Pantelis Natsiavas, George Nikolaidis, Jenny Pliatsika, Achilles Chytas, George Giannios, Haralampos Karanikas, Margarita Grammatikopoulou, Martha Zachariadou, Vlasios Dimitriadis, Spiros Nikolopoulos, Ioannis Kompatsiaris
{"title":"PrescIT 平台:可互操作的电子处方临床决策支持系统,用于预防药物不良反应和药物间相互作用。","authors":"Pantelis Natsiavas, George Nikolaidis, Jenny Pliatsika, Achilles Chytas, George Giannios, Haralampos Karanikas, Margarita Grammatikopoulou, Martha Zachariadou, Vlasios Dimitriadis, Spiros Nikolopoulos, Ioannis Kompatsiaris","doi":"10.1007/s40264-024-01455-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and \"intelligent\" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.</p><p><strong>Objectives: </strong>The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.</p><p><strong>Methods: </strong>The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.</p><p><strong>Results: </strong>The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.</p><p><strong>Conclusions: </strong>The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The PrescIT platform: An interoperable Clinical Decision Support System for ePrescription to Prevent Adverse Drug Reactions and Drug-Drug Interactions.\",\"authors\":\"Pantelis Natsiavas, George Nikolaidis, Jenny Pliatsika, Achilles Chytas, George Giannios, Haralampos Karanikas, Margarita Grammatikopoulou, Martha Zachariadou, Vlasios Dimitriadis, Spiros Nikolopoulos, Ioannis Kompatsiaris\",\"doi\":\"10.1007/s40264-024-01455-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and \\\"intelligent\\\" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.</p><p><strong>Objectives: </strong>The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.</p><p><strong>Methods: </strong>The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.</p><p><strong>Results: </strong>The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.</p><p><strong>Conclusions: </strong>The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.</p>\",\"PeriodicalId\":11382,\"journal\":{\"name\":\"Drug Safety\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug Safety\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s40264-024-01455-z\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/20 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Safety","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40264-024-01455-z","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/20 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
The PrescIT platform: An interoperable Clinical Decision Support System for ePrescription to Prevent Adverse Drug Reactions and Drug-Drug Interactions.
Introduction: Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and "intelligent" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.
Objectives: The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.
Methods: The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.
Results: The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.
Conclusions: The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.
期刊介绍:
Drug Safety is the official journal of the International Society of Pharmacovigilance. The journal includes:
Overviews of contentious or emerging issues.
Comprehensive narrative reviews that provide an authoritative source of information on epidemiology, clinical features, prevention and management of adverse effects of individual drugs and drug classes.
In-depth benefit-risk assessment of adverse effect and efficacy data for a drug in a defined therapeutic area.
Systematic reviews (with or without meta-analyses) that collate empirical evidence to answer a specific research question, using explicit, systematic methods as outlined by the PRISMA statement.
Original research articles reporting the results of well-designed studies in disciplines such as pharmacoepidemiology, pharmacovigilance, pharmacology and toxicology, and pharmacogenomics.
Editorials and commentaries on topical issues.
Additional digital features (including animated abstracts, video abstracts, slide decks, audio slides, instructional videos, infographics, podcasts and animations) can be published with articles; these are designed to increase the visibility, readership and educational value of the journal’s content. In addition, articles published in Drug Safety Drugs may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand important medical advances.