{"title":"一个智能和可视化的临床决策支持系统,用于医院入院时的药物调解。","authors":"Rory Schofield, Jean-Baptiste Lamy","doi":"10.3233/SHTI251505","DOIUrl":null,"url":null,"abstract":"<p><p>Medication reconciliation (MR) aims to prevent medication errors during transitions of care, particularly at hospital admission. Despite its importance, MR remains time-consuming, and existing electronic tools lack collaborative features and visual approaches. This study describes the design of a new electronic tool for MR, developed within ABiMed, a clinical decision support system for medication review and polypharmacy management. The tool follows the main steps of the MR process: the best possible medication history (BPMH) elaborated by the pharmacist is compared to the admission medication order (AMO), and discrepancies are semi-automatically identified and classified. Unresolved discrepancies can be directly sent to the prescriber. The tool builds on features included in ABiMed, such as an ontology-based structure allowing for integration in other tools, real-time collaboration between pharmacists and prescribers, visual drug data specific to the patient, and automatic execution of STOPP/START clinical guidelines. These approaches encourage shared responsibility, and support more clinically relevant and useful pharmacist interventions. The tool has yet to undergo clinical evaluation. Future work will assess usability and impact on outcomes such as time spent on MR, prescriber acceptance of interventions, and the tool will further be expanded to include more clinical guidelines.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"103-107"},"PeriodicalIF":0.0000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Intelligent and Visual Clinical Decision Support System for Medication Reconciliation at Admission in a Hospital Setting.\",\"authors\":\"Rory Schofield, Jean-Baptiste Lamy\",\"doi\":\"10.3233/SHTI251505\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Medication reconciliation (MR) aims to prevent medication errors during transitions of care, particularly at hospital admission. Despite its importance, MR remains time-consuming, and existing electronic tools lack collaborative features and visual approaches. This study describes the design of a new electronic tool for MR, developed within ABiMed, a clinical decision support system for medication review and polypharmacy management. The tool follows the main steps of the MR process: the best possible medication history (BPMH) elaborated by the pharmacist is compared to the admission medication order (AMO), and discrepancies are semi-automatically identified and classified. Unresolved discrepancies can be directly sent to the prescriber. The tool builds on features included in ABiMed, such as an ontology-based structure allowing for integration in other tools, real-time collaboration between pharmacists and prescribers, visual drug data specific to the patient, and automatic execution of STOPP/START clinical guidelines. These approaches encourage shared responsibility, and support more clinically relevant and useful pharmacist interventions. The tool has yet to undergo clinical evaluation. Future work will assess usability and impact on outcomes such as time spent on MR, prescriber acceptance of interventions, and the tool will further be expanded to include more clinical guidelines.</p>\",\"PeriodicalId\":94357,\"journal\":{\"name\":\"Studies in health technology and informatics\",\"volume\":\"332 \",\"pages\":\"103-107\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies in health technology and informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/SHTI251505\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in health technology and informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI251505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Intelligent and Visual Clinical Decision Support System for Medication Reconciliation at Admission in a Hospital Setting.
Medication reconciliation (MR) aims to prevent medication errors during transitions of care, particularly at hospital admission. Despite its importance, MR remains time-consuming, and existing electronic tools lack collaborative features and visual approaches. This study describes the design of a new electronic tool for MR, developed within ABiMed, a clinical decision support system for medication review and polypharmacy management. The tool follows the main steps of the MR process: the best possible medication history (BPMH) elaborated by the pharmacist is compared to the admission medication order (AMO), and discrepancies are semi-automatically identified and classified. Unresolved discrepancies can be directly sent to the prescriber. The tool builds on features included in ABiMed, such as an ontology-based structure allowing for integration in other tools, real-time collaboration between pharmacists and prescribers, visual drug data specific to the patient, and automatic execution of STOPP/START clinical guidelines. These approaches encourage shared responsibility, and support more clinically relevant and useful pharmacist interventions. The tool has yet to undergo clinical evaluation. Future work will assess usability and impact on outcomes such as time spent on MR, prescriber acceptance of interventions, and the tool will further be expanded to include more clinical guidelines.