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            <div class="meta-super-class">Integrating Clinical Trials and Practice</div>
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          <div class="meta-date"><span class="epreprint"><span class="month">August&nbsp;</span><span class="day">5, </span><span class="year">2024</span></span></div>
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            <h1 class="meta-article-title ">Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence</h1>
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            <span class="meta-authors--limited"><span
                class="wi-fullname brand-fg"><a href="/searchresults?author=Joseph+B.+Franklin&amp;q=Joseph+B.+Franklin" rel="nofollow" target="_blank">Joseph B.&nbsp;Franklin,&nbsp;JD, PhD<sup>1</sup></a></span><span class="al-author-delim">;
              </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Caroline+Marra&amp;q=Caroline+Marra" rel="nofollow" target="_blank">Caroline&nbsp;Marra,&nbsp;PhD<sup>1</sup></a></span><span class="al-author-delim">;
              </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Kaleab+Z.+Abebe&amp;q=Kaleab+Z.+Abebe" rel="nofollow" target="_blank">Kaleab Z.&nbsp;Abebe,&nbsp;PhD<sup>2</sup></a></span>;
              <a class="meta-authors--etal td-u stats-meta-authors--etal">et al</a></span>
            <span class="meta-authors--remaining"><span class="wi-fullname brand-fg"><a href="/searchresults?author=Atul+J.+Butte&amp;q=Atul+J.+Butte" rel="nofollow" target="_blank">Atul J.&nbsp;Butte,&nbsp;MD, PhD<sup>3,4</sup></a></span><span
                class="al-author-delim">; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Deborah+J.+Cook&amp;q=Deborah+J.+Cook" rel="nofollow" target="_blank">Deborah J.&nbsp;Cook,&nbsp;MD<sup>5</sup></a></span><span
                class="al-author-delim">; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Laura+Esserman&amp;q=Laura+Esserman" rel="nofollow" target="_blank">Laura&nbsp;Esserman,&nbsp;MD, MBA<sup>6</sup></a></span><span
                class="al-author-delim">; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Lee+A.+Fleisher&amp;q=Lee+A.+Fleisher" rel="nofollow" target="_blank">Lee A.&nbsp;Fleisher,&nbsp;MD<sup>7</sup></a></span><span
                class="al-author-delim">; </span><span
                class="wi-fullname brand-fg"><a href="/searchresults?author=Cynthia+I.+Grossman&amp;q=Cynthia+I.+Grossman" rel="nofollow" target="_blank">Cynthia I.&nbsp;Grossman,&nbsp;PhD<sup>8</sup></a></span><span class="al-author-delim">;
              </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Nancy+E.+Kass&amp;q=Nancy+E.+Kass" rel="nofollow" target="_blank">Nancy E.&nbsp;Kass,&nbsp;ScD<sup>9</sup></a></span><span class="al-author-delim">; </span><span
                class="wi-fullname brand-fg"><a href="/searchresults?author=Harlan+M.+Krumholtz&amp;q=Harlan+M.+Krumholtz" rel="nofollow" target="_blank">Harlan M.&nbsp;Krumholtz,&nbsp;MD, SM<sup>10</sup></a></span><span class="al-author-delim">;
              </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Kathy+Rowan&amp;q=Kathy+Rowan" rel="nofollow" target="_blank">Kathy&nbsp;Rowan,&nbsp;PhD<sup>11,12</sup></a></span><span class="al-author-delim">; </span><span
                class="wi-fullname brand-fg"><a href="/searchresults?author=Amy+P.+Abernethy&amp;q=Amy+P.+Abernethy" rel="nofollow" target="_blank">Amy P.&nbsp;Abernethy,&nbsp;MD, PhD<sup>13</sup></a></span><span class="al-author-delim">; </span>for
              the JAMA Summit on Clinical Trials Participants<sup></sup></span>
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                  <div class="meta-author-name"><sup>1</sup>Verily Life Sciences, South San Francisco, California</div>
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                  <div class="meta-author-name"><sup>2</sup>Center for Biostatistics &amp; Qualitative Methodology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania</div>
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                  <div class="meta-author-name"><sup>3</sup>Bakar Computational Health Sciences Institute, University of California, San Francisco</div>
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                  <div class="meta-author-name"><sup>4</sup>Center for Data-Driven Insights and Innovation, University of California Health, Oakland</div>
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                  <div class="meta-author-name"><sup>5</sup>Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada</div>
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                  <div class="meta-author-name"><sup>6</sup>Departments of Surgery and Radiology and Institute for Health Policy Studies, University of California, San Francisco</div>
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                  <div class="meta-author-name"><sup>7</sup>Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia</div>
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                  <div class="meta-author-name"><sup>8</sup>Biogen, Boston, Massachusetts</div>
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                  <div class="meta-author-name"><sup>9</sup>Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland</div>
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                  <div class="meta-author-name"><sup>10</sup>Yale University School of Medicine, New Haven, Connecticut</div>
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                  <div class="meta-author-name"><sup>11</sup>National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research Programme, London, United Kingdom</div>
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                  <div class="meta-author-name"><sup>12</sup>Intensive Care National Audit &amp; Research Centre (ICNARC), London, United Kingdom</div>
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                  <div class="meta-author-name"><sup>13</sup>Highlander Health, Dallas, Texas</div>
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            <span class="meta-citation-journal-name">JAMA. </span><span class="meta-citation"> Published online August 5, 2024. doi:10.1001/jama.2024.0268</span>
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              <p><strong>Importance</strong>&nbsp; <span>The 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.</span></p>
              <p><strong>Observations</strong>&nbsp; <span>Clinical 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.</span></p>
              <p><strong>Conclusions and Relevance</strong>&nbsp; <span>We 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.</span></p>
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                                <legend id="captions-background-vjs_video_3_component_549">Text Background</legend><span class="vjs-bg-color"><label id="captions-background-color-vjs_video_3_component_549" class="vjs-label"
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Black">Black</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-White">White</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Red">Red</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Green">Green</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Blue">Blue</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Yellow">Yellow</option>
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                                      aria-labelledby="captions-background-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549 captions-background-color-vjs_video_3_component_549-Magenta">Magenta</option>
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Special Communication
Integrating Clinical Trials and Practice
August 5, 2024


