The Reformation of the Danish Acute Care System – from the Many Small Hospitals to Few Big Emergency De- Partments

The reformation of the Danish acute care system – from the many small hospitals to few big emergency departments

Description of a PhD Project

PhD student Marianne Fløjstrup MD Department of Emergency Medicine, Sydvestjysk Sygehus, Esbjerg, Denmark Email: [email protected]

Main Supervisor Mikkel Brabrand MD, PhD Research director, Department of Emergency Medicine, Sydvestjysk Sygehus, Esbjerg, Denmark, Consultant, Department of Emergency Medicine, Odense University Hospital Clinical Associate Professor, University of Southern Denmark, Insti- tute of Regional Health Research. Email: [email protected]

Co Supervisors Daniel Henriksen MD, PhD Department of Respiratory Medicine, Odense University Hospital, Denmark Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Denmark Email: [email protected]

Søren Bie Bogh MSc, PhD Counseling and researcher at Centre for Quality, Region of Southern Denmark Email: [email protected]

Mickael Bech Msc, PhD CEO of VIVE – The Danish Centre of Applied Social Science and professor in health economics. Email: [email protected]

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Background Reorganisation of the Danish Health system The Danish healthcare system has been through big organisational changes during the last decade.

In 2004, the Danish government decided to reorganize the entire healthcare system (1) and in 2006, the Danish National Board of Health published a report on how to implement the changes in order to improve the quality of acute care in Denmark (2). The proposed changes were recommended by a panel of experts from different medical and professional corpora- tions, police, politicians, prehospital leaders and ambulance services. The recommendations were primarily based on a combination of medical, administrative and expert assessments rather than scientific literature (3).

The changes were not made without protests. In 2005 the reorganisation was criticised, as a report from The Danish Institute for Health Services Research concluded that centralization would not per se lead to improved healthcare for the acute patient (4).

As part of the reorganisation, acute hospital care was centralised to fewer but larger hospitals. Prior to the changes 44 hospitals had status of acute hospitals (5). The centralization was done in order to increase patient volume, staff experience and quality of care at all remaining acute care units. Another aim was to improve resource utilization. Emergency departments (ED) were to have a new and more central role after the reform. The role of the EDs is to identify and treat ill and injured from both medical and surgical speciali- ties, while discharging the well safely. EDs operate as the interface between the primary sec- tor (general practice) and the specialized wards. The reform also required updated hospital facilities with easier access to radiology, quicker turnaround time on blood samples and 24/7 access to echocardiography. All in all, this was supposed to make care more effective for the acute patient.

International studies on the effect of EDs have shown a decrease in length of stay (6-9), mortality (6, 9-12) and a reduction in transfer to ICU (13) compared with other models of care. However, more studies are needed.

Based on limited evidence the Danish government has invested more than 47 billion DKK in the reorganisation of acute cares system over the past 10 years (14). The reorganisation have had implications on the healthcare system, however, the potential impact on patient outcomes, including mortality, has so far not been evaluated. Our hypothesis is that the reorganisation have improved acute care, which have resulted in a lower short and long term mortality.

Aim First, we aim to characterize the national temporal trends in the prognostic profile, including demographic, clinical and socioeconomic factors, as well as mortality among patients with acute hospitals contacts. Secondly, we will examine changes in mortality prior, during and after the reorganisation in the individual hospitals. Thirdly, we will incorporate additional detailed individual-level data on disease severity to further account for potential confounding.

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Material and methods This project is based on a series of historic cohort studies. The aim of this project is to examine changes in long- and short-term mortality among patients with acute contacts before, during and after the reform of the acute care system in Denmark between 2005 and 2015.

All three studies will have the same time frame; from 1 January 2005 to 31 December 2015, with one year follow up to 31 December 2016. This time period is chosen, to get data from a period prior to, during and after the establishment of the EDs.

Due to the implementation of new electronic patient system in the Capital region of Denmark, the region have had problems with validation of data sent to Danish registers from 1 May 2016 (15). To prevent the influence of this, we choose to end our study period on 31 Decem- ber 2015.

The three studies will be based on data from the Danish National Patient Register, the Danish Civil Registration system, the Danish National Prescription Registry, the Danish National Health Service Register and Statistics Denmark (16-20).

The Danish National Patient Register will be used as a source for information regarding admission and discharge dates, type of contact, discharge diagnoses, comorbidity (calculated as the Charlsons co-morbidity index (CCI) as a marker for chronic co-morbidity burden (21)) and discharge diagnosis(16, 17).

