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| Natura: | Preprint |
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2024
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| Accesso online: | https://arxiv.org/abs/2409.01903 |
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| _version_ | 1866910588468199424 |
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| author | Mouazer, Abdelmalek Dubois, Sophie Léguillon, Romain Boudegzdame, Nada Levrard, Thibaud Bars, Yoann Le Simon, Christian Séroussi, Brigitte Grosjean, Julien Lelong, Romain Letord, Catherine Darmoni, Stéfan Sedki, Karima Meneton, Pierre Tsopra, Rosy Falcoff, Hector Lamy, Jean-Baptiste |
| author_facet | Mouazer, Abdelmalek Dubois, Sophie Léguillon, Romain Boudegzdame, Nada Levrard, Thibaud Bars, Yoann Le Simon, Christian Séroussi, Brigitte Grosjean, Julien Lelong, Romain Letord, Catherine Darmoni, Stéfan Sedki, Karima Meneton, Pierre Tsopra, Rosy Falcoff, Hector Lamy, Jean-Baptiste |
| contents | Background: Medication review is a structured interview of the patient, performed by the pharmacist and aimed at optimizing drug treatments. In practice, medication review is a long and cognitively-demanding task that requires specific knowledge. Clinical practice guidelines have been proposed, but their application is tedious. Methods: We designed ABiMed, a clinical decision support system for medication reviews, based on the implementation of the STOPP/START v2 guidelines and on the visual presentation of aggregated drug knowledge using tables, graphs and flower glyphs. We evaluated ABiMed with 39 community pharmacists during a randomized simulation trial, each pharmacist performing a medication review for two fictitious patients without ABiMed, and two others with ABiMed. We recorded the problems identified by the pharmacists, the interventions proposed, the response time, the perceived usability and the comments. Pharmacists' medication reviews were compared to an expert-designed gold standard. Results: With ABiMed, pharmacists found 1.6 times more relevant drug-related problems during the medication review (p=1.1e-12) and proposed better interventions (p=9.8e-9), without needing more time (p=0.56). The System Usability Scale score is 82.7, which is ranked "excellent". In their comments, pharmacists appreciated the visual aspect of ABiMed and its ability to compare the current treatment with the proposed one. A multifactor analysis showed no difference in the support offered by ABiMed according to the pharmacist's age or sex, in terms of percentage of problems identified or quality of the proposed interventions. Conclusions: The use of an intelligent and visual clinical decision support system can help pharmacists when they perform medication reviews. Our main perspective is the validation of the system in clinical conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_01903 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A randomized simulation trial evaluating ABiMed, a clinical decision support system for medication reviews and polypharmacy management Mouazer, Abdelmalek Dubois, Sophie Léguillon, Romain Boudegzdame, Nada Levrard, Thibaud Bars, Yoann Le Simon, Christian Séroussi, Brigitte Grosjean, Julien Lelong, Romain Letord, Catherine Darmoni, Stéfan Sedki, Karima Meneton, Pierre Tsopra, Rosy Falcoff, Hector Lamy, Jean-Baptiste Artificial Intelligence Human-Computer Interaction J.3 Background: Medication review is a structured interview of the patient, performed by the pharmacist and aimed at optimizing drug treatments. In practice, medication review is a long and cognitively-demanding task that requires specific knowledge. Clinical practice guidelines have been proposed, but their application is tedious. Methods: We designed ABiMed, a clinical decision support system for medication reviews, based on the implementation of the STOPP/START v2 guidelines and on the visual presentation of aggregated drug knowledge using tables, graphs and flower glyphs. We evaluated ABiMed with 39 community pharmacists during a randomized simulation trial, each pharmacist performing a medication review for two fictitious patients without ABiMed, and two others with ABiMed. We recorded the problems identified by the pharmacists, the interventions proposed, the response time, the perceived usability and the comments. Pharmacists' medication reviews were compared to an expert-designed gold standard. Results: With ABiMed, pharmacists found 1.6 times more relevant drug-related problems during the medication review (p=1.1e-12) and proposed better interventions (p=9.8e-9), without needing more time (p=0.56). The System Usability Scale score is 82.7, which is ranked "excellent". In their comments, pharmacists appreciated the visual aspect of ABiMed and its ability to compare the current treatment with the proposed one. A multifactor analysis showed no difference in the support offered by ABiMed according to the pharmacist's age or sex, in terms of percentage of problems identified or quality of the proposed interventions. Conclusions: The use of an intelligent and visual clinical decision support system can help pharmacists when they perform medication reviews. Our main perspective is the validation of the system in clinical conditions. |
| title | A randomized simulation trial evaluating ABiMed, a clinical decision support system for medication reviews and polypharmacy management |
| topic | Artificial Intelligence Human-Computer Interaction J.3 |
| url | https://arxiv.org/abs/2409.01903 |