk of falling in nursing home residents. Summary J Am Geriatr Soc 2000; 48: 682-5. 23 Thapa PB, Gideon P, Cost TW, Milam AB, Ray WA. Antidepressants and risk of falls among nursing home residents. N Engl J Med 1998; 339: 875-82. This thesis focuses on drug use in the elderly, in particular those residing in Dutch nursing 24 Yip YB, Cumming RG. The association between medications and falls in Australian nursing home residents. homes: the frail elderly. These elderly are especially prone to drug-related problems because of Med J Aust 1994; 160: 14-8. 25 Wang PS, Bohn RL, Glynn RJ, Mogun H, Avorn J. Zolpidem use and hip fractures in older people. their age, frequently occurring co-morbidity and polypharmacy. Relatively little is known of J Am Geriatr Soc 2001; 49: 1685-90. drug use and drug-related problems in these frail elderly. The studies described in this thesis 26 Monane M, Avorn J, Beers MH, Everitt DE. Anticholinergic drug use and bowel function in nursing home aim to increase the knowledge on drug use and drug-related problems in this population. The patients. Arch Intern Med 1993; 153: 633-8. 158 27 De Vries CS, Van den Berg PB, Timmer JW, Reicher A, Blijleven W, Tromp ThFJ, De Jong-van den Berg LTW. thesis comprises four main parts. 159 Prescription data as a tool in pharmacotherapy audit: (II) the development of an instrument. Pharm World Sci 1999; 21: 85-90. In chapter 1, the introductory chapter, the scope and the objective of this thesis are described and the problems of drug use in elderly people are outlined. Because of co-morbidity, reduced homeostatic mechanisms and the prescription of several drugs simultaneously, elderly people are at an increased risk of drug-related problems such as drug-drug interactions, drug- disease interactions and adverse drug effects. Drugs may also inadvertently be withheld from the elderly, sometimes as a result of underdiagnosing. In view of these considerations, prescribers need a thorough understanding of the risks and benefits of drug therapy in the elderly, especially in the frail elderly, most of whom will be residing in nursing homes. In the Netherlands, relatively few epidemiological studies on drug use in nursing homes have been carried out. The objective of this thesis is to provide insight in the extent, determinants and characteristics of drug use, as well as the outcomes of drug use in frail elderly. Section 1.2 gives an overview of the Dutch health care system for ambulatory and institutionalised elderly. The Dutch nursing home is a healthcare institution for chronically ill persons in need of permanent medical and paramedical attention and complex nursing care. The type of care can be characterised as continuous, long-term, systematic and multidisciplinary. Recently it was concluded that quality aspects should be more incorporated in medication distribution processes and in pharmaceutical care activities in Dutch nursing homes. Hospital pharmacists play a role in drug and therapeutics committees, the evaluation of prescribing practices on patient level, and development and implementation of drug formularies.

Chapter 2 describes several studies that investigated drug use in nursing home residents and elderly outpatients. The first part describes the studies performed in nursing home residents. In section 2.1 an introduction is given to the field of drug utilisation studies and studies that describe the quality of drug use in nursing homes. Many studies have investigated the extent of drug use, whereas only few studies used longitudinal prescription data to evaluate drug effects over time. The studies showed an average number of drugs prescribed per resident ranging from 2.5 to 8.8. The studies that were carried out in the Netherlands involved relative- ber of different drugs (based on 5th level of Anatomical Therapeutic Chemical (ATC) code) per ly small numbers of residents, and did not study overall drug use on individual patient level. In resident was 8.9 (SD 4.9). Duration of drug use was relatively long: eight of the ten therapeutic particular in the United States, much attention has been given to rationality and appropriate- drug groups prescribed most frequently were used for more than 50% of the time spent in the ness of prescribing in nursing homes. Several studies have focused on applying tools, also nursing home. In particular psycholeptic drugs, diuretics, and laxatives were used chronically referred to as quality or prescribing indicators, to measure medication appropriateness. These (83%, 81% and 80% of the nursing home stay, respectively). Except for laxatives and diuretics, studies have shown that a considerable proportion of the nursing home residents received the prescribed daily dosages were relatively low. We concluded that drug use in the nursing