Complex drug therapy might impede the safe and reliable medication administration to patients. Consequently, a novel tool automatically evaluates structured pharmaceutical data for elements that might contribute to the complexity. It then personalizes the results by assessing the importance of each found component to the patient through key questions. Consequently, customized optimization measures might be provided. In this controlled, prospective, exploratory investigation, 9 general practitioners (GP) were evaluated in 3 research groups: In the 2 intervention groups, the tool was used in versions with (GI_with) and without (GI_without) personalized key questions for the analysis. In contrast, the control group (GC) did not utilize any tools (routine care). The patient-perspective effects of optimization techniques to reduce or lessen the complexity of pharmacological therapy were evaluated 4 to 8 weeks following the implementation of the instrument. A total of 126 patients who frequently used more than 5 medications could be analyzed. GP offered 117 GI_with optimization measures, 83 GI_without optimizations, and 2 GC optimization measures. GI_with patients were more likely to rate an optimization measure as useful than GI_without patients (IRR: 3.5; 95% CI: 1.2–10.3). Thus, the number of recommended optimization measures had no significant effect (P=0.167). The study implied that an automated analysis that took patient perceptions into account leads to more beneficial optimization methods than an automated analysis alone; this finding needs to be confirmed by other research.

Source –bmcprimcare.biomedcentral.com/articles/10.1186/s12875-022-01757-0