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<article xmlns:xlink="http://www.w3.org/1999/xlink" article-type="review-article" dtd-version="2.0">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMIR</journal-id>
      <journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id>
      <journal-title>Journal of Medical Internet Research</journal-title>
      <issn pub-type="epub">1438-8871</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v22i3e17026</article-id>
      <article-id pub-id-type="pmid">32191214</article-id>
      <article-id pub-id-type="doi">10.2196/17026</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Review</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Review</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Eysenbach</surname>
            <given-names>Gunther</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Wyatt</surname>
            <given-names>David</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Choi</surname>
            <given-names>Sung</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author" equal-contrib="yes">
          <name name-style="western">
            <surname>Platt</surname>
            <given-names>Jodyn E</given-names>
          </name>
          <degrees>MPH, PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-4902-4903</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author" corresp="yes" equal-contrib="yes">
          <name name-style="western">
            <surname>Raj</surname>
            <given-names>Minakshi</given-names>
          </name>
          <degrees>MPH</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <address>
            <institution>Department of Health Management and Policy</institution>
            <institution>University of Michigan School of Public Health</institution>
            <addr-line>1420 Washington Heights</addr-line>
            <addr-line>Ann Arbor, MI, 48109</addr-line>
            <country>United States</country>
            <phone>1 3155593112</phone>
            <email>miraj@umich.edu</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-1457-7850</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author" equal-contrib="yes">
          <name name-style="western">
            <surname>Wienroth</surname>
            <given-names>Matthias</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff3" ref-type="aff">3</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-9722-3918</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Department of Learning Health Sciences</institution>
        <institution>University of Michigan Medical School</institution>
        <addr-line>Ann Arbor, MI</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Department of Health Management and Policy</institution>
        <institution>University of Michigan School of Public Health</institution>
        <addr-line>Ann Arbor, MI</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution>School of Geography, Politics &#38; Sociology</institution>
        <institution>Newcastle University</institution>
        <addr-line>Newcastle upon Tyne</addr-line>
        <country>United Kingdom</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Minakshi Raj <email>miraj@umich.edu</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <month>3</month>
        <year>2020</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>19</day>
        <month>3</month>
        <year>2020</year>
      </pub-date>
      <volume>22</volume>
      <issue>3</issue>
      <elocation-id>e17026</elocation-id>
      <history>
        <date date-type="received">
          <day>12</day>
          <month>11</month>
          <year>2019</year>
        </date>
        <date date-type="rev-request">
          <day>21</day>
          <month>12</month>
          <year>2019</year>
        </date>
        <date date-type="rev-recd">
          <day>30</day>
          <month>12</month>
          <year>2019</year>
        </date>
        <date date-type="accepted">
          <day>31</day>
          <month>12</month>
          <year>2019</year>
        </date>
      </history>
      <copyright-statement>©Jodyn E Platt, Minakshi Raj, Matthias Wienroth. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.03.2020.</copyright-statement>
      <copyright-year>2020</copyright-year>
      <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
        <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="http://www.jmir.org/2020/3/e17026/" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>In the past decade, Lynn Etheredge presented a vision for the Learning Health System (LHS) as an opportunity for increasing the value of health care via rapid learning from data and immediate translation to practice and policy. An LHS is defined in the literature as a system that seeks to continuously generate and apply evidence, innovation, quality, and value in health care.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>This review aimed to examine themes in the literature and rhetoric on the LHS in the past decade to understand efforts to realize the LHS in practice and to identify gaps and opportunities to continue to take the LHS forward.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We conducted a thematic analysis in 2018 to analyze progress and opportunities over time as compared with the initial <italic>Knowledge Gaps and Uncertainties</italic> proposed in 2007.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>We found that the literature on the LHS has increased over the past decade, with most articles focused on theory and implementation; articles have been increasingly concerned with policy.</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>There is a need for attention to understanding the ethical and social implications of the LHS and for exploring opportunities to ensure that these implications are salient in implementation, practice, and policy efforts.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>learning health system</kwd>
        <kwd>review</kwd>
        <kwd>knowledge management</kwd>
        <kwd>bioethics</kwd>
        <kwd>health information exchange</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <sec>
        <title>Background</title>
