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Drug Interactions in the Elderly

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Drug Interactions in the Elderly Drug Interactions in the Elderly James F. Kurfees, MD, and Rachel L. Dotson Louisville, Kentucky Polypharmacy and its dangers in the elderly are of increasing concern. The pur­ pose of this study was to determine the incidence of drug with drug, drug with food, and drug with alcohol interactions in a population aged 60 years or greater. Four hundred patients were randomly selected from a university family medicine outpatient clinic population of 4,483 in this age group. A total of 292 drugs were involved for a total of 1,052 potential interactions: 310 drug-food, 316 drug-alco­ hol, and 426 drug-drug. Interactions were analyzed using The Drug Master com­ puter program and rated as to their clinical significance. Chart review revealed no serious actual interaction for any patient even though potential interactions could be categorized as highly significant for 27 percent of the drug-drug, 11 percent of the drug-alcohol, and 3 percent of the drug-food. Thirty-two percent of the to­ tal population were taking five or more drugs concurrently. The mean number of drugs for men was 3.75 and for women 4.22 (P < .05). Age and race differences were also noted in the number of drugs taken. The most common drugs and their interactions with drug, food, and alcohol are reviewed. ecause of ongoing concern about the practice of drug-drug interaction was reported in 17 percent of the B polypharmacy, especially in the elderly, a university surgical patients studied by Durrence et al.3 After studying family practice outpatient population was studied for any all hospital patients at a private community hospital, potential or actual drug-drug interactions by analyzing Greenlaw and Zellers4 reported potential drug interactions the frequency, severity, and character of these interactions. in about 9 percent of the patients per day. Chronic care As drug-food and drug-alcohol interactions frequently facilities and nursing homes report drug interaction rates occur, these were also investigated. The objectives of this of 23 to 53 percent and drug utilization of 4.85 to 8.33 study were (1) to estimate the rates for drug-drug, drug- drugs per patient.5-12 Studies report a 6 percent frequency food, and drug-alcohol interactions in a family practice of drug interaction in an ambulatory population with an clinic population aged 60 years or older; (2) to compare average of 9.2 prescriptions per year per patient.5-12 Brown the incidence of polypharmacy and interactions for cohort et al13 observed that the incidence of adverse reaction is groups by age, sex, and race; and (3) to provide a discussion increased when prescriptions are written on an as-needed and descriptive summary of the most common drug in­ basis. Lamy,14 referring to Robinson’s article,15 indicates teractions with other drugs, foods, and alcohol. that most adverse drug interactions are predictable and For the past 25 years there has been a dramatic rise in avoidable. Lamy further states that the drugs that are most the use of prescription drugs, from 2.4 to 7.5 prescriptions common offenders are the most commonly prescribed per person annually. Among elderly patients the use is drugs, not the rarely used drugs. much higher—as many as 13 prescriptions a year.1 May et al16 reported that patients on five or fewer drugs Mitchell et al2 reported a potential drug-drug interaction have a 4 percent adverse response rate, whereas for pa­ incidence rate of 32.5 percent for patients on more than tients on 16 to 20 drugs, the rate escalates to 54 percent. single-drug therapy. They also reported an even higher It can be expected, according to calculations by May and rate of 47 percent potential interaction for the monitored colleagues, that patients taking six to 10 drugs would have ambulatory population studied. At least one potential an adverse reaction rate of 10 percent. While,the literature addresses the dangers of multiple drug interactions, there is a paucity of information about Submitted, revised, June 5, 1987. these interactions when multiple drugs are admixed. From the Department of Family Practice, University of Louisville, School of Med­ Nearly all tables and computer designs reference only one icine, Louisville, Kentucky. Requests for reprints should be addressed to Dr. drug with one other. No study reports the interaction of James E. Kurfees, Department of Family Practice, University of Louisville, Louis­ ville, KY 40292. host factors and multiple drugs. It is rare to find references © 1987 Appleton & Lange THE JOURNAL OF FAMILY PRACTICE, VOL. 25, NO. 5: 477-488, 1987 477 DRUG INTERACTIONS IN THE ELDERLY was counted as one medication. These compound prep­ TABLE 1. NUMBER AND PERCENTAGE