inappropriate prescribing. However, prescribing indicators used in one health care system are homes was high and many drugs were used chronically. In view of possible adverse effects and 160 not automatically applicable to other health care systems due to differences in pharmacothe- the risks of parallel prescribing and drug-drug interactions, the prescribing of psycholeptic 161 rapy guidelines and drug formularies. Section 2.2 describes how computerised medication drugs, laxatives, loop diuretics, and ulcer-healing drugs should be re-evaluated. In section 2.4 order data were used to build a nursing home database with the aim to perform drug utilisa- a study is presented on drug-drug interactions (DDIs) in the nursing home. We developed pre- tion studies. We collected medication order data of all nursing home residents from 6 nursing scribing indicators based on the frequency, nature and duration of DDIs to systematically homes in Friesland, the Netherlands, for a 2-year study period between 01-10-1993 and 01-10- assess potential DDIs in the cohort of nursing home patients. We found 32% of all residents 1995. These records were subsequently record-linked with a national information system on were exposed to at least one clinically relevant DDI. The number of medications prescribed was nursing home residents (SIVIS). The SIVIS database contains information on medical (such as a strong predictor of the occurrence of a potential DDI. Drug groups most frequently involved in diagnoses), nursing (such as activities of daily living and mobility) and administrative data col- DDIs were oral anticoagulants, antibiotics and theophylline. The interaction between non-ste- lected on individual nursing home residents. The source population consisted of 2,966 patients. roidal anti-inflammatory drugs (NSAIDs) and loop diuretics, and between NSAIDs and oral As a result of the record-linkage with SIVIS, missing data and age-limits (residents aged < 65 anticoagulants were the potential DDIs most frequently encountered. The number of days on years were excluded), the final study population consisted of 2,355 residents. We have made which drugs were prescribed concomitantly was relatively high. Nineteen out of 32 DDIs were several recommendations for those who want to collect medication order data from nursing prescribed for an average of 50 days or more per 100 days of index drug use. The prescribing home residents to perform pharmacoepidemiological studies. For example, an adequate samp- indicators developed in this study provide the tools to audit DDI occurrence in nursing homes le size is necessary, and data confidentiality must be guaranteed. Data should be as accurate systematically. Finally, in section 2.5 a pilot study is presented that used several prescribing and complete as possible, which can be ensured by adequate data entry in hospital pharmacy indicators, based on the studies in sections 2.3 and 2.4, to evaluate drug prescribing in Dutch computer systems and checks against other sources, e.g. SIVIS data. Furthermore, it is impor- nursing homes. We evaluated prescribing of benzodiazepines, NSAIDs, ulcer-healing drugs and tant that the data can be collected on a continuous basis, as longitudinal data are required to diuretics. Prescribing indicators were used to identify prescribing that was potentially not in study drug use over time. Keeping individual medication histories for several years is therefo- line with recommendations in national and regional prescribing guidelines. Both descriptive re a prerequisite. Another important aspect is the registration of admission and discharge dates indicators, such as percentage of users, and indicators reflecting potentially suboptimal pre- in (pharmacy) computer systems so actual duration of stay in the nursing home can be calcu- scribing, such as use of drugs outside the drug formulary and prescription of drug dosages lated and provide person time as the denominator when studying person time exposed to above recommended values were used. We found the majority of prescribing to be in line with drugs. We found little agreement between SIVIS diagnoses data and pharmacy prescription recommendations upon which we based our prescribing indicators. Clinical information from data for both diabetes mellitus and Parkinson’s disease, indicating that both pharmacy data and the prescriber was necessary to get insight into actual prescribing appropriateness. The second SIVIS should be verified against each other in order to get the right estimation of disease pre- part of chapter 2 describes two drug utilisation studies that were performed in ambulatory valence in the nursing home population. In section 2.3 we performed a drug utilisation study elderly, and partly in nursing home patients. Section 