        <p>In 2007, Lynn Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] envisioned the Learning Health System (LHS) in which he described a system aimed at increasing the value of health care without <italic>draconian</italic> cost cutting. He encouraged facilitating what he called <italic>rapid learning</italic> from new evidence for practice and policy. The publication of this first article to explicitly use the language of the LHS and urge the further consideration of such a system coincided with the adoption of electronic health records (EHRs) in clinical settings aimed at integrating clinical, financial, and administrative data [<xref ref-type="bibr" rid="ref1">1</xref>]. Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] described several opportunities for answering key questions about population health and health care delivery. Addressing these questions would demand a change in institutional (eg, Medicaid) and organizational (eg, in hospitals) leadership and in funding structures to advance the use of health information to improve health [<xref ref-type="bibr" rid="ref1">1</xref>]. Etheredge’s proposals envisioned competitive markets led by health plans and providers who use EHRs; payment linked to evidence-based protocols; and Medicaid and the State Children’s Health Insurance Program as national leaders in EHR adoption and in the use of EHR research databases. National computer-searchable clinical trial databases and national assessments of new technologies would support these efforts. Here, we considered Etheredge’s article [<xref ref-type="bibr" rid="ref1">1</xref>] as an initial conceptualization of gaps and opportunities for future examination and development of the LHS. Many subsequent articles on the LHS topic have cited the guiding principles presented in Etheredge’s article [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>].</p>
        <p>Over a decade has passed since this early vision. Health care provision generates significant amounts of patient and experiential data, and health records, laboratory results, population health surveillance, and patient-generated data, that can be agglomerated and analyzed within health systems. These activities are the result of (1) an increase in health data availability within growing information technology systems via the widening use of patients’ EHRs; (2) efforts to increase the volume of clinical research with patients undertaken at health care facilities; and (3) considerable research and data generation by government-funded and commercial enterprises [<xref ref-type="bibr" rid="ref3">3</xref>-<xref ref-type="bibr" rid="ref8">8</xref>]. Bringing together diverse actors in the health and life sciences context, LHSs aim to gather and analyze differently sourced data to create useful knowledge that is disseminated to all stakeholders, put into practice, and then evaluated [<xref ref-type="bibr" rid="ref9">9</xref>].</p>
        <p>The LHS framework marks a departure from data practices that are governed by the intended use for data, be it research, quality improvement (QI), clinical care, or public health. The aim of LHS is to enable continuously and rapidly operating virtuous cycles of study, feedback, and practice change, regardless of the original intention for data collection; its vision has come to shape the goals of initiatives in the United States, the United Kingdom, and globally [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>]. Examples include the American Society of Clinical Oncology’s CancerLinQ initiative, which offers an emerging large-scale database for an oncology learning community to improve the quality of cancer care [<xref ref-type="bibr" rid="ref10">10</xref>], the CommonWell Health Alliance, which enables querying of treatment data for over 17 million unique individuals [<xref ref-type="bibr" rid="ref11">11</xref>], and the National Institutes of Health <italic>All of Us</italic> research initiative, which seeks to connect genomic, health, and social media data from over 1 million individuals [<xref ref-type="bibr" rid="ref12">12</xref>]. Similar avenues toward large-scale agglomeration, analysis, and sharing of patient health information exist in the United Kingdom, such as the National Health Service–supported data platform, Lambeth DataNet, which provides general physicians and academic researchers with access to data from approximately 350,000 patients [<xref ref-type="bibr" rid="ref13">13</xref>] and the Connected Health Cities initiative [<xref ref-type="bibr" rid="ref14">14</xref>], which is building data stores to support direct care across the North of England region.</p>
      </sec>
      <sec>
        <title>Objectives</title>
        <p>In this review, we aimed to examine the literature and rhetoric on the LHS, identify trends and themes in published efforts undertaken to moving this idea from concept to reality, and assess gaps in the literature that suggest areas for future research and policy considerations that are necessary for moving the LHS forward (<xref rid="figure1" ref-type="fig">Figure 1</xref>).</p>
        <fig id="figure1" position="float">
          <label>Figure 1</label>
          <caption>
            <p>Areas critical to the realization of a learning health system.</p>
          </caption>
          <graphic xlink:href="jmir_v22i3e17026_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Search Strategy</title>
        <p>We conducted a scoping review using search terms “learning health system(s),” “learning health care system(s),” and “learning healthcare system(s)” on PubMed, Web of Science, and Scopus databases to identify peer-reviewed publications. The search was limited to peer-reviewed articles published in the English language between January 2007 and December 2017.</p>
        <p>We identified and included articles published in a variety of clinical contexts, with most articles focusing on the United States and written by US-based authors and some focused on the United Kingdom, India, Sweden, Kenya, and China. Articles describing or examining the LHS from clinical, technical, and ethical perspectives were included. Our initial search yielded 542 articles for review, including USA Institute of Medicine (now USA National Academy of Medicine) proceedings and chapters that informed our search but were not included in the final full analyses.</p>
      </sec>
      <sec>
        <title>Data Extraction and Article Selection</title>
        <p>Following a title and abstract review, we excluded 222 articles. Articles were excluded if they were duplicates, conference proceedings or posters, or not peer reviewed. Results were compared among members of the study team before exclusion. We created a Microsoft Excel spreadsheet charting information from the 320 remaining articles, including (1) article title; (2) year; (3) country; (4) category; (5) concern or focus; (6) field; and (7) number of papers citing the article of interest (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
        <p>Next, we sorted articles by year, identified the top quarter of most cited papers within each year. We used citation data provided by Web of Science and Scopus to determine the number of citations for each article, sorted all included articles in the sample to identify the top quarter, and then compiled a list of these articles. We chose to focus on the most cited papers as representatives of those with the most salient themes to the discourse and scholarship on the LHS. This sorting resulted in 85 articles for our final review, which represents just over 15.7% (85/542) of the total number of articles identified in our initial search (see <xref rid="figure2" ref-type="fig">Figure 2</xref>). The 85 articles were read in full to conduct a more thorough discourse (thematic mapping) analysis that could be compared with the vision laid out in Etheredge’s [<xref ref-type="bibr" rid="ref1">1</xref>] manuscript in 2007, which is described in the section, <italic>Analytical Strategy</italic>.</p>
