Using an Electronic Decision Support Tool to Reduce Inappropriate Polypharmacy and Optimize Medicines: Rationale and Methods

BACKGROUND Polypharmacy and inappropriate continuation of medicines can lead to a significant risk of adverse drug events and drug interactions with patient harm and escalating health care costs as a result. Thorough review of patients' medications focusing on the need for each drug can reduce the potential for harm. Limitations in performing effective medicine reviews in practice include consultation time constraints and funding for pharmacy services. We will aim to overcome these problems by designing an automatic electronic decision support tool (the medicines optimization/review and evaluation (MORE) module) that is embedded in general practice electronic records systems. The tool will focus on medicines optimization and reducing polypharmacy to aid prescribers in reviewing medicines and improve patient outcomes. OBJECTIVE The objectives of this study are: (1) to develop an electronic decision support tool to assist prescribers in performing clinical medication reviews with a particular focus on patients experiencing multimorbidity and polypharmacy, and (2) evaluate and assess the use of the electronic decision support tool, providing pilot data on its usefulness in supporting prescribers during consultations with patients. METHODS The first three study phases involve development of clinical rules outlining clinical interventions and the creation and validation of the MORE decision support tool. Phase four is a community-based, single-blind, prospective, 6-month controlled trial involving two interventions and two control general practices, matched for practice demographics. We will be measuring the number of times prescribers engage with the tool, total number of interventions suggested by the tool, and total number of times prescribers change medicines in response to recommendations. There will also be prospective follow-up of patients in the intervention group to examine whether changes to medications are upheld, and to determine the number of hospitalizations or emergency department visits within 6 months of a medicine intervention. Comparisons between control and intervention practices will measure the changes in proportions of patients with polypharmacy and inappropriately prescribed medicines before and after the introduction of the electronic decision support tool, proportions of patients receiving appropriate treatment in each practice, and changed, maintained, or improved health status, hospitalizations, and deaths in the study year. Initiation rates of inappropriately prescribed medicines will be measured as a secondary outcome. As well as external assessment of the extent of use and application of the tool, prescribers will receive monthly practice progress reports detailing the proportion of their patients experiencing polypharmacy and taking inappropriately prescribed medicines identified for review. RESULTS Phase one has now been completed and the decision support tool is under development. Final data analysis is expected to be available in December 2016. CONCLUSIONS This study will establish whether the MORE decision support tool stands up to real world conditions and promotes changes in prescribing practice.