MODERNIZING THE DATA INFRASTRUCTURE FOR CLINICAL RESEARCH TO MEET EVOLVING
DEMANDS FOR EVIDENCE

Joseph B. Franklin, JD, PhD1; Caroline Marra, PhD1; Kaleab Z. Abebe, PhD2; et al
Atul J. Butte, MD, PhD3,4; Deborah J. Cook, MD5; Laura Esserman, MD, MBA6; Lee
A. Fleisher, MD7; Cynthia I. Grossman, PhD8; Nancy E. Kass, ScD9; Harlan
M. Krumholtz, MD, SM10; Kathy Rowan, PhD11,12; Amy P. Abernethy, MD, PhD13; for
the JAMA Summit on Clinical Trials Participants
Author Affiliations Article Information
 * 1Verily Life Sciences, South San Francisco, California
 * 2Center for Biostatistics & Qualitative Methodology, University of Pittsburgh
   School of Medicine, Pittsburgh, Pennsylvania
 * 3Bakar Computational Health Sciences Institute, University of California, San
   Francisco
 * 4Center for Data-Driven Insights and Innovation, University of California
   Health, Oakland
 * 5Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
 * 6Departments of Surgery and Radiology and Institute for Health Policy
   Studies, University of California, San Francisco
 * 7Anesthesiology and Critical Care, University of Pennsylvania Perelman School
   of Medicine, Philadelphia
 * 8Biogen, Boston, Massachusetts
 * 9Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
 * 10Yale University School of Medicine, New Haven, Connecticut
 * 11National Institute for Health and Care Research (NIHR) Health and Social
   Care Delivery Research Programme, London, United Kingdom
 * 12Intensive Care National Audit & Research Centre (ICNARC), London, United
   Kingdom
 * 13Highlander Health, Dallas, Texas

JAMA. Published online August 5, 2024. doi:10.1001/jama.2024.0268

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Envisioning a Path Forward for Clinical Trials—JAMA Summit Keynote Presentation
by Amy P. Abernethy, MD, PhD
Full Text
Abstract

Importance  The 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.

Observations  Clinical 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 Relevance  We 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.



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Franklin JB, Marra C, Abebe KZ, et al. Modernizing the Data Infrastructure for
Clinical Research to Meet Evolving Demands for Evidence. JAMA. Published online
August 05, 2024. doi:10.1001/jama.2024.0268

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