As EDs historically cannot reliably be identified in the Danish registries, we will include all acute hospital contacts. From 2014 acute contacts are registered in the Danish National Pa- tient Register as a separate contact – acute outpatient. Until 2014, the acute outpatients were registered as emergency patients. The admitted patients were registered either as acute or not acute (22). The registration of acute admissions have been validated, and found an overall positive predictive value of acute admission among medical patients to be 97.6 % (95% CI, 93.8%-99.3%) (23). Additional sensitivity analyses will be performed on the data to ensure data are valid.

Follow-up will be done through the Danish Civil Registration system (24, 25). We will extract information regarding civil status, death and emigration date.

The Danish National Prescription Registry obtains statistics on the sale of medicines in Den- mark, and will be used as a source for information regarding medication use (18).

We will extract data on the acute contacts from Statistics Denmark, regarding demographic and socioeconomic data as well as health care utilization (20).

Data from the National Health Service Register will be used regarding data on the numbers of consultations at general practitioner and specialists(19).

Some patients will have more than one acute contact through the study period; all contacts will be a part of the study. Death will only be counted once in relation to the last contact prior to the patient’s death.

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All data will be presented anonymised. Statistical analyses will be performed with Stata version 14.0 or higher (Stat Corporation LP, Texas, USA)

Part 1 Objective: To characterize the national and regional temporal changes in demographic, socioeconomic, clinical characteristics, discharge diagnosis, comorbidities, healthcare utilization including medication use and mortality among patients with acute hospitals contacts between 2005- 2015.

Population: We will include all adult patients (>18 years) with a Danish civil registration number, who have had an acute contact in the study period from January 1 2005 to December 31 2015, with one year follow up to 31 December 2016. Patients will be followed until death, emigration or end of study period, whichever comes first.

Endpoints: Primary endpoint will be seven day and one year mortality. Secondary endpoints age in age groups, length of stay, discharge diagnosis, CCI, readmissions, civil status, medicine use, edu- cation level, income level, numbers of visits at general practitioners and specialists.

Analysis: Data will be stratified by the five regions (Capital Region of Denmark, Region Zealand, Region of Southern Denmark, Central Denmark Region and Region of Northern Denmark), when relevant. Demographic and clinical characteristics will be compared over time using pseudo values. Mortality will be compared using the pseudo values approach in generalized linear models and thereby estimate relative risks and risk differences.

Part 2 Objective: To investigate the changes in seven days and one-year mortality before, during and after the reorganisation of the Danish healthcare system on hospital level.

Population We include adult patients (>18 years) with a Danish civil registration number, who have had an acute contact in the study period from January 1 2005 to December 31 2015, with one year follow up to 31 December 2016. Patients are followed until death, emigration or end of study period, whichever comes first.

Endpoints: Primary endpoint will be seven days and one year mortality.

Analysis: We aim to use a multilevel, longitudinal, stepped-wedge study. Each hospital will have its own unique time period divided into three periods, prior to, during and after the reorganisation.

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The reorganisations happen on different times for each hospital, resulting in individual time- lines for each hospital. The whole period will be defined in months.

Each hospital have different date were EDs were established and the implementation period were unique, due to this each hospital will have individual time periods. Each hospital will be contacted due to obtaining the unique time period for each hospital.

The impact of the reorganisation will be determined with analysing the trends between the three periods according to the stepped-wedge design (26).

A segmented logistic regression model will be used, this includes, a variable A for continues time (months) throughout the entire period, B a variable for time (months) after the beginning of the reorganisation and C a variable for time (months) after the beginning of the post- reorganisation period. These variables model A trends in the prior reorganisation period, B change in trend between the prior to and during the reorganisation period and C changes in trend between the during and the post reorganisation periods. Mixed effect models will be used in order to allow adjustment for heterogeneity between hospitals. In addition, random slops at each period will be used to allow all hospitals to have individual trends through the study period.

Part 3 Objective: To investigate changes in seven days and one year mortality before, during and after the reorganisation of the Danish healthcare system. This study will be on individual level, and results will be adjusted to acute and chronic morbidity.

Population: This study aims to include a representative patient cohort with data from one teaching hospital and one university hospital from each of the five Regions in Denmark. All adult patient (>18 years) with a Danish identification number, who have had an acute contacts to one of the included hospitals in the study period from January 1 2005 to December 31 2015, with one year follow up to 31 December 2016. Patients are followed until death, emigration or end of study period, whichever comes first.

Methods: In addition to the data described earlier, this study will also incorporate data extracted from the local hospital databases on blood test results. Biochemical tests such as albumin, urea and lactate have been shown to be good predictors for short term mortality (27-32). Data from the hospitals will be collected after contact to each hospital. Together with the other patient- related prognostic variables, these data will provide detailed information on the prognostic profile of the individual patient and will enable analyses where potential changes over time in case mix at the individual hospitals have been accounted for.

Endpoints: Primary endpoint will be seven days and one year mortality.