        <table-wrap position="float" id="table1">
          <label>Table 1</label>
          <caption>
            <p>Summary of abstracted information.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="230"/>
            <col width="770"/>
            <thead>
              <tr valign="top">
                <td>Information documented</td>
                <td>Description</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Article title</td>
                <td>Title of publication</td>
              </tr>
              <tr valign="top">
                <td>Year</td>
                <td>Year of publication</td>
              </tr>
              <tr valign="top">
                <td>Country</td>
                <td>Global context of publication</td>
              </tr>
              <tr valign="top">
                <td>Category</td>
                <td>Preset categories for thematic understanding, including the following:<break/><list list-type="bullet"><list-item><p>Policy (eg, relating to health reform)</p></list-item><list-item><p>Advocacy (eg, encouraging implementation into organizations)</p></list-item><list-item><p>Theory (ie, generating or enhancing LHS<sup>a</sup> frameworks)</p></list-item><list-item><p>Empirical (eg, studies testing infrastructures or hypotheses)</p></list-item><list-item><p>Implementation (ie, evaluating implementation into clinical contexts)</p></list-item><list-item><p>Ethics (ie, introducing or describing ethical perspectives or limitations of the LHS)</p></list-item><list-item><p>General commentary</p></list-item></list></td>
              </tr>
              <tr valign="top">
                <td>Concern and/or Focus</td>
                <td>Information on the primary focus or concern of the article, such as the following:<break/><list list-type="bullet"><list-item><p>Quality improvement</p></list-item><list-item><p>Personalized health care</p></list-item><list-item><p>Evidence-based medicine</p></list-item><list-item><p>Electronic health record</p></list-item><list-item><p>Ethical oversight</p></list-item></list></td>
              </tr>
              <tr valign="top">
                <td>Field</td>
                <td>Information on perspective through which article discusses the LHS, such as the following:<break/><list list-type="bullet"><list-item><p>Clinical context (eg, oncology and surgery)</p></list-item><list-item><p>Professional context (eg, nursing)</p></list-item><list-item><p>Discourse context (eg, medical informatics, research, and ethics)</p></list-item><list-item><p>Health care system (ie, articles discussing the LHS across a larger scope)</p></list-item></list></td>
              </tr>
              <tr valign="top">
                <td>Number of citations</td>
                <td>Number of times each article has been cited according to Web of Science or Scopus</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table1fn1">
              <p><sup>a</sup>LHS: Learning Health System.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <fig id="figure2" position="float">
          <label>Figure 2</label>
          <caption>
            <p>Summary of search strategy and themes.</p>
          </caption>
          <graphic xlink:href="jmir_v22i3e17026_fig2.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
      <sec>
        <title>Analytical Strategy</title>
        <p>The analysis presented in this paper draws on both quantitative and qualitative approaches. First, we identified historical trends in the LHS discourse by quantitatively assessing the number of articles published on the LHS over time. We then evaluated article categories over time and assessed the variety of clinical domains that have integrated the LHS discourse for the 85 articles selected for review.</p>
        <p>Next, we performed a thematic mapping analysis to qualitatively examine the variety of ways in which articles define the LHS. This is a method for extracting, analyzing, and reporting themes in data, such as from interviews or texts [<xref ref-type="bibr" rid="ref15">15</xref>]. Themes describe textual data that are grouped around a main issue [<xref ref-type="bibr" rid="ref16">16</xref>] and are recurrent and systematic [<xref ref-type="bibr" rid="ref17">17</xref>]. Moreover, themes emerge from the data and can be refined into levels or subthemes that reflect on the theme [<xref ref-type="bibr" rid="ref18">18</xref>]. In this review, we initially identified broad themes that emerged from the articles. These themes were then refined into subthemes. Finally, we compared the qualitative findings from our literature review with the vision developed by Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] in 2007 to assess the extent to which these initiatives have been undertaken and discussed according to the literature over the past decade and to identify areas for continued effort. One member of the study team coded the 85 articles using the MAXQDA software and shared codes and code relation matrices with the other members to ensure agreement. The study team held meetings every 2 weeks to discuss emerging themes and subthemes, thus arriving at the final list iteratively and collaboratively.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <sec>
        <title>Defining the Learning Health System</title>
        <p>Articles in our final sample most commonly draw upon the Institute of Medicine’s (now the National Academy for Medicine) ambitious and encompassing definition describing LHSs as those that: <italic>generate and apply the best evidence for the collaborative health care</italic> <italic>choices of each patient and provider;…drive the process of discovery as a natural outgrowth of patient care; and ensure innovation, quality, safety, and value in health care</italic> [<xref ref-type="bibr" rid="ref19">19</xref>].</p>
        <p>These articles describe the LHS as an avenue for delivering more targeted, safe, and effective health care by using information from the experiences and treatment of patients to inform decision making and subsequent care in real time [<xref ref-type="bibr" rid="ref20">20</xref>,<xref ref-type="bibr" rid="ref21">21</xref>]. A central ambition, as well as a vehicle for the aspirations of the LHS, is the notion of <italic>learning</italic>. Importantly, learning itself is considered the transfer of knowledge through formal curricula (eg, during medical training) and a transfer of culture, attitudes, and beliefs in ways that can be implemented in research as well as practice when combined with QI methods [<xref ref-type="bibr" rid="ref21">21</xref>,<xref ref-type="bibr" rid="ref22">22</xref>]. For example, Faden et al [<xref ref-type="bibr" rid="ref23">23</xref>] describe learning as a process including research, information gleaned from QI efforts, and comparative effectiveness research, culminating in improved practice [<xref ref-type="bibr" rid="ref24">24</xref>]. In this way, QI is described as a critical stepping stone to learning, which depends on research and also has the potential to bridge the traditional gap between research and practice to inform the goals of an LHS [<xref ref-type="bibr" rid="ref24">24</xref>].</p>