2.6 presents a study on the concomitant among 2,355 nursing home residents. During the two-year study period, 89%, 77% and 56% use of benzodiazepines and antidepressants in two cohorts of elderly outpatients and the nur- of the study population used a drug from ATC main group N (central nervous system), A (ali- sing home cohort. We assessed whether differences in co-prescribing between tricyclic antide- mentary tract and metabolism), and C (cardiovascular system), respectively. The average num- pressants (TCAs) and selective serotonine reuptake inhibitors (SSRIs) existed. Pharmacy dispensing data from the InterAction database were used for the study among ambulatory elder- drugs that exhibit moderately to strongly constipating effects and occurrence of constipation ly. We found that in two cohorts of elderly (one during 1994-1995 and one during 1998-1999) the was found, the risk was not as high as seen in previous studies. In section 3.2 the clinical effect risk of initiating benzodiazepine drug therapy during antidepressant therapy was higher for of a DDI was investigated. In a cohort of elderly outpatients attending the Groningen SSRI users than for TCA users (overall incidence RR 1.6; CI95 1.3-2.0). This could be due to the Outpatient Thrombosis Service, we studied the effects of the interaction between three NSAIDs fact that the less sedative effects of SSRIs may contribute to the increased frequency of benzo- (diclofenac, naproxen and ibuprofen) and the oral anticoagulant acenocoumarol on prothrom- diazepine prescribing. In the nursing home cohort, no difference in frequency of benzodiazepi- bin time, expressed as the International Normalised Ratio (INR). Genotyping of cytochrome ne co-prescribing was found between SSRI users compared with TCA users. Partly this may be P450 2C9 was performed to determine whether genotype was a predictive variable for the 162 due to the fact that hypnotic drug use in this population was already high, as was shown in sec- occurrence of an increased INR as a result of this DDI. The study population consisted of 112 163 tion 2.3. The prevalence of concomitant prescribing was considerable: in both ambulatory and patients stable on acenocoumarol therapy, of whom 52 (46%) showed an elevation of the INR institutionalised elderly more than 50% of TCA and SSRI users were prescribed a benzodiaze- above the desired therapeutic level (average INR increase between 1 and 4 units). In 12 pine drug concomitantly. On average, concomitant drug use lasted for greater than 67 days per patients, the INR increased above 6, indicating a clinically relevant risk of severe haemorrha- 100 days of antidepressant drug use. The combined use of TCAs and benzodiazepines seems of ge. No association between CYP2C9 genotype and an increased INR as a result of the DDI was concern in view of the cumulation of adverse effects such as excess sedation and an increased found, and no other predictive variables were identified. We recommend close monitoring of risk of falls. In section 2.7, we studied a potential beneficially combination of drugs: the conco- the INR of all patients receiving NSAIDs and acenocoumarol as at present we cannot predict mitant use of NSAIDs and gastroprotective drugs in a cohort of elderly outpatients. Use of who will and who will not be affected by this DDI. NSAIDs is associated with an increased risk of gastrointestinal toxicity, in particular when risk factors such as advanced age are present. We studied the prevalence of concomitant prescri- In chapter 4 the results of the studies described in the thesis are placed in a broader per- bing, as well as the prophylactic prescribing of gastroprotective drugs among ambulatory spective and suggestions for clinical practice and further study are given. For example, hospi- NSAID users aged 65 years and over. Co-prescribing of gastroprotective drugs occurred in 23% tal pharmacists can play a leading role in the monitoring of drug-related problems in the frail of the NSAID users (n=6,557), with an average duration of 67 days per 100 days of NSAID use. elderly both on an individual and a population based level. Concomitant use of oral corticosteroids, coumarins and low dose aspirin were significantly associated with both prophylactic and concomitant prescribing of gastroprotective agents during NSAID therapy. We recommend giving feedback to prescribers to improve prescribing practices in this high risk group.

