Rishi J Desai, Keith Marsolo, Joshua Smith, David Carrell, Robert Penfold, Haritha S Pillai, Joyce Lii, Kerry Ngan, Robert Winter, Margaret Adgent, Arvind Ramaprasan, Meighan Rogers Driscoll, Daniel Scarnecchia, Daniel Kiernan, Christine Draper, Jennifer G Lyons, Anjum Khurshid, Judith C Maro, Ruth Zimmerman, Jeffrey Brown, Patricia Bright, José J Hernández-Muñoz, Michael E Matheny, Sebastian Schneeweiss
{"title":"FDA 哨兵真实世界证据数据企业 (RWE-DE)。","authors":"Rishi J Desai, Keith Marsolo, Joshua Smith, David Carrell, Robert Penfold, Haritha S Pillai, Joyce Lii, Kerry Ngan, Robert Winter, Margaret Adgent, Arvind Ramaprasan, Meighan Rogers Driscoll, Daniel Scarnecchia, Daniel Kiernan, Christine Draper, Jennifer G Lyons, Anjum Khurshid, Judith C Maro, Ruth Zimmerman, Jeffrey Brown, Patricia Bright, José J Hernández-Muñoz, Michael E Matheny, Sebastian Schneeweiss","doi":"10.1002/pds.70028","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making.</p><p><strong>Methods: </strong>In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives.</p><p><strong>Results: </strong>We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed.</p><p><strong>Conclusions: </strong>Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.</p>","PeriodicalId":19782,"journal":{"name":"Pharmacoepidemiology and Drug Safety","volume":"33 10","pages":"e70028"},"PeriodicalIF":2.4000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).\",\"authors\":\"Rishi J Desai, Keith Marsolo, Joshua Smith, David Carrell, Robert Penfold, Haritha S Pillai, Joyce Lii, Kerry Ngan, Robert Winter, Margaret Adgent, Arvind Ramaprasan, Meighan Rogers Driscoll, Daniel Scarnecchia, Daniel Kiernan, Christine Draper, Jennifer G Lyons, Anjum Khurshid, Judith C Maro, Ruth Zimmerman, Jeffrey Brown, Patricia Bright, José J Hernández-Muñoz, Michael E Matheny, Sebastian Schneeweiss\",\"doi\":\"10.1002/pds.70028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making.</p><p><strong>Methods: </strong>In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives.</p><p><strong>Results: </strong>We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed.</p><p><strong>Conclusions: </strong>Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.</p>\",\"PeriodicalId\":19782,\"journal\":{\"name\":\"Pharmacoepidemiology and Drug Safety\",\"volume\":\"33 10\",\"pages\":\"e70028\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmacoepidemiology and Drug Safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/pds.70028\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacoepidemiology and Drug Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/pds.70028","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).
Purpose: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making.
Methods: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives.
Results: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed.
Conclusions: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.
期刊介绍：
The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report.
Particular areas of interest include:
design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology;
comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world;
methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology;
assessments of harm versus benefit in drug therapy;
patterns of drug utilization;
relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines;
evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.
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