        <p>Some articles refer to the LHS more specifically, as a <italic>rapid learning health system</italic> to emphasize the celerity—eg, <italic>real-time</italic> delivery—with which evidence-based medicine can be used to determine health care decisions [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref25">25</xref>]. A system, in this context, is characterized as requiring a coherent, flexible organizational structure, with data maintained in a repository until needed for a particular purpose [<xref ref-type="bibr" rid="ref26">26</xref>]. In addition, mechanisms are in place to ensure that data are usable by all entities within the system and that they are transferred appropriately, safely, and ethically. Data originate from clinical practice, research, participation, and inquiry provided by organizational leaders, physicians, researchers, patients, and research participants [<xref ref-type="bibr" rid="ref26">26</xref>]. Although some publications in our sample offer a discussion of the LHS as a large-scale system spanning borders, others implement, evaluate, or present challenges on the system at a local or regional scale.</p>
      </sec>
      <sec>
        <title>Quantitative Trends in the Learning Health System Discourse</title>
        <p>Our review indicated historical trends in the LHS discourse, with a particular surge in articles published between 2013 and 2017. This trend, we noticed in the broader literature search, is consistent with the trends in articles we selected for review (<xref rid="figure3" ref-type="fig">Figure 3</xref>).</p>
        <p>Our review resulted in the selection of 85 articles published between 2007 and 2017. Most of the 85 articles included in our review were published in 2014, and the articles cited most were published in 2010 (132 citations); 2007 (116 citations); and 2013 (102 citations).</p>
        <fig id="figure3" position="float">
          <label>Figure 3</label>
          <caption>
            <p>Frequency of articles published by year (n=542).</p>
          </caption>
          <graphic xlink:href="jmir_v22i3e17026_fig3.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
      <sec>
        <title>Trends in Categories of Articles</title>
        <p>Following the categorization of each paper according to its primary concerns, we found that a striking majority of articles are concerned with theory (n=33), followed by implementation (n=23), commentary (n=18), advocacy, ie, promoting the idea or driving the demand for an LHS (n=12), empirical data (n=11), ethics (n=8), and policy (n=7). Articles published in 2007 were exclusively theory and/or advocacy; in 2010, articles were published across a broader variety of categories. However, articles predominantly discussing ethics in our sample were only published in 2013; similarly, policy articles were only published in 2007 and 2014 (<xref rid="figure4" ref-type="fig">Figure 4</xref>).</p>
        <fig id="figure4" position="float">
          <label>Figure 4</label>
          <caption>
            <p>Trends in article categories among frequently cited articles based on review of frequently cited articles (n=85).</p>
          </caption>
          <graphic xlink:href="jmir_v22i3e17026_fig4.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <p>Most of the implementation and empirical articles discuss the LHS in the context of oncology (n=10) [<xref ref-type="bibr" rid="ref27">27</xref>-<xref ref-type="bibr" rid="ref36">36</xref>]; however, other contexts include primary care (n=3) [<xref ref-type="bibr" rid="ref37">37</xref>,<xref ref-type="bibr" rid="ref38">38</xref>], surgery (n=3) [<xref ref-type="bibr" rid="ref20">20</xref>,<xref ref-type="bibr" rid="ref39">39</xref>], and pediatrics (n=7) as well as others. Some articles, such as commentary articles, exemplify clinical contexts such as pediatrics (n=3) and oncology (n=3) but are not exclusively concerned with a particular clinical context. In <xref ref-type="table" rid="table2">Table 2</xref>, we summarize the clinical contexts of articles included in our review, including the initiative of interest in each article. Articles were classified based on the objective of the literature—ie, (1) whether the article discusses or is concerned with the use of the initiative for QI, (2) whether the article discusses or is concerned with the use of the initiative for research, and/or (3) whether the article specifically evaluates the initiative with regard to improving quality or research. Most of the articles are classified as being concerned with QI, eg, around EHR point-of-care diagnostic capabilities or in clinical guidelines and subsequent process measures via networks through which information is shared. Some of these articles frame research as a stepping stone for improving point-of-care quality; however, their ultimate objective is not to improve research itself. Some studies evaluate the efficacy of QI initiatives. Fewer articles (n=9) are concerned with initiatives seeking to improve research, eg, through the development of clinical trials, or by considering the limitations in the processes through which data are collected in research used to inform practice (eg, informed consent).</p>
        <table-wrap position="float" id="table2">
          <label>Table 2</label>
          <caption>
            <p>Clinical context of articles.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="30"/>
            <col width="30"/>
            <col width="400"/>
            <col width="430"/>
            <col width="110"/>
            <thead>
              <tr valign="top">
                <td colspan="3">Article type, clinical context, source</td>
                <td>Name or focus of initiative</td>
                <td>Classification</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td colspan="5">
                  <italic>
                    <bold>Implementation</bold>
                  </italic>
                  <sup>a</sup>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Oncology</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Buetow and Niederhuber [<xref ref-type="bibr" rid="ref29">29</xref>]</td>
                <td>Cancer Biomedical Informatics Grid</td>
                <td>QI<sup>b</sup></td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Abernathy et al [<xref ref-type="bibr" rid="ref28">28</xref>]</td>
                <td>Rapid learning health care</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Elson et al [<xref ref-type="bibr" rid="ref27">27</xref>]</td>
