265 OPERAM: cluster randomised controlled trial - SI using the web-based STRIP Assistant (STRIPA), a decision-support system (see details below). Via the software, based on STRIP recommendations and their own complementary expertise, the physician and the pharmacist generated a first report with prescribing recommendations to discontinue, initiate or modify medications, accompanied by detailed evidence-based explanations. In the third step, this report was discussed with the attending hospital physician to reach a consensus about the recommendations. In addition, to promote patient engagement and to take patient preferences into account, a shared decisionmaking process with the patient or proxy took place. The researchers, treating hospital physicians and the patient agreed on the final medication changes. The research team was trained to each step of the intervention and standard operating procedures supported the process. Lastly, after considering additional in-hospital clinical information (e.g. new diagnoses, adverse drug reactions), a final report was sent to the patient’s GP to inform about in-hospital medication changes and all recommendations, including those that could not be implemented during the index hospitalization. All recommendations provided evidence-based reasons for changes. STRIPA The STRIP Assistant (STRIPA) version 2.0 is a stand-alone, web-based software tool that was used to perform a pharmaceutical analysis, an important step of the STRIP process. Data on diagnoses and current drug use (collected via SHiM and the actual medical record), recent measurements and laboratory values (e.g. renal function, blood pressure) and possible adverse drug reactions, as listed in the patient’s medical record and according to patient information (SHiM) were entered in STRIPA. The assignment of drugs to diseases has been implemented through a drag and drop mechanism (see Methods appendix Figure). START A1 and START A2 were merged to one and STOPP A2 could not be converted into an algorithm, leaving a total of 79 STOPP and 33 START algorithms implemented into the clinical decision support system. Based on these data, pharmacotherapy optimization signals were generated by the clinical decision support software and evaluated for appropriateness on the individual patient level by the research physician and pharmacist. 3
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