{"title":"使用数据驱动的决策算法和真实世界的数据更新临床实践指南。","authors":"Thijs van Vegchel, Kees C W J Ebben","doi":"10.3233/SHTI250312","DOIUrl":null,"url":null,"abstract":"<p><p>Clinical practice guidelines often struggle to stay updated, especially as cancer care becomes more personalized. We transformed guidelines into data-driven Clinical Decision Algorithms (CDAs) and compared Dutch and US CDAs, enriching the Dutch version with real-world data from the Netherlands Cancer Registry. An interactive dashboard was developed to automate guideline comparisons, adherence analysis, and alternative treatment evaluations, enabling timely updates and more responsive, evidence-based care.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"327 ","pages":"229-230"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Data-Driven Decision Algorithms and Real-World Data for Updating Clinical Practice Guidelines.\",\"authors\":\"Thijs van Vegchel, Kees C W J Ebben\",\"doi\":\"10.3233/SHTI250312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Clinical practice guidelines often struggle to stay updated, especially as cancer care becomes more personalized. We transformed guidelines into data-driven Clinical Decision Algorithms (CDAs) and compared Dutch and US CDAs, enriching the Dutch version with real-world data from the Netherlands Cancer Registry. An interactive dashboard was developed to automate guideline comparisons, adherence analysis, and alternative treatment evaluations, enabling timely updates and more responsive, evidence-based care.</p>\",\"PeriodicalId\":94357,\"journal\":{\"name\":\"Studies in health technology and informatics\",\"volume\":\"327 \",\"pages\":\"229-230\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-15\",\"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/SHTI250312\",\"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/SHTI250312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Data-Driven Decision Algorithms and Real-World Data for Updating Clinical Practice Guidelines.
Clinical practice guidelines often struggle to stay updated, especially as cancer care becomes more personalized. We transformed guidelines into data-driven Clinical Decision Algorithms (CDAs) and compared Dutch and US CDAs, enriching the Dutch version with real-world data from the Netherlands Cancer Registry. An interactive dashboard was developed to automate guideline comparisons, adherence analysis, and alternative treatment evaluations, enabling timely updates and more responsive, evidence-based care.