                <td>Athena Breast Health Network</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Sledge et al [<xref ref-type="bibr" rid="ref30">30</xref>]</td>
                <td>CancerLinQ</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Schilsky et al [<xref ref-type="bibr" rid="ref31">31</xref>]</td>
                <td>CancerLinQ</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Abernathy et al [<xref ref-type="bibr" rid="ref32">32</xref>]</td>
                <td>Innovation in oncology</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Primary care</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Delaney et al [<xref ref-type="bibr" rid="ref37">37</xref>]</td>
                <td>Electronic Primary Care Research Network</td>
                <td>E<sup>c</sup></td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Peterson et al [<xref ref-type="bibr" rid="ref38">38</xref>]</td>
                <td>Practice-based Research Networks</td>
                <td>E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Surgery</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Kwon et al [<xref ref-type="bibr" rid="ref39">39</xref>]</td>
                <td>Surgical Care and Outcomes Assessment Program</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Flum et al [<xref ref-type="bibr" rid="ref20">20</xref>]</td>
                <td>Comparative Effectiveness Research Translation Network</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Pediatrics</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Forrest et al [<xref ref-type="bibr" rid="ref40">40</xref>]</td>
                <td>PEDSnet consortium of 8 children’s hospitals</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Forrest et al [<xref ref-type="bibr" rid="ref41">41</xref>]</td>
                <td>ICN<sup>d</sup></td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Endocrinology</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Fiore et al [<xref ref-type="bibr" rid="ref42">42</xref>]</td>
                <td>Point-of-care clinical trial</td>
                <td>R<sup>e</sup>/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Cardiology</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Califf and Sugarman [<xref ref-type="bibr" rid="ref43">43</xref>]<break/>  <break/>  </td>
                <td>Pragmatic clinical trials<break/>  <break/>  </td>
                <td>R<break/>  <break/>  </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Maddox et al [<xref ref-type="bibr" rid="ref44">44</xref>]</td>
                <td>Veterans Administration Clinical Assessment, Reporting, and Tracking program</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Intensive Care Unit</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Warner et al [<xref ref-type="bibr" rid="ref45">45</xref>]</td>
                <td>Temporal phenotype data via an EHR<sup>f</sup></td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Gastro-enterology</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Forrest et al [<xref ref-type="bibr" rid="ref41">41</xref>]</td>
                <td>ICN</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Public Health Departments</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Klann et al [<xref ref-type="bibr" rid="ref46">46</xref>]</td>
                <td>Query Health</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Health systems</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Greene et al [<xref ref-type="bibr" rid="ref47">47</xref>]</td>
                <td>Rapid learning health system</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Harper [<xref ref-type="bibr" rid="ref48">48</xref>]</td>
                <td>Clinical Demand Index</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Weng et al [<xref ref-type="bibr" rid="ref49">49</xref>]</td>
                <td>Integrated Model for Patient Care and Clinical Trials</td>
                <td>R/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Forrest et al [<xref ref-type="bibr" rid="ref40">40</xref>]</td>
                <td>PEDSnet consortium of 8 children’s hospitals</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>McGlynn et al [<xref ref-type="bibr" rid="ref50">50</xref>]</td>
                <td>Patient Outcomes Research to Advance Learning network</td>
                <td>R</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Mandl et al [<xref ref-type="bibr" rid="ref51">51</xref>]</td>
                <td>Scalable Collaborative Infrastructure for a Learning Healthcare System</td>
                <td>R/E</td>
              </tr>
              <tr valign="top">
                <td colspan="5">
                  <italic>
                    <bold>Empirical</bold>
                  </italic>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Pediatrics</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Lannon and Peterson [<xref ref-type="bibr" rid="ref52">52</xref>]</td>
                <td>Pediatric Collaborative Improvement Networks</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Kelley et al [<xref ref-type="bibr" rid="ref53">53</xref>]</td>
                <td>Examining attitudes toward research</td>
                <td>R</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Oncology</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Spinks et al [<xref ref-type="bibr" rid="ref33">33</xref>]</td>
                <td>Not applicable</td>
                <td>Not applicable</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Surgery</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Pingleton et al [<xref ref-type="bibr" rid="ref21">21</xref>]</td>
                <td>Evaluating quality and patient safety curricula</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Nephrology</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Kelley et al [<xref ref-type="bibr" rid="ref53">53</xref>]</td>
                <td>Not applicable</td>
                <td>Not applicable</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="2">
                  <bold>Primary care and/or internal medicine</bold>
                </td>
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Pingleton et al [<xref ref-type="bibr" rid="ref21">21</xref>]</td>
                <td>Evaluating quality and patient safety curricula</td>
                <td>QI/E</td>
              </tr>
              <tr valign="top">
                <td colspan="5">
                  <italic>
                    <bold>General</bold>
                  </italic>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Pediatrics</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Clancy et al [<xref ref-type="bibr" rid="ref22">22</xref>]</td>
                <td>Collaborative Improvement Networks</td>
                <td>QI/R</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Gardner and Kelleher [<xref ref-type="bibr" rid="ref54">54</xref>]</td>
                <td>LHS<sup>g</sup> for Pediatrics</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Kahn et al [<xref ref-type="bibr" rid="ref55">55</xref>]</td>
