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Digital Medication Management in Polypharmacy—Findings of a Cluster-Randomized, Controlled Trial With a Stepped-Wedge
Robin Brünn1, Jale Basten, Dorothea Lemke
1Institute of General Practice, Goethe University Frankfurt am Main; Pharmacy of University Hospital Frankfurt; Department of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum; Department of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum; Institute of General Practice, Goethe University Frankfurt am Main; Working Group General and Family Medicine, Medical Faculty East Westphalia-Lippe, University of Bielefeld; Institute of General Practice, Goethe University Frankfurt am Main; Bergisch Competence Center for Health Economics and Health Services Research, Bergische University Wuppertal; Chair of General Medicine II and Patient Orientation in Primary Care, Institute of General Medicine and Ambulatory Health Care (iamag), University Witten/Herdecke; Working Group for Health Economics and Health Management, Faculty of ; Health Sciences, Bielefeld University; Chairman of the Drug Therapy Management and Drug Therapy Safety Commission, German Society for Internal Medicine (DGIM); Barmer, Wuppertal; Institute of Clinical Pharmacology, University Hospital and Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main; Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Gold Coast, Queensland, 4229, Australia; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; PMV Research Group, Faculty of Medicine, University Hospital Cologne, University of Cologne; Institute of General Practice, Goethe-University Frankfurt am Main; Department of Family Medicine, Care and Public Health Research Institute, Maastricht University; Department of Public Health and Primary Care, Academic Centre of General Practice, KU Leuven.
Background:
Inappropriate drug prescriptions for patients with polypharmacy can have avoidable adverse consequences. We studied the effects of a clinical decision-support system (CDSS) for medication management on hospitalizations and mortality.
Methods:
This stepped-wedge, cluster-randomized, controlled trial involved an open cohort of adult patients with polypharmacy in primary care practices (=clusters) in Westphalia-Lippe, Germany. During the period of the intervention, their medication lists were checked annually using the CDSS. The CDSS warns against inappropriate prescriptions on the basis of patient-related health insurance data. The combined primary endpoint consisted of overall mortality and hospitalization for any reason. The secondary endpoints were mortality, hospitalizations, and high-risk prescription. We analyzed the quarterly health insurance data of the intention- to-treat population with a mixed logistic model taking account of clustering and repeated measurements. Sensitivity analyses addressed effects of the COVID-19 pandemic and other effects.
Results:
688 primary care practices were randomized, and data were obtained on 42 700 patients over 391 994 quarter years. No significant reduction was found in either the primary endpoint (odds ratio [OR] 1.00; 95% confidence interval [0.95; 1.04]; p = 0.8716) or the secondary endpoints (hospitalizations: OR 1.00 [0.95; 1.05]; mortality: OR 1.04 [0.92; 1.17]; high-risk prescription: OR 0.98 [0.92; 1.04]).
Conclusion:
The planned analyses did not reveal any significant effect of the intervention. Pandemicadjusted analyses yielded evidence that the mortality of adult patients with polypharmacy might potentially be lowered by the CDSS. Controlled trials with appropriate follow-up are needed to prove that a CDSS has significant effects on mortality in patients with polypharmacy.
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