In chapter 3, outcomes of drug use are studied in nursing home patients and elderly outpatients. Section 3.1 presents a study among nursing home residents, in which the association between drug use and constipation was investigated. We performed a prospective cohort study of 2,355 nursing home patients to estimate the incidence relative risk of constipation associated with drug use using prescription sequence analysis of each resident’s detailed pharmacy records and data on morbidity and mobility. Use of drugs that according to the summaries of product characteristics and the literature on adverse effects have moderately to strongly constipating properties was associated with a relative risk of 1.6 (CI95 1.2-2.0) for the occurrence of constipation during exposure. Use of drugs with mildly to moderately constipating effects was not associated with an increased frequency of laxative use. Although an association between Samenvatting aandoeningen. De medische zorg wordt geleverd door speciaal hiervoor opgeleide verpleeg- huisartsen. De geneesmiddelendistributie en farmaceutische zorg worden geleverd door open- Dit proefschrift beschrijft het gebruik van geneesmiddelen bij ouderen, in het bijzonder bare apothekers of ziekenhuisapothekers. verpleeghuisbewoners. Vanwege hun leeftijd zijn ouderen gevoeliger voor de effecten en bijwerkingen van geneesmiddelen. Verpleeghuisbewoners lijden vaak gelijktijdig aan verschil- Het gebruik van geneesmiddelen bij ouderen lende aandoeningen met als gevolg het gelijktijdig gebruik van verschillende geneesmiddelen (polyfarmacie). Er is weinig bekend over het gebruik van geneesmiddelen en het optreden van Hoofdstuk 2 gaat nader in op het geneesmiddelgebruik bij ouderen. Het eerste deel 164 problemen als gevolg van geneesmiddelgebruik bij deze kwetsbare groep ouderen. De onder- beschrijft het geneesmiddelgebruik bij verpleeghuisbewoners. In paragraaf 2.1 wordt een lite- 165 zoeken die in dit proefschrift zijn beschreven beogen de kennis over het geneesmiddelgebruik ratuuroverzicht gegeven van de studies die het geneesmiddelgebruik bij verpleeghuisbewo- en geneesmiddelgerelateerde problemen bij ouderen te vergroten. ners beschrijven. Deze studies zijn voornamelijk in de Verenigde Staten uitgevoerd. Aangezien Amerikaanse ‘nursing homes’ nogal verschillen van de Nederlandse verpleeghuizen, zijn de Inleiding resultaten van deze studies niet zonder meer van toepassing op de Nederlandse situatie. In Nederland is slechts weinig onderzoek uitgevoerd waarin het geneesmiddelgebruik op indivi- In het eerste hoofdstuk worden de achtergrond en de doelstelling van het proefschrift dueel patiëntniveau wordt beschreven. Dit komt mede doordat het geneesmiddelgebruik pas beschreven. Oudere patiënten lopen meer risico op het krijgen van geneesmiddelgerelateerde sinds een aantal jaren wordt vastgelegd in geautomatiseerde gegevensbestanden. Vóór de problemen. Voorbeelden zijn interacties tussen geneesmiddelen, waardoor de werking van een jaren negentig werden de geneesmiddelgegevens vaak alleen in de medische status opge- geneesmiddel verzwakt of juist versterkt wordt. Ook treden bijwerkingen van geneesmiddelen schreven, hetgeen het uitvoeren van farmacoepidemiologisch onderzoek, dat gegevens van vaker op bij ouderen, bijvoorbeeld maagklachten als gevolg van bepaalde pijnstillers vele patiënten nodig heeft, bemoeilijkt. Paragraaf 2.2 beschrijft hoe de geneesmiddelgegevens (NSAID’s). Ook het ten onrechte niet aan oudere patiënten voorschrijven van geneesmiddelen, van alle verpleeghuisbewoners van zes verpleeghuizen zijn verzameld in één databestand. De bijvoorbeeld wanneer een bepaalde aandoening (zoals een depressie) niet wordt herkend, kan gegevens betroffen de periode 1-10-1993 tot 1-10-1995. Dit databestand is gekoppeld aan een voorkomen. Men spreekt dan van onderbehandeling. Om deze redenen is het van belang dat de landelijk verpleeghuis-databestand (SIVIS), waarmee gegevens over de diagnosen, de aard voorschrijvend arts een goed beeld heeft van de effecten en bijwerkingen van geneesmiddelen van de verpleging (somatisch of psychogeriatrisch) en de mobiliteit van de verpleeghuispa- bij ouderen, met name de kwetsbare ouderen die in verpleeghuizen verblijven. Door middel tiënten werden verkregen. De uiteindelijke studiepopulatie omvatte 2355 verpleeghuisbewo- van farmacoepidemiologisch onderzoek kan men inzicht krijgen in het gebruik van geneesmid- ners. In deze paragraaf worden aanbevelingen gedaan voor het uitvoeren van farmacoepide- delen en de factoren die van invloed zijn op dit gebruik, in bepaalde populaties in de dagelijk- miologisch onderzoek met behulp van apotheekgegevens. Van belang is dat alleen geanonimi- se praktijk. Ons onderzoek geeft inzicht in het geneesmiddelgebruik, de factoren die dit gebruik seerde gegevens verzameld worden, dat de gegevens een redelijke tijdsperiode (minimaal 2 bepalen (‘determinanten’) en de uitkomsten van geneesmiddelgebruik bij ouderen, in het bij- jaar) beslaan, en dat de gegevens zo volledig mogelijk zijn (bijvoorbeeld een juiste registratie zonder verpleeghuisbewoners. Paragraaf 1.2 beschrijft de zorg voor thuiswonende