                <td>Common Pediatric Research Terminology</td>
                <td>R/E</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td colspan="4">
                  <bold>Oncology</bold>
                </td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Feeley et al [<xref ref-type="bibr" rid="ref34">34</xref>]</td>
                <td>Health Information Technology to improve quality of cancer care</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Shaikh et al [<xref ref-type="bibr" rid="ref35">35</xref>]</td>
                <td>Collaborative Biomedicine</td>
                <td>QI</td>
              </tr>
              <tr valign="top">
                <td>
                  <break/>
                </td>
                <td>
                  <break/>
                </td>
                <td>Shah et al [<xref ref-type="bibr" rid="ref36">36</xref>]</td>
                <td>CancerLinQ</td>
                <td>R/E</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table2fn1">
              <p><sup>a</sup>Italicized categories describe concern or focus of article.</p>
            </fn>
            <fn id="table2fn2">
              <p><sup>b</sup>QI: quality improvement.</p>
            </fn>
            <fn id="table2fn3">
              <p><sup>c</sup>E: evaluation.</p>
            </fn>
            <fn id="table2fn4">
              <p><sup>d</sup>ICN: ImproveCareNow.</p>
            </fn>
            <fn id="table2fn5">
              <p><sup>e</sup>R: research.</p>
            </fn>
            <fn id="table2fn6">
              <p><sup>f</sup>EHR: electronic health record.</p>
            </fn>
            <fn id="table2fn7">
              <p><sup>g</sup>LHS: Learning Health System</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Themes</title>
        <p>Our thematic analysis revealed five broad themes across the 85 articles we reviewed: (1) culture, ie, the environment or environmental change required to support the LHS; (2) innovations, including new tools or ideas needed or being developed to realize the vision of an LHS; (3) data infrastructure; and (4) ethical considerations generally framed as moral imperatives or in terms of principles such as privacy and efficiency [<xref ref-type="bibr" rid="ref15">15</xref>]. Although some articles present evidence or discussion on multiple themes, others tend to focus exclusively on one theme, eg, articles commenting on ethical aspects. Furthermore, articles focusing on technical or research aspects rarely comment on social or ethical considerations of the LHS.</p>
        <sec>
          <title>Culture</title>
          <p>Most articles (n=81) set clear expectations and priorities for advancing the LHS and achieving its goals. Culture, describing the way in which research and clinical care are considered and how they contribute to the vision or mission of the LHS, is central to enhancing the system. For example, academic health centers are discussed for balancing high-quality teaching with attention to increasing customer service, productivity, and research missions and reducing knowledge gaps for evidence-based medicine [<xref ref-type="bibr" rid="ref56">56</xref>]. In the reviewed papers, aspects of culture included (1) organizational culture; (2) research and practice; and (3) establishing a framework for health, ie, establishing the boundaries of research, practice, and QI while ensuring appropriate oversight of risks and benefits. These aspects of culture align with the initial priorities set by Etheredge in 2007, including and extending beyond leadership and collaboration, to include actionable steps such as professional education [<xref ref-type="bibr" rid="ref1">1</xref>].</p>
        </sec>
        <sec>
          <title>Innovations, Tools, and Ideas</title>
          <p>Most of the reviewed articles (n=77) propose ideas and tools or evaluate innovations that are anticipated to contribute to achieving an LHS by (1) enhancing existing research and (2) envisioning, developing, and enhancing care methodologies to ultimately be implemented in care. For example, the Patient Outcomes Research to Advance Learning network is a research network studying the effectiveness of various approaches to diagnosis, treatment, and management, which could create cohorts of patients with common diagnoses to conduct large-scale comparative effectiveness research to accomplish its goals of assisting patients, caregivers, and physicians in making informed decisions [<xref ref-type="bibr" rid="ref50">50</xref>]. Other tools, in contrast, are concerned with enhancing methodologies for clinical practice. For example, ImproveCareNow (ICN) is a network aiming to transform the health of children with Crohn disease and ulcerative colitis through a collaboration of pediatric gastroenterology practices working together to develop and enhance care methodologies [<xref ref-type="bibr" rid="ref57">57</xref>]. The innovations, tools, and ideas that have been developed since 2007 seem particularly responsive to Etheredge’s envisioning of moving toward an LHS via the EHR, predictive modeling, and software development [<xref ref-type="bibr" rid="ref1">1</xref>].</p>
        </sec>
        <sec>
          <title>Data Infrastructure</title>
          <p>Data infrastructure emerges as a key theme in articles (n=67), with authors discussing a variety of technical avenues for pursuing and/or achieving the LHS. Given that the LHS framework is heavily reliant on an emerging technical infrastructure, the significance of this theme is not surprising. Publications are concerned with (1) networks and platforms; (2) expanding study and data reliability and/or validity; and (3), particularly, the EHR as a valuable resource. In 2007, Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] discussed the Cancer Research Network, the Vaccine Safety Datalink network, and the American Medical Group Association as exemplars of data infrastructure progressing toward an LHS. A decade later, the literature is discussing myriad networks and platforms such as the National Patient-Centered Clinical Research Network and the data-sharing platform, PopMedNet [<xref ref-type="bibr" rid="ref46">46</xref>,<xref ref-type="bibr" rid="ref50">50</xref>].</p>
