ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management
CoRR(2023)
摘要
Background: Polypharmacy, i.e. taking five drugs or more, is both a public
health and an economic issue. Medication reviews are structured interviews of
the patient by the community pharmacist, aiming at optimizing the drug
treatment and deprescribing useless, redundant or dangerous drugs. However,
they remain difficult to perform and time-consuming. Several clinical decision
support systems were developed for helping clinicians to manage polypharmacy.
However, most were limited to the implementation of clinical practice
guidelines. In this work, our objective is to design an innovative clinical
decision support system for medication reviews and polypharmacy management,
named ABiMed.
Methods: ABiMed associates several approaches: guidelines implementation, but
the automatic extraction of patient data from the GP's electronic health record
and its transfer to the pharmacist, and the visual presentation of
contextualized drug knowledge using visual analytics. We performed an ergonomic
assessment and qualitative evaluations involving pharmacists and GPs during
focus groups and workshops.
Results: We describe the proposed architecture, which allows a collaborative
multi-user usage. We present the various screens of ABiMed for entering or
verifying patient data, for accessing drug knowledge (posology, adverse
effects, interactions), for viewing STOPP/START rules and for suggesting
modification to the treatment. Qualitative evaluations showed that health
professionals were highly interested by our approach, associating the automatic
guidelines execution with the visual presentation of drug knowledge.
Conclusions: The association of guidelines implementation with visual
presentation of knowledge is a promising approach for managing polypharmacy.
Future works will focus on the improvement and the evaluation of ABiMed.
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