ouderen en van opname- en ontslagdata van verpleeghuisbewoners). Met het databestand is een genees- voor ouderen die wonen in verzorgings- en verpleeghuizen. Het verpleeghuis in Nederland middelgebruiksstudie uitgevoerd (paragraaf 2.3). Het geneesmiddelgebruik bij de verpleeg- biedt verzorging en verpleging aan personen die chronisch ziek zijn en continue medische en huispatiënten bleek hoog te zijn. Gemiddeld gebruikte iedere bewoner 4,9 verschillende paramedische zorg nodig hebben. Het type zorg dat in Nederlandse verpleeghuizen wordt gele- geneesmiddelen per dag. Geneesmiddelen die werken op het centrale zenuwstelsel (zoals mid- verd wordt gekenmerkt als continu, op de lange termijn gericht, systematisch en multidiscipli- delen tegen psychosen, slaap- en kalmeringsmiddelen), laxeermiddelen, pijnstillende midde- nair. Er is een onderscheid tussen de zorg voor somatische verpleeghuisbewoners, die lijden len en middelen ter voorkoming van bloedstolling werden het meest frequent gebruikt. Veel aan ernstige lichamelijke aandoeningen (zoals de ziekte van Parkinson) en de zorg voor psy- geneesmiddelen werden langdurig gebruikt, met name psychofarmaca, diuretica en laxantia: chogeriatrische verpleeghuisbewoners, die lijden aan dementie en andere psychogeriatrische deze werden gedurende meer dan driekwart van de verblijfsduur in het verpleeghuis gebruikt. De doseringen die werden voorgeschreven waren relatief laag, met uitzondering van diuretica namelijk die tussen NSAID’s en maagbeschermende geneesmiddelen. NSAID’s zijn bekend en laxantia. In paragraaf 2.4 gaan we in op het gelijktijdig voorschrijven van geneesmiddelen vanwege maagdarmklachten, zoals maagdarmzweren en maagdarmbloedingen. Met name waarvan gelijktijdig gebruik juist wordt afgeraden, hetgeen tot een klinisch relevante bijwer- ouderen zijn hier gevoelig voor. De aanbeveling is dat mensen ouder dan 65 jaar die een NSAID king kan leiden. We hebben de frequentie, de aard en de duur van een aantal potentieel nodig hebben, tevens een geneesmiddel moeten gebruiken dat de maag beschermt. We onder- schadelijke geneesmiddelcombinaties in hetzelfde cohort verpleeghuispatiënten onderzocht. zochten of dit ook gebeurt in de dagelijkse praktijk. Dit was slechts het geval bij 23% van de Hier bleek dat 32% van de populatie tenminste één ongewenste geneesmiddelcombinatie NSAID gebruikers boven de 65 jaar. Verder onderzoek is nodig om te achterhalen waarom 77% kreeg voorgeschreven gedurende de studieperiode van 2 jaar. De interactie tussen lisdiuretica van de oudere NSAID gebruikers niet tegelijkertijd een maagbeschermer kreeg voorgeschreven 166 en NSAID’s en de interactie tussen orale anticoagulantia (bloedverdunnende middelen) en en of er bij die patiënten inderdaad klinisch relevante maagdarmklachten optreden. 167 NSAID’s kwamen in deze populatie het meest frequent voor. Ook bleek dat per interactie niet meer dan 10% van de bewoners waren blootgesteld. Paragraaf 2.5 beschrijft een pilot onder- Bijwerkingen van geneesmiddelen in de praktijk zoek waarin het geneesmiddelgebruik in twee verpleeghuizen is geëvalueerd door middel van het toepassen van voorschrijfindicatoren (‘prescribing indicators’). In dit onderzoek wordt de Hoofdstuk 3 richt zich op de uitkomsten van geneesmiddelgebruik bij ouderen. Paragraaf 3.1 mate waarin het voorschrijven van geneesmiddelen afwijkt van bepaalde richtlijnen in ver- beschrijft een onderzoek naar de relatie tussen het laxantiagebruik in verpleeghuizen en het pleeghuizen, zoals een geneesmiddelformularium, bestudeerd. Hier bleek dat het voorschrijf- gebruik van obstiperende medicatie. In dit onderzoek werd een epidemiologische techniek, gedrag weinig afweek van de richtlijnen. Als er werd afgeweken, bijvoorbeeld bij een te hoge prescriptie-sequentie-analyse, toegepast. Dit houdt in dat we bestudeerden of laxeermiddelen dosering, bestond daar een goede reden voor en werden eventuele bijwerkingen in de gaten vaker werden voorgeschreven aan gebruikers van obstiperende geneesmiddelen om de bij- gehouden. De voorschrijfindicatoren bleken goed bruikbaar om het voorschrijfgedrag in kaart werkingen van deze geneesmiddelen (obstipatie) tegen te gaan. Verpleeghuisbewoners die te brengen. Om vanuit voorschrijfgegevens suboptimaal voorschrijven te kunnen detecteren, geneesmiddelen met een matig tot sterk obstiperende werking gebruikten, hadden 60% meer was vaak klinische informatie over de patiënt nodig. Het tweede deel bestaat uit 2 onderzoe- risico om een laxans te gebruiken dan verpleeghuisbewoners die deze geneesmiddelen niet ken die zijn uitgevoerd door middel van analyse van voorschrijfgegevens van ambulante oude- gebruikten. Dit risico was minder hoog dan in de literatuur is gemeld. In paragraaf 3.2 onder- ren. Hiervoor werd gebruik gemaakt van de