          <p>The literature argues that these networks and platforms rely on robust participation to build reliability and validity; however, reported participation is limited owing to inadequate sampling, limited availability of clinical information in datasets, lack of rigorous inclusion and/or exclusion criteria resulting in confounders, and resulting issues around generalizability of findings [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>]. Furthermore, the quality of data suffers because of issues such as inconsistent terminology and the use of statistical techniques that are not advanced enough for complex observational data aggregated from the EHR [<xref ref-type="bibr" rid="ref37">37</xref>,<xref ref-type="bibr" rid="ref61">61</xref>]. However, articles regard the EHR as a valuable resource with the capacity to capture, communicate, aggregate, store, and analyze large pools of data for real-time clinician decision support and, broadly, for establishing a nationwide LHS [<xref ref-type="bibr" rid="ref26">26</xref>,<xref ref-type="bibr" rid="ref30">30</xref>,<xref ref-type="bibr" rid="ref48">48</xref>]. Indeed, articles address limitations of the EHR spanning from the practice of individual teams building their own data repositories to the need for manual data aggregation [<xref ref-type="bibr" rid="ref25">25</xref>,<xref ref-type="bibr" rid="ref39">39</xref>]. However, articles urge enhancing data interoperability and tailoring the technology to specific clinical contexts such as oncology to ensure effective use of the EHR [<xref ref-type="bibr" rid="ref28">28</xref>].</p>
        </sec>
        <sec>
          <title>Ethics</title>
          <p>According to Faden et al [<xref ref-type="bibr" rid="ref23">23</xref>], the development of an LHS relies heavily on altruism and the understanding that although participating in research may not offer personal therapeutic or curative benefits, what is inherent to clinical research is the potential for large-scale benefits to society by filling knowledge gaps and enhancing care methods. Only eight papers focus on ethics, and most of these are part of the same special issue of the Hastings Center Report in 2013 [<xref ref-type="bibr" rid="ref24">24</xref>,<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]. Yet, many other papers—just under half of the reviewed papers (n=39)—discuss at least some ethical and/or social aspects of the LHS, including what is often posited as <italic>challenges</italic> in combining research and clinical frameworks and cultures. Specifically, articles address (1) efficacy and patient safety in research and practice, (2) the moral imperative on patients to participate in research, (3) effects of participation, eg, on privacy and the lack of guaranteed therapeutic benefits in research studies, and (4) questions of social justice (ie, fair subject selection and a just distribution of research benefits and burdens) [<xref ref-type="bibr" rid="ref23">23</xref>,<xref ref-type="bibr" rid="ref24">24</xref>,<xref ref-type="bibr" rid="ref43">43</xref>,<xref ref-type="bibr" rid="ref63">63</xref>]. For example, patients who are actively undergoing treatment may be more willing to participate in research as a result of their current experience of benefiting from treatment and scientific knowledge. However, as participants in an LHS, EHRs and other data sources will be used during, and after, specific instances of being a patient. Notions of benefit and risk are likely to change over time, both for a specific individual and within the context of a given institution. Ongoing conversations about the risks and benefits of participation, and what the idiom <italic>research</italic> refers to, will be critical to achieving adequate engagement and ensuring that willingness to participate is not confounded with a need for care [<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref65">65</xref>]. Furthermore, potential users of health care services may anticipate receiving further and/or advanced treatment for long-term and rare diseases. For example, in the context of the United States, health care is not free of charge and features some of the highest costs globally for health services and long-term care. A question of social justice would be how data from patients are used for the health system to ultimately give back to patients who are charged for services and whose health and associated data may be turned into monetizable assets by health care providers.</p>
          <p>It is a positive sign that such a significant number of articles in the sample engage with ethical and social aspects of the LHS. However, this engagement still focuses primarily on efficacy and safety and on espousing a moral duty for physicians, clinicians, and patients to participate in the LHS. In his 2007 article, Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] discusses the ethical implications of an LHS, particularly in terms of responsibility, gaps in our understanding of comparative benefits and risks of clinical research, and prescriptions across minority and special needs groups, and raises issues of patient confidentiality. The literature, to date, concerned with ethical implications of an LHS, though sparse, continues to prioritize these gaps. Furthermore, it urges the consideration of participation and recognizes some of these issues as relating to social justice more broadly.</p>
        </sec>
      </sec>
      <sec>
        <title>Progress and Opportunities Over the Past Decade</title>
        <p>Over the past decade, there has been tremendous movement with regard to the technical side of LHS infrastructure including the EHR, which is discussed in much of the literature as a valuable resource for research, clinical care, and the translation from one to the other [<xref ref-type="bibr" rid="ref66">66</xref>,<xref ref-type="bibr" rid="ref67">67</xref>]. Much of the literature in our review focuses on using EHRs for QI, signaling progress in the use and impact of health information technology on moving toward the vision of the LHS. However, our findings suggested a lack of attention to ethical considerations, eg, social justice issues, to intersections of different types of data that might enter potentially large-scale data systems such as the LHS (health, welfare, education, criminal justice, etc), and to the role, recruitment, and retention of participants in research, and equitable distribution of benefits. These aspects of health care and research have been discussed in other bodies of health literature but do not seem to have been adapted widely for and by the LHS discourse. There is also a need for further consideration of leadership, collaboration, and responsibilities of various entities within the health care system. Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] cites Medicaid as a key leader of the LHS; for leaders to emerge, it is essential to identify, understand, and map the responsibilities of LHS leaders and identify how other stakeholders such as providers, patients, and hospitals conceptualize the LHS as a sociotechnical system.</p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Principal Findings</title>
        <p>Since Etheredge’s paper [<xref ref-type="bibr" rid="ref1">1</xref>] and the US Institute of Medicine’s roundtable report in 2007 [<xref ref-type="bibr" rid="ref2">2</xref>], more than 500 academic papers have been published discussing the LHS, with most of these emerging since 2014. This work predominantly cites empirical research describing technical developments and analytical capacity. However, LHS infrastructure concepts navigate complex systems of policy, ethics, networks, and processes in local clinical care and research settings as well as in the global consortia. Although the literature is expanding with the rate of technological innovation, an empirically based ethical analysis of large health data systems, including the deliberation of their ethical management and sociotechnical engagements, further requires considerable attention.</p>