Analysis:

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The multilevel, longitudinal, stepped-wedge analysis mentioned in part 2, will be used on an individual level with adjustment for patient-related prognostic factors as described above. The time period will be divided into 3 periods, prior, during and after the reorganisation.

Collaboration and research group behind the project This project is a part of a larger research program, which aims to investigate how the reformation of the Danish healthcare system has affected the quality of care and patient outcome as well as identify approaches for improvements. The team of researchers are from Hospital of Southern Jutland, Hospital of Southwest Jutland, Odense University Hospital and Centre for Quality, Region of Southern Denmark. We pursue the research aim through six perspectives (Institute of Medicine’s dimensions of quality: safe, patient centred, efficient, timely, effective and equitable) with eight interrelated studies (33). See figure 1.

The group of supervisors consist of experienced researchers within clinical epidemiological, emergency medicine and health economics. Several of supervisors have experienced in super- vising PhD students, and have clinical and research experience with emergency medicine.

Collaboration has been established with Søren Paaske Johnsen, an epidemiologist at Aarhus University (from 1 January 2018 Aalborg University). He has great experience in register research. An international collaboration with Professor Colin Graham, the Chinese University of Hong Kong, has been established. He has great experience in research in emergency medicine.

Ethics In compliance with Danish law, register studies are exempted for the need for approval from an ethics committee. Approval will be sought from Statistics Denmark and the Danish Data Protection Agency. All data extracted from registers and local hospital databases and analyses will be performed on a secure server based at Statistics Denmark.

Milestones The total timeframe of the PhD is 36 months and milestones are presented as a timeline in figure 2.

Dissemination of project results This study will be a PhD study with at least three papers peer reviewed international journals with the PhD student as first author and other authors in accordance with the Vancouver rules for authorship..

Perspectives The reorganisation from the many small hospitals to fewer bigger hospitals has been a huge organisational change. This project will contribute with one side of the facet to understanding the complex picture of the changes in the healthcare system. The findings from this study and the future studies will inform improvement efforts. The knowledge from this research will thus be useful to patients, clinicians and decision makers in Denmark. To raise awareness about this topic, we will conduct an open workshop, based on the achievements of the three parts in this project, once the study is complete. It will be open to all interested parties and invitations disseminated broadly.

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References

1.Sundhedsministeriet I-o. Aftale om strukturreform, juni 2004 Denmark2004 [Available from: http://www.sum.dk/Aktuelt/Publikationer/~/media/Filer%20- %20Publikationer_i_pdf/2004/Strukturaftale.ashx. 2.Sundhedsstyrelsen. Styrket akutberedskab – planlægningsgrundlag for det regionale sundhedsvæsen. 2007 Denmark2007 [Available from: https://www.sst.dk/da/udgivelser/2007/~/media/0B0FC17774D74E7FA404D272DA9C93 69.ashx. 3.Sundhedsstyrelsen. Bilag til rapport om styrket akutberedskab - planlægningsgrundlag for det regionale sundhedsvæsen. 2007 Denmark2007 [Available from: https://www.sst.dk/da/udgivelser/2007/~/media/0B0FC17774D74E7FA404D272DA9C93 69.ashx. 4.Ankjær-Jenen A. Sygehusstruktur i Danmark - en antologi om konsekvenserne af centralisering i sygehusvæsenet. Denmark: DSI Institut for Sundhedsvæsen; 2005 [Available from: https://www.kora.dk/media/763546/dsi-1660.pdf. 5.Sundhedsstyrelsen. Vurdering af den akut medicinske indsats i Danmark 2005 Denmark2005 [Available from: https://www.sst.dk/da/udgivelser/2005/~/media/7784DC45878F4DC185F842DF64E9B68 8.ashx. 6.Conway R, O'Riordan D, Silke B. Long-term outcome of an AMAU--a decade's experience. QJM : monthly journal of the Association of Physicians. 2014;107(1):43-9. 7.St Noble VJ, Davies G, Bell D. Improving continuity of care in an acute medical unit: initial outcomes. QJM : monthly journal of the Association of Physicians. 2008;101(7):529-33. 8.Moloney ED, Bennett K, Silke B. Effect of an acute medical admission unit on key quality indicators assessed by funnel plots. Postgraduate medical journal. 2007;83(984):659-63. 9.Reid LE, Dinesen LC, Jones MC, Morrison ZJ, Weir CJ, Lone NI. The effectiveness and variation of acute medical units: a systematic review. International journal for quality in health care : journal of the International Society for Quality in Health Care. 2016;28(4):433- 46. 10.Rooney T, Moloney ED, Bennett K, O'Riordan D, Silke B. Impact of an acute medical admission unit on hospital mortality: a 5-year prospective study. QJM : monthly journal of the Association of Physicians. 2008;101(6):457-65. 11.Boyle AA, Ahmed V, Palmer CR, Bennett TJ, Robinson SM. Reductions in hospital admissions and mortality rates observed after integrating emergency care: a natural experiment. BMJ open. 2012;2(4). 12.Boyle A, Fuld J, Ahmed V, Bennett T, Robinson S. Does integrated emergency care reduce mortality and non-elective admissions? A retrospective analysis. Emergency medicine journal : EMJ. 2012;29(3):208-12. 13.Yong TY, Li JY, Roberts S, Hakendorf P, Ben-Tovim DI, Thompson CH. The selection of acute medical admissions for a short-stay unit. Internal and emergency medicine. 2011;6(4):321-7. 14.Danske Regioner SoS-oÆ. De danske akutmodtagelser - status 2016 Denmark2016 [Available from: http://www.regioner.dk/media/3084/statusrapport-om- akutmodtagelserne.pdf. 15.Sundhedsdatastyrelsen. Analyse af indberetninger til Landspatientregistret, pr 12. september 2017,