InterActie-databank, een databestand waarin de zochten we de klinische relevantie van een geneesmiddelinteractie, namelijk die tussen geneesmiddelgegevens van circa 135.000 mensen in de regio Noordoost Nederland geanoni- NSAID’s en acenocoumarol (een bloedverdunnend middel). Beide middelen worden frequent miseerd worden vastgelegd. Paragraaf 2.6 beschrijft het gebruik van benzodiazepinen (slaap- door ouderen gebruikt. De studiepopulatie bestond uit 112 patiënten die geselecteerd waren via en kalmeringsmiddelen) bij ouderen boven de 65 jaar en verpleeghuisbewoners die antide- de Stichting Trombosedienst Groningen. Bij 46% bleek de INR (International Normalised pressiva gebruikten. Het bleek dat de ambulante ouderen die nieuwere antidepressiva gebruik- Ratio, een maat voor de stolling van het bloed) verhoogd te zijn wanneer deze patiënten ten (selectieve serotonine heropname remmers (SSRI’s)), een grotere kans hadden om met een behandeld waren met een NSAID. Dit betekent een verhoogde kans op bloedingen. Het ver- benzodiazepine te starten dan personen die klassieke antidepressiva (tricyclische antidepres- moeden bestond dat een bepaalde erfelijke eigenschap, namelijk een mutatie op het enzym- siva (TCA’s)) gebruikten. Mogelijk komt dit doordat TCA’s een groter kalmerend effect hebben, systeem cytochroom P450 2C9 (CYP2C9), verantwoordelijk zou kunnen zijn voor de verhoogde waar met name ouderen gevoelig voor zijn. Bij de verpleeghuispatiënten kon een dergelijk INR als gevolg van de geneesmiddelinteractie. Daarom is bij 80 patiënten het genotype van verhoogde kans niet worden aangetoond, wellicht doordat deze mensen al veel benzodiazepi- CYP2C9 bepaald. Er bleek geen relatie aantoonbaar te zijn tussen de verhoogde INR (als gevolg nen gebruikten. Opvallend was dat het gecombineerd gebruik van antidepressiva en benzodia- van de geneesmiddelinteractie) en het CYP2C9 genotype. Dit betekent dat op dit moment (nog) zepinen groot was: meer dan 50% van de TCA en SSRI gebruikers kreeg tevens een benzodia- niet voorspeld kan worden bij wie de INR stijgt door deze geneesmiddelinteractie en bij wie zepine voorgeschreven. Het gelijktijdig gebruik bleek ook langdurig te zijn. Vervolgonderzoek niet. Deze studie laat zien dat het nuttig is om klinische gegevens (zoals de INR) en voor- zou inzicht moeten geven in de redenen waarom deze middelen zo lang gelijktijdig voorge- schrijfgegevens te gebruiken om mogelijk bijwerkingen van geneesmiddelen te kunnen detec- schreven worden. In paragraaf 2.7 onderzochten we een wenselijke geneesmiddelcombinatie, teren. Daarnaast is duidelijk dat het lastig is om te voorspellen bij wie de interactie zal optreden en bij wie niet. Betekenis voor de praktijk Dankwoord

In hoofdstuk 4 worden de resultaten van de onderzoeken in dit proefschrift in breder per- Dat dit proefschrift er ligt is voor het overgrote deel te danken aan de inspirerende, motiveren- spectief geplaatst en worden suggesties voor de praktijk en voor verder onderzoek gegeven. de en ondersteunende bijdragen van velen. Bijwerkingen van geneesmiddelen kunnen bij deze kwetsbare ouderen grote gevolgen op de Allereerst mijn beide promotores: Lolkje de Jong-van den Berg en Koos Brouwers. kwaliteit van leven hebben, zoals de kans op verminderd geheugen door benzodiazepinen, de Lolkje, dankzij jouw enthousiasme, steun en vertrouwen in dit onderzoek is dit proefschrift nu kans op een delier (acute verwardheid) door bepaalde (anticholinerge) medicatie, en de kans geworden wat het is. Ik ben ontzettend blij dat ik met je heb mogen samenwerken. Altijd wist 168 op vallen door psychofarmaca. Daarom dienen de voordelen van het gebruik van geneesmid- je me weer te overtuigen van de relevantie van het onderzoek. Ik heb veel geleerd van de 169 delen altijd afgewogen te worden tegen de mogelijke bijwerkingen, met name bij ouderen. Om manier waarop jij onderzoek doet en steeds het wetenschappelijk aspect van elke studie bena- te bepalen welke patiënten het hoogste risico lopen op geneesmiddelgerelateerde problemen, drukt. Daarbij was het natuurlijk ook erg gezellig! Dank je voor de tijd die je altijd voor me had. is onderzoek zoals in dit proefschrift beschreven nodig. Naast voorschrijfgegevens zijn ook kli- Koos, met jou begon dit onderzoek toen je me in 1994 de mogelijkheid gaf om het laxantia- nische gegevens (zoals laboratoriumuitslagen en gegevens over de diagnosen van een patiënt) gebruik bij verpleeghuisbewoners nader te onderzoeken. Jij was de ‘linking-pin’ met de uni- nodig om inzicht te krijgen in de relevantie van geneesmiddelgerelateerde problemen. Een versiteit en degene die me enthousiast maakte voor het onderzoek. Ik waardeer jouw klinisch- voorbeeld is de interactie tussen NSAID’s en anticoagulantia: we weten dat deze interactie rela- farmacologische