Calvo-Cidoncha Elena, Verdinelli Julián, González-Bueno Javier, López-Soto Alfonso, Camacho Hernando Concepción, Pastor-Duran Xavier, Codina-Jané Carles, Lozano-Rubí Raimundo
Pharmacy Service, Hospital Clínic of Barcelona, Barcelona, Spain.
Clinical Informatics Service, Hospital Clínic of Barcelona, Barcelona, Spain.
JMIR Med Inform. 2023 Jul 13;11:e45850. doi: 10.2196/45850.
Inappropriate medication in older patients with multimorbidity results in a greater risk of adverse drug events. Clinical decision support systems (CDSSs) are intended to improve medication appropriateness. One approach to improving CDSSs is to use ontologies instead of relational databases. Previously, we developed OntoPharma-an ontology-based CDSS for reducing medication prescribing errors. The primary aim was to model a domain for improving medication appropriateness in older patients (chronic patient domain). The secondary aim was to implement the version of OntoPharma containing the chronic patient domain in a hospital setting. A 4-step process was proposed. The first step was defining the domain scope. The chronic patient domain focused on improving medication appropriateness in older patients. A group of experts selected the following three use cases: medication regimen complexity, anticholinergic and sedative drug burden, and the presence of triggers for identifying possible adverse events. The second step was domain model representation. The implementation was conducted by medical informatics specialists and clinical pharmacists using Protégé-OWL (Stanford Center for Biomedical Informatics Research). The third step was OntoPharma-driven alert module adaptation. We reused the existing framework based on SPARQL to query ontologies. The fourth step was implementing the version of OntoPharma containing the chronic patient domain in a hospital setting. Alerts generated from July to September 2022 were analyzed. We proposed 6 new classes and 5 new properties, introducing the necessary changes in the ontologies previously created. An alert is shown if the Medication Regimen Complexity Index is ≥40, if the Drug Burden Index is ≥1, or if there is a trigger based on an abnormal laboratory value. A total of 364 alerts were generated for 107 patients; 154 (42.3%) alerts were accepted. We proposed an ontology-based approach to provide support for improving medication appropriateness in older patients with multimorbidity in a scalable, sustainable, and reusable way. The chronic patient domain was built based on our previous research, reusing the existing framework. OntoPharma has been implemented in clinical practice and generates alerts, considering the following use cases: medication regimen complexity, anticholinergic and sedative drug burden, and the presence of triggers for identifying possible adverse events.
老年多病患者使用不适当药物会导致药物不良事件的风险更高。临床决策支持系统（CDSS）旨在提高用药合理性。改进CDSS的一种方法是使用本体而不是关系数据库。此前，我们开发了OntoPharma——一种基于本体的CDSS，用于减少用药处方错误。主要目标是为改善老年患者（慢性病患者领域）的用药合理性构建一个领域模型。次要目标是在医院环境中实施包含慢性病患者领域的OntoPharma版本。我们提出了一个四步流程。第一步是定义领域范围。慢性病患者领域专注于改善老年患者的用药合理性。一组专家选择了以下三个用例：用药方案复杂性、抗胆碱能和镇静药物负担，以及存在识别可能不良事件的触发因素。第二步是领域模型表示。由医学信息学专家和临床药剂师使用Protégé-OWL（斯坦福生物医学信息学研究中心）进行实施。第三步是OntoPharma驱动的警报模块适配。我们重新使用了基于SPARQL的现有框架来查询本体。第四步是在医院环境中实施包含慢性病患者领域的OntoPharma版本。对2022年7月至9月生成的警报进行了分析。我们提出了6个新类和5个新属性，对先前创建的本体进行了必要的更改。如果用药方案复杂性指数≥40、药物负担指数≥1或存在基于异常实验室值的触发因素，则会显示警报。共为107名患者生成了364条警报；154条（42.3%）警报被接受。我们提出了一种基于本体的方法，以可扩展、可持续和可重复使用的方式为改善老年多病患者的用药合理性提供支持。慢性病患者领域是基于我们之前的研究构建的，重新使用了现有框架。OntoPharma已在临床实践中实施并生成警报，考虑了以下用例：用药方案复杂性、抗胆碱能和镇静药物负担，以及存在识别可能不良事件的触发因素。
