Michelle Pfaffenlehner, Max Behrens, Daniela Zöller, Kathrin Ungethüm, Kai Günther, Viktoria Rücker, Jens-Peter Reese, Peter Heuschmann, Miriam Kesselmeier, Flavia Remo, André Scherag, Harald Binder, Nadine Binder, the EVA4MII project
{"title":"利用常规临床护理数据获取真实世界证据的方法论挑战:利用系统文献检索和焦点小组讨论进行快速审查","authors":"Michelle Pfaffenlehner, Max Behrens, Daniela Zöller, Kathrin Ungethüm, Kai Günther, Viktoria Rücker, Jens-Peter Reese, Peter Heuschmann, Miriam Kesselmeier, Flavia Remo, André Scherag, Harald Binder, Nadine Binder, the EVA4MII project","doi":"10.1101/2024.09.05.24313049","DOIUrl":null,"url":null,"abstract":"<strong>Background</strong> The integration of real-world evidence (RWE) from real-world data (RWD) in clinical research is crucial for bridging the gap between clinical trial results and real-world outcomes. Analyzing routinely collected data to generate clinical evidence faces methodological concerns like confounding and bias, similar to prospectively documented observational studies. This study focuses on additional limitations frequently reported in the literature, providing an overview of the challenges and biases inherent to analyzing routine clinical care data, including health claims data (hereafter: routine data).","PeriodicalId":501071,"journal":{"name":"medRxiv - Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Methodological Challenges using Routine Clinical Care Data for Real-World Evidence: a Rapid Review utilizing a systematic literature search and focus group discussion\",\"authors\":\"Michelle Pfaffenlehner, Max Behrens, Daniela Zöller, Kathrin Ungethüm, Kai Günther, Viktoria Rücker, Jens-Peter Reese, Peter Heuschmann, Miriam Kesselmeier, Flavia Remo, André Scherag, Harald Binder, Nadine Binder, the EVA4MII project\",\"doi\":\"10.1101/2024.09.05.24313049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Background</strong> The integration of real-world evidence (RWE) from real-world data (RWD) in clinical research is crucial for bridging the gap between clinical trial results and real-world outcomes. Analyzing routinely collected data to generate clinical evidence faces methodological concerns like confounding and bias, similar to prospectively documented observational studies. This study focuses on additional limitations frequently reported in the literature, providing an overview of the challenges and biases inherent to analyzing routine clinical care data, including health claims data (hereafter: routine data).\",\"PeriodicalId\":501071,\"journal\":{\"name\":\"medRxiv - Epidemiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Epidemiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.09.05.24313049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.05.24313049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Methodological Challenges using Routine Clinical Care Data for Real-World Evidence: a Rapid Review utilizing a systematic literature search and focus group discussion
Background The integration of real-world evidence (RWE) from real-world data (RWD) in clinical research is crucial for bridging the gap between clinical trial results and real-world outcomes. Analyzing routinely collected data to generate clinical evidence faces methodological concerns like confounding and bias, similar to prospectively documented observational studies. This study focuses on additional limitations frequently reported in the literature, providing an overview of the challenges and biases inherent to analyzing routine clinical care data, including health claims data (hereafter: routine data).