blik altijd zeer. Dank je voor je vertrouwen en je grote bijdrage aan dit onder- tief veel voorkomt en mogelijk tot problemen kan leiden. Op dit moment weten we nog niet hoe zoek. we de personen die het meeste risico lopen op een klinische relevant effect, van te voren kun- Zonder mijn referent, Corinne de Vries, had dit proefschrift zeker nog wat langer op zich nen herkennen. Door het combineren van individuele medicatiegegevens en klinische data kan moeten laten wachten. Corinne, vanaf het eerste artikel tot en met de discussie: je was altijd op patiëntniveau het optreden van geneesmiddelgerelateerde problemen bewaakt worden. ontzettend betrokken bij dit onderzoek. Kortom, de ‘ideale referent’! Je vertrek naar Engeland Tevens kan door het combineren van deze gegevens op grote schaal farmaco-epidemiologisch veranderde hier gelukkig niets aan: via de mail heb je talloze versies van artikelen gecorrigeerd onderzoek worden uitgevoerd waarbij de nadruk ligt op het bestuderen van uitkomsten van en aangevuld. Jouw epidemiologische inbreng heeft mede voor de publicaties gezorgd. Dank je geneesmiddelgebruik (zoals een ziekenhuisopname als gevolg van een bijwerking van een voor zoveel input!! geneesmiddel). Hierbij kunnen verschillende disciplines, zoals ziekenhuisapothekers, ver- De leden van de leescommissie, prof. dr. A.C.G. Egberts, prof. dr. F.M. Haaijer-Ruskamp en pleeghuisartsen en klinisch chemici een belangrijke rol spelen. De rol van de ziekenhuisapo- prof. dr. J.P.J. Slaets, dank ik voor hun snelle beoordeling van het manuscript en de waardevol- theker kan zowel initiërend als faciliterend zijn, zowel op het gebied van de verzameling van le opmerkingen. voorschrijfgegevens als op het gebied van het in samenwerking met universitaire centra uit- Paul van den Berg, mede-auteur van bijna alle hoofdstukken van dit boekje, was het brein voeren van farmacoepidemiologisch onderzoek. achter alle analyses. Paul, van jouw expertise op het gebied van databestanden heb ik dank- baar gebruik gemaakt. Je wist tot ver in het SQL-tijdperk nog met mijn dBase-bestanden om te gaan, gelukkig zonder al te veel morren. Dank je voor je geduld en je kritische opmerkingen. Dick Bloemhof en Jan Sijtsma: ik ben jullie zeer erkentelijk voor de hulp met het verzame- len van de voorschrijfgegevens uit de verpleeghuizen. Margriet Piersma-Wichers, mede dankzij jouw enthousiasme is paragraaf 3.2 in dit proefschrift verschenen. Ik vond het erg leuk dat je betrokken was bij dit onderzoek. Lisa Pont: gelukkig kwam er toch nog een artikel over de ‘prescribing indicators’. Dank voor je inbreng hierbij en natuurlijk ook voor de Engelse correcties in enkele stukken. Dan waren er nog vele SFF-ers die mijn pad hebben gekruist tijdens mijn wekelijkse dag- En dan als laatste, de onmisbare basis die gevormd wordt door familie en vrienden. Lieve mam jes op de universiteit. Roel, het was leuk om met jou en Taco de farepi-cursus in Boston te vol- en pap: jullie dank ik voor jullie niet aflatende steun en vertrouwen. Paula, Wiebe en Veerle: gen. Taco, dank voor je hulp bij de voor mij soms ingewikkelde logistische regressie analyses. Haarlem was (en is) altijd een prima afleiding! Petra en Karen: ik ben heel blij dat jullie mijn Hilde, bij jou kon ik altijd terecht met een statistisch vraagje. Op de valreep heb ik nog veel van paranimfen willen zijn. Lieve Peter, dank, heel veel dank voor al je liefde en support en voor je geleerd tijdens je statistiek cursus. Ada, Bert, Claudia, Eric, Evelyn, Jackie, Janet, Jasper, zoveel meer dat eigenlijk niet in dit boekje thuishoort. Jeroen, Jos, Jos, Maarten, Marijke, Sipke, Willemijn, René, Rogier: dank voor jullie meeleven tijdens de vorderingen van dit onderzoek. De SFF-borrels, lunches en de jaarlijkse bbq waren 170 altijd erg leuk (dit geldt ook voor de ex-SFF-ers)! De leden van de dRUGs-werkgroep dank ik 171 voor hun interesse en feedback. Een aantal enthousiaste bijvakstudenten heeft mij geholpen bij de onderzoeken die zijn beschreven in dit boekje. Anne-Margreeth Dijkema, jij was de eerste ‘bijvakker’ en jij hebt zeker je bijdrage geleverd aan paragraaf 3.1. Maria Franken, jij hebt een belangrijk onderdeel van paragraaf 2.5 uitgevoerd. Het was plezierig met je samen te werken. Arian Plat: jij was de (snelle) motor achter het onderzoek bij de coumarine-gebruikers. Dankzij jouw inzet bij de recrute- ring van de patiënten was het mogelijk om het onderzoek naar het polymorfisme van CYP2C9 uit te voeren. Veel succes met jouw promotieonderzoek! Alieke van Dijk was er vervolgens om de genotypering van 80 patiënten uit te voeren. Alieke, dank je voor je nauwgezette werk! Aukje Stenekes bepaalde de R- en S-acenocoumarolspiegels (helaas kon dat niet meer in het boekje). Dank voor je hulp bij het transport van de bloedmonsters. Dan