ArticleBMC medical informatics and decision making2025
ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management.
Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Development and Temporal Validation of Machine Learning Models for Hyponatremia Risk in Community-Dwelling Older Adults: A Nationwide Claims-Based Study.Journal of clinical medicine · 2026Article
- Adaptive questionnaires for facilitating patient data entry in clinical decision support systems: methods and application to STOPP/START v2.BMC medical informatics and decision making · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPolypharmacy can be both a public health and an economic issue. Medication reviews are structured interviews of the patient by the pharmacist, aiming at optimizing the drug treatment and deprescribing potentially inappropriate medications. However, they remain difficult to perform and time-consuming. Several clinical decision support systems were developed for helping clinicians to reduce inappropriate 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.
methodsABiMed associates several approaches: guidelines implementation, but also 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.
resultsWe 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 in our approach, associating the automatic guidelines execution with the visual presentation of drug knowledge.
conclusionsThe 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.