OF PATIENTS BY arations, however, were analyzed for adverse reactions by CATEGORY OF CONCURRENT DRUGS USED the computer according to their component drugs. Number of Drugs Screening was done by a computer program entitled, Taken Concurrently Number of Patients Percent The Drug Master by Thomas Shreve.18 This program was used on an ITT XP microcomputer equipped with a 20- 2 103 26 3 96 24 megabyte hard disk. Fifteen hundred drugs make up the 4 73 18 database of this program, which offers the possibility of 5 53 13 entering for interaction analysis up to 15 drugs at one 6 29 7 time. The program automatically performs an interaction 7 or more 46 12 analysis not only between the drugs entered but also be­ Total 400 100 tween those drugs and food and alcohol. A drug list for each of the 400 patients was entered into the computer. A rating of low, moderate, or high clinical significance was assigned to each interaction, and a computer hard­ to the often important drug-food and drug-alcohol in­ copy printout giving the potential drug-drug, drug-food, teractions. Indeed, as one author observed, patients are and drug-alcohol interactions was obtained. Potential in­ becoming “living chemistry sets.”17 teractions were also cross-referenced with the 1986 Phy­ sicians ’ Desk Reference,19 the Physicians ’ Desk Reference for Nonprescription Drugs,20 The Medical Letter,21 Facts METHODS and Comparisons,22 Goodman and Gilman’s The Phar­ macological Basis of Therapeutics, ed 7,23 and current A study was undertaken in which patient charts from a literature as noted in the references. Student’s t test was university family practice outpatient clinic were reviewed used for statistical analysis of data and alpha levels (P) for drug interactions. Approved by the university Human were set at .05. Studies Committee, the chart review took approximately 12 weeks and covered visits made during the previous year. The contents of the medical records were searched RESULTS for the types of medications and any reported adverse drug effects. These charts were pulled from a total patient Of the 400 patients selected for this study, about two thirds population of 33,733, which included 5,281 patients aged were female and one third were male. About 87 percent 60 years and over. Of these 5,281 records, only 4,483 of the group were aged 65 years or older with an age range were accessible in the principal clinic studied. Those cho­ from 60 to 100 years. Racial distribution reflected that of sen for the survey were required to satisfy two criteria: (1) the general clinic population, with 41 percent black and the patient had to be 60 years of age or older, and (2) the 44 percent white. The race of the remaining 14 percent patient had to be taking two or more medications con­ could not be determined from the charts. currently as documented in chart notes. The charts were Comparisons between patient groups using Student’s t pulled at random, and the first 400 patient charts that tests revealed significant differences at the .05 level be­ met these criteria were selected for the study. The charts tween men and women on the mean number of drugs were arranged into categories according to the number of taken (3.75 and 4.22, respectively). Number of drugs taken medications being taken to form cohorts of two, three, also differed between (1) patients aged 75 years and over four, five, six, and seven or more concurrent drugs used and those who were younger than 75 years (4.3 and 3.8, per patient. respectively) and (2) white patients and black patients, Data collected from the charts included the patients’ with white patients taking significantly more drugs. age, sex, race, number of medications, and the names of This sample of patients was using 292 different drugs the medications. All medications listed in the charts, in­ at the time of data collection. The number of drugs per cluding vitamins, potassium, calcium, aspirin, and any patient ranged from 2 to 16 with the average number per over-the-counter medications were counted along with patient being 4.1. The cohort groups are described in Table all prescription items in the survey. 1 by number of drugs taken concurrently. In this sample, For the purpose of counting the number of medications 32 percent were taking five or more drugs concurrently. each patient was taking, each medication listed was Even though all patients were taking at least two or counted as one, even if it contained a combination of two more drugs, 96 (24 percent) were not at risk for drug in­ or more chemical compounds. For example, Dyazide, teraction with food, alcohol, or other drugs. In Table 2, though composed of triamterene and hydrochlorothiazide, the sample is described by the type of potential of inter- 478 THE JOURNAL OF FAMILY PRACTICE, VOL. 25, NO.
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