waren er natuurlijk de collega-ziekenhuisapothekers, die zorgden voor een goede basis op het werk. Toen ik in 1997 in de apotheek van het Wilhemina Ziekenhuis Assen voor 0.8 begon, wist ik nog niet hoeveel tijd die andere 0.2 me zou kosten. Uiteindelijk was het de moei- te waard en dat kan denk ik alleen als de basis goed is. Jaap: je was altijd geïnteresseerd in het onderzoek. Daarbij kwam het goed uit dat ik als aandachtsgebied de verpleeghuizen had. Dank je voor de mogelijkheid om de zomercursus Epidemiologie in Boston te kunnen volgen en voor je hulp bij de medisch-ethische toetsing van het coumarine onderzoek. Wobbe, Lous en Hans: ook jullie dank ik voor de interesse die jullie altijd hadden in mijn onderzoek. Hans: veel succes met jouw onderzoek. Alle andere apotheekmedewerkers: ik kijk met veel plezier terug op mijn WZA-tijd! Sinds een paar maanden weer terug in het Friese: mijn kersverse collega’s van de apotheek Zorggroep Noorderbreedte hebben alleen het staartje van het onderzoek meege- maakt. Het was een drukke tijd, met veel printjes en ritjes naar Groningen. Bob, dank je voor het meedenken met het coumarine onderzoek. Eric, Folgert, Jan Peter, Nicole, Rients, Romke: dank voor jullie flexibiliteit. Dit geldt natuurlijk ook voor alle andere apotheek ZNB-medewer- kers. Publications Curriculum vitae

Publications related to the thesis Karen van Dijk werd op 23 oktober 1966 geboren in Den Haag. Aan het Rhedens Lyceum te Van Dijk KN, De Vries CS, Brouwers JRBJ, De Jong-van den Berg LTW. Farmaco-epidemiolo- Rozendaal behaalde zij in 1985 haar VWO diploma. Aansluitend begon zij met de studie gisch onderzoek in verpleeghuizen: een prospectief vervolgonderzoek naar de associatie tus- Farmacie aan de Rijksuniversiteit Groningen. Het doctoraalexamen werd in 1991 gehaald, sen medicatie en obstipatie. Ziekenhuisfarmacie 1996; 4: 242-4. waarna zij een maand Frans studeerde in Besançon. Het apothekersexamen werd in 1992 Van Dijk KN, De Vries CS, Van den Berg PB, Dijkema AM, Brouwers JRBJ, De Jong- van den behaald. Na een korte tijd werkzaam geweest te zijn in de openbare farmacie in Den Haag 172 Berg LTW. Constipation as an adverse effect of drug use in nursing home patients: an overesti- (Waldeck Apotheek), werd in 1993 gestart met de opleiding tot ziekenhuisapotheker in 173 mated risk. Br J Clin Pharmacol 1998; 46: 255-61. Heerenveen en daarna Leeuwarden (opleiders: prof.dr. J.R.B.J. Brouwers en drs. R.J. Boskma). Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Drug Het registratieonderzoek leidde tot een promotieonderzoek aan de Rijksuniversiteit utilisation in Dutch nursing homes. Eur J Clin Pharmacol 2000; 55: 765-71. Groningen, vakgroep Sociale Farmacie, Farmacoepidemiologie en Farmacotherapie (prof.dr. Van Dijk KN, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. L.T.W. de Jong-van den Berg, prof. dr. J.R.B.J. Brouwers en dr. C.S. de Vries), dat in de periode Occurrence of potential drug-drug interactions in nursing home patients. Int J Pharm Pract 1995-2001 werd uitgevoerd. Van april 1997 tot oktober 2001 was zij als ziekenhuisapotheker 2001; 9:45-52. werkzaam in het Wilhelmina Ziekenhuis te Assen. In 1999 volgde zij de zomercursus Van Dijk KN, Ter Huurne K, De Vries CS, Van den Berg PB, Brouwers JRBJ, De Jong-van den Epidemiologie aan het Epidemiology Research Institute te Boston. Sinds november 2001 werkt Berg LTW. Prescribing of gastroprotective drugs among elderly NSAID users in the Netherlands. zij in het Medisch Centrum Leeuwarden. Pharm World Sci (in press). Van Dijk KN, De Vries CS, Ter Huurne K, Van den Berg PB, Brouwers JRBJ, De Jong-van den Berg LTW. Concomitant prescribing of benzodiazepines during antidepressant therapy in the elderly. J Clin Epidemiol (in press). Van Dijk KN, Pont LG, De Vries CS, Franken M, Brouwers JRBJ, De Jong-van den Berg LTW. Prescribing indicators as a tool to evaluate drug use in nursing homes: a pilot study. Submitted. Van Dijk KN, Plat AW, Van Dijk AAC, Piersma-Wichers G, De Vries-Bots AMB, Slomp J, De Jong-van den Berg LTW, Brouwers JRBJ. Potential interaction between acenocoumarol and diclofenac, naproxen and ibuprofen and the role of CYP2C9 genotype. Submitted.

Other publications Bloemhof H, Van Dijk KN, De Graaf SSN, Vendrig DEMM, Uges DRA. Sensitive method for the determination of vincristine in human serum by high-performance liquid chromatography after on-line column extraction. J Chromatogr 1991; 572: 171-9, Biomedical Applications. Van Dijk KN, Van der Meer YG. Medicamenteuze behandeling van diabetische neuropathie. Pharm Weekbl 1992; 127: 1081-2. Van Dijk KN. Miltefosine: lokaal cytostaticum. Ziekenhuisfarmacie 1996; 12: 106. Lentelink MB, De Vries TW, Van Dijk KN. Accidental metronidazol overdose in a preterm newborn [letter]. Clin Pharmacokin 1997; 32: 496-7.