{"title":"测量计算机化医嘱输入系统(CPOE)中警报效率的新型数据可视化方法","authors":"Shuo-Chen Chien , Chia-Hui Chien , Chun-You Chen , Yen-Po (Harvey) Chin , Po-Han Chien , Chun-Kung Hsu , Hsuan-Chia Yang , Yu-Chuan (Jack) Li","doi":"10.1016/j.hlpt.2024.100852","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>To introduce a novel visualization technique for evaluating the efficacy of clinical decision support system (CDSS) alerts as perceived by physicians and to differentiate between various alert categories for optimization.</p></div><div><h3>Methods</h3><p>We developed a visualization method, which segments into four distinct zones: Appropriate (+/+), Over-frequent yet Effective (−/+), Potentially Problematic (−/−), and Less Effective but Acceptably Frequent (+/−). Alerts from a 908-bed academic medical center in Northern Taiwan were collected over two years and classified using this technique, along with three perspectives: Safety, Completeness, and Response.</p></div><div><h3>Results</h3><p>We collected the viewpoints of 72 clinical physicians on the system's top 20 most frequent alerts. The proposed visualization technique offers a user-centric, adaptable method for assessing CDSS alerts. Roughly five alerts were categorized as Potentially Problematic, whereas another five were deemed Appropriate. Intriguingly, certain alerts, while not beneficial for patient safety, were found to assist physicians in completing clinical workflows.</p></div><div><h3>Conclusions</h3><p>This approach, emphasizing visual clarity and adaptability, diverges from traditional methods that lean heavily on expert opinions or statistics. It paves the way for diverse assessment perspectives, furnishing healthcare institutions with a valuable tool to improve CDSS alert systems, ensuring a harmonious balance between user efficiency and patient safety.</p></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"13 2","pages":"Article 100852"},"PeriodicalIF":3.4000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel data visualization method to measure alert efficiency in computerized physician order entry (CPOE) system\",\"authors\":\"Shuo-Chen Chien , Chia-Hui Chien , Chun-You Chen , Yen-Po (Harvey) Chin , Po-Han Chien , Chun-Kung Hsu , Hsuan-Chia Yang , Yu-Chuan (Jack) Li\",\"doi\":\"10.1016/j.hlpt.2024.100852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>To introduce a novel visualization technique for evaluating the efficacy of clinical decision support system (CDSS) alerts as perceived by physicians and to differentiate between various alert categories for optimization.</p></div><div><h3>Methods</h3><p>We developed a visualization method, which segments into four distinct zones: Appropriate (+/+), Over-frequent yet Effective (−/+), Potentially Problematic (−/−), and Less Effective but Acceptably Frequent (+/−). Alerts from a 908-bed academic medical center in Northern Taiwan were collected over two years and classified using this technique, along with three perspectives: Safety, Completeness, and Response.</p></div><div><h3>Results</h3><p>We collected the viewpoints of 72 clinical physicians on the system's top 20 most frequent alerts. The proposed visualization technique offers a user-centric, adaptable method for assessing CDSS alerts. Roughly five alerts were categorized as Potentially Problematic, whereas another five were deemed Appropriate. Intriguingly, certain alerts, while not beneficial for patient safety, were found to assist physicians in completing clinical workflows.</p></div><div><h3>Conclusions</h3><p>This approach, emphasizing visual clarity and adaptability, diverges from traditional methods that lean heavily on expert opinions or statistics. It paves the way for diverse assessment perspectives, furnishing healthcare institutions with a valuable tool to improve CDSS alert systems, ensuring a harmonious balance between user efficiency and patient safety.</p></div>\",\"PeriodicalId\":48672,\"journal\":{\"name\":\"Health Policy and Technology\",\"volume\":\"13 2\",\"pages\":\"Article 100852\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Policy and Technology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211883724000157\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH POLICY & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Policy and Technology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211883724000157","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
Novel data visualization method to measure alert efficiency in computerized physician order entry (CPOE) system
Objectives
To introduce a novel visualization technique for evaluating the efficacy of clinical decision support system (CDSS) alerts as perceived by physicians and to differentiate between various alert categories for optimization.
Methods
We developed a visualization method, which segments into four distinct zones: Appropriate (+/+), Over-frequent yet Effective (−/+), Potentially Problematic (−/−), and Less Effective but Acceptably Frequent (+/−). Alerts from a 908-bed academic medical center in Northern Taiwan were collected over two years and classified using this technique, along with three perspectives: Safety, Completeness, and Response.
Results
We collected the viewpoints of 72 clinical physicians on the system's top 20 most frequent alerts. The proposed visualization technique offers a user-centric, adaptable method for assessing CDSS alerts. Roughly five alerts were categorized as Potentially Problematic, whereas another five were deemed Appropriate. Intriguingly, certain alerts, while not beneficial for patient safety, were found to assist physicians in completing clinical workflows.
Conclusions
This approach, emphasizing visual clarity and adaptability, diverges from traditional methods that lean heavily on expert opinions or statistics. It paves the way for diverse assessment perspectives, furnishing healthcare institutions with a valuable tool to improve CDSS alert systems, ensuring a harmonious balance between user efficiency and patient safety.
期刊介绍:
Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments.
HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology.
Topics covered by HPT will include:
- Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems
- Cross-national comparisons on health policy using evidence-based approaches
- National studies on health policy to determine the outcomes of technology-driven initiatives
- Cross-border eHealth including health tourism
- The digital divide in mobility, access and affordability of healthcare
- Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies
- Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies
- Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making
- Stakeholder engagement with health technologies (clinical and patient/citizen buy-in)
- Regulation and health economics