Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence

Author:

Franklin Joseph B.1,Marra Caroline1,Abebe Kaleab Z.2,Butte Atul J.34,Cook Deborah J.5,Esserman Laura6,Fleisher Lee A.7,Grossman Cynthia I.8,Kass Nancy E.9,Krumholz Harlan M.10,Rowan Kathy1112,Abernethy Amy P.13, ,Abbasi Ali B14,Abebe Kaleab Z14,Abernethy Amy P14,Adam Stacey J.14,Angus Derek C14,Ard Jamy14,Bender Ignacio Rachel A14,Berkwits Michael14,Berry Scott M14,Bhatt Deepak L.14,Bibbins-Domingo Kirsten14,Bonow Robert O.14,Bonten Marc14,Brangman Sharon A.14,Brownstein John14,Buntin Melinda J. B.14,Butte Atul J14,Califf Robert M.14,Campbell Marion K14,Cappola Anne R.14,Chiang Anne C14,Cook Deborah14,Cummings Steven R14,Curfman Gregory14,Esserman Laura J14,Fleisher Lee A14,Franklin Joseph B14,Gonzalez Ralph14,Grossman Cynthia I14,Haddad Tufia C.14,Herbst Roy S.14,Hernandez Adrian F.14,Holder Diane P14,Horn Leora14,Huang Grant D.14,Huang Alison14,Kass Nancy14,Khera Rohan14,Koroshetz Walter J.14,Krumholz Harlan M.14,Landray Martin14,Lewis Roger J.14,Lieu Tracy A14,Malani Preeti N.14,Martin Christa Lese14,McClellan Mark14,McDermott Mary M.14,Morain Stephanie R.14,Murphy Susan A14,Nicholls Stuart G14,Nicholls Stephen J14,O'Dwyer Peter J.14,Patel Bhakti K14,Peterson Eric14,Prindiville Sheila A.14,Ross Joseph S.14,Rowan Kathryn M14,Rubenfeld Gordon14,Seymour Christopher W.14,Taylor Rod S14,Waldstreicher Joanne14,Wang Tracy Y.14

Affiliation:

1. Verily Life Sciences, South San Francisco, California

2. Center for Biostatistics & Qualitative Methodology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania

3. Bakar Computational Health Sciences Institute, University of California, San Francisco

4. Center for Data-Driven Insights and Innovation, University of California Health, Oakland

5. Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada

6. Departments of Surgery and Radiology and Institute for Health Policy Studies, University of California, San Francisco

7. Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia

8. Biogen, Boston, Massachusetts

9. Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

10. Yale University School of Medicine, New Haven, Connecticut

11. National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research Programme, London, United Kingdom

12. Intensive Care National Audit & Research Centre (ICNARC), London, United Kingdom

13. Highlander Health, Dallas, Texas

14. for the JAMA Summit on Clinical Trials Participants

Abstract

ImportanceThe ways in which we access, acquire, and use data in clinical trials have evolved very little over time, resulting in a fragmented and inefficient system that limits the amount and quality of evidence that can be generated.ObservationsClinical trial design has advanced steadily over several decades. Yet the infrastructure for clinical trial data collection remains expensive and labor intensive and limits the amount of evidence that can be collected to inform whether and how interventions work for different patient populations. Meanwhile, there is increasing demand for evidence from randomized clinical trials to inform regulatory decisions, payment decisions, and clinical care. Although substantial public and industry investment in advancing electronic health record interoperability, data standardization, and the technology systems used for data capture have resulted in significant progress on various aspects of data generation, there is now a need to combine the results of these efforts and apply them more directly to the clinical trial data infrastructure.Conclusions and RelevanceWe describe a vision for a modernized infrastructure that is centered around 2 related concepts. First, allowing the collection and rigorous evaluation of multiple data sources and types and, second, enabling the possibility to reuse health data for multiple purposes. We address the need for multidisciplinary collaboration and suggest ways to measure progress toward this goal.

Publisher

American Medical Association (AMA)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3