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for hospitalsenheder i Region H der har taget Sundhedsplatformen i brug. 2017 September 26 2017. 16.Lynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scand J Public Health. 2011;39(7 Suppl):30-3. 17.Schmidt M, Schmidt SA, Sandegaard JL, Ehrenstein V, Pedersen L, Sorensen HT. The Danish National Patient Registry: a review of content, data quality, and research potential. Clin Epidemiol. 2015;7:449-90. 18.Kildemoes HW, Sorensen HT, Hallas J. The Danish National Prescription Registry. Scandinavian journal of public health. 2011;39(7 Suppl):38-41. 19.Andersen JS, Olivarius Nde F, Krasnik A. The Danish National Health Service Register. Scandinavian journal of public health. 2011;39(7 Suppl):34-7. 20.http://dst.dk/en/OmDS.aspx: Statistics Denmark; [ 21.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987;40(5):373-83. 22.Institut SS. Slut-rapport - ’Arbejdsgruppen vedr. udarbejdelse af retningslinjer til ensartet national indberetning på akutområdet’ 2012. 23.Vest-Hansen B, Riis AH, Christiansen CF. Registration of acute medical hospital admissions in the Danish National Patient Registry: a validation study. Clinical epidemiology. 2013;5:129- 33. 24.Pedersen CB. The Danish Civil Registration System. Scandinavian journal of public health. 2011;39(7 Suppl):22-5. 25.Schmidt M, Pedersen L, Sorensen HT. The Danish Civil Registration System as a tool in epidemiology. European journal of epidemiology. 2014;29(8):541-9. 26.Brown CA, Lilford RJ. The stepped wedge trial design: a systematic review. BMC medical research methodology. 2006;6:54. 27.Jellinge ME, Henriksen DP, Hallas P, Brabrand M. Hypoalbuminemia is a strong predictor of 30-day all-cause mortality in acutely admitted medical patients: a prospective, observational, cohort study. PloS one. 2014;9(8):e105983. 28.Lyons O, Whelan B, Bennett K, O'Riordan D, Silke B. Serum albumin as an outcome predictor in hospital emergency medical admissions. European journal of internal medicine. 2010;21(1):17-20. 29.Ha DT, Dang TQ, Tran NV, Pham TN, Nguyen ND, Nguyen TV. Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED). Scientific reports. 2017;7:46474. 30.Loekito E, Bailey J, Bellomo R, Hart GK, Hegarty C, Davey P, et al. Common laboratory tests predict imminent death in ward patients. Resuscitation. 2013;84(3):280-5. 31.Goldwasser P, Feldman J. Association of serum albumin and mortality risk. Journal of clinical epidemiology. 1997;50(6):693-703. 32.del Portal DA, Shofer F, Mikkelsen ME, Dorsey PJ, Jr., Gaieski DF, Goyal M, et al. Emergency department lactate is associated with mortality in older adults admitted with and without infections. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine. 2010;17(3):260-8. 33.Delivery IoMUCotNQRoHC. Envisioning the National Health Care Quality Report. Margarita P. Hurtado EKS, and Janet M. Corrigan., editor. Washington (DC): National Academies Press (US); 2001.

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Figure 1: Research framework and studies

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Figure 2: Timeline

Activity 2018 2019 2020 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 General preparation Application and approval - datatilsynet Creating database Part A Data analysis Writing article 1 Part B Data analysis Writing article 2 Part C Data analysis Writing article 3 Study abroad for 3 md in Hong Kong Compiling the Ph.D. Continuous activity Teaching >>> Attending courses >>> Presenting results at conference/relevant meetings >>>

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