Digital Medication Management in Polypharmacy

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. Pandemic-adjusted 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.