        <p>Articles in our review generally suggest an engagement with the LHS discourse by exploring or evaluating tools and innovations to bring the LHS framework to fruition in research and practice; by examining technical infrastructures to test the process of aggregating data from research to implement findings into practice; and by evaluating challenges and subsequent priorities to facilitate the LHS across teams and institutions. Our sample suggests that the LHS framework is considered suitable for, and is in parts already utilized across, a variety of institutions and clinical contexts, albeit not anywhere near the capacity of what the LHS framework suggests might be possible. The publication numbers themselves are indicative of the desire and effort to present, develop, and apply the LHS in action as research, technical, and clinical teams collaborate and propose new models. However, while some articles test the LHS framework as an avenue to pursuing QI, others consider the LHS a framework for implementable research. There is a need to examine whether, in applying an LHS model, a boundary exists between QI and research, and, further, the terms and implications of such a boundary. At present, the expectations and requirements for informed consent, notification, return of research results, risk assessment, privacy, and confidentiality are vastly different for research vs QI.</p>
        <p>Future studies should examine stakeholder perceptions of the boundaries between QI and research, engaging patients, healthy participants, researchers, clinicians, and technical designers involved in LHS teams to understand the extent to which they distinguish between the two. Importantly, the ways that the LHS might be utilized need to be clarified to develop appropriate and effective governance frameworks.</p>
        <p>Our review revealed a number of trends and themes in the LHS discourse that may inform avenues for further deliberation to contribute to a more robust discussion of the LHS. For example, the relatively small number of articles comprehensively engaging with its social, ethical, and governance aspects is surprising. This may suggest limited discussion of the LHS as a concept in the social sciences and humanities and an opportunity for further examination of aspects and implications of the LHS from these perspectives—ongoing discussions in bodies of social science scholarship around health and data would provide fruitful platforms for further discussion. The LHS relies on the collaboration of various stakeholders in research, clinical, and technical arenas to utilize technology for the improvement of patient health, in fact forming an ecosystem of interrelated and linked activities. One might expect that these interpersonal interactions as well as interactions between stakeholders and technologies would prompt further discussion of the social and ethical concerns that might arise or of the social and societal enablers, drivers, and impacts of the LHS. For example, the intersection between the patient duty to participate and the technical challenge of maintaining privacy, including data security, could be examined further to understand whether there are nuances to when patients may be more or less willing to share data across a network and to understand what the processes for decision making and data sharing need to look like to be compatible with data subjects’ needs [<xref ref-type="bibr" rid="ref23">23</xref>].</p>
        <p>To date, the LHS has primarily focused on the technical access between different users (via EHRs) and across local networks; this is reflected in the articles in our sample as well, suggesting a need for tests of implementation at a larger scale. ICN is an example of a regional-level network; there is the possibility of testing similar networks at a global level. It is possible that owing to our criteria of including only articles written in English, our sample excluded global-level examples of LHSs; however, it is unclear whether there are current collaborations between global settings and whether this is a part of the current LHS vision. We do know that aspects of types of LHSs—such as data governance in health care research—are being discussed in other bodies of the literature but that scholarship either does not refer to the LHS or does not take a systemic approach to health research and care.</p>
      </sec>
      <sec>
        <title>Implications for Future Research, Practice, and Policy</title>
        <p>Our review suggests that although some knowledge gaps and uncertainties presented by Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] have received consideration over the past decade, significant gaps persist, presenting opportunities for future research and policy (<xref ref-type="table" rid="table3">Table 3</xref>).</p>
        <table-wrap position="float" id="table3">
          <label>Table 3</label>
          <caption>
            <p>Progress over the past decade in addressing knowledge gaps and uncertainties.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="180"/>
            <col width="470"/>
            <col width="350"/>
            <thead>
              <tr valign="top">
                <td>Knowledge gaps and uncertainties (Etheredge, 2007) [<xref ref-type="bibr" rid="ref1">1</xref>]</td>
                <td>Perspectives from the literature (2007-2017)</td>
                <td>Areas for considering the way forward</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Diffused responsibility</td>
                <td>Robust discussion of the need for leadership and coordination across various stakeholders, research, policy, and practice. Tools exist for development of new technologies; however, they appear to be largely segregated into those for enhancing research vs practice, leading to disparate regulatory oversight</td>
                <td>Further examination is needed of stakeholder perspectives of funding and responsibility for supporting research. Need for a better understanding of the roles and responsibilities of those involved in research from collection to sharing and implementation</td>
              </tr>
              <tr valign="top">
                <td>Concerns about clinical trials</td>
                <td>The past decade has seen a variety of innovations for enhancing research as well as clinical care, along with the emergence of networks and platforms for trials and studies across various clinical contexts. The literature sees a continued need for clinical trials to support precision medicine but asserts the need for ensuring that participants are well-informed about risks and benefits of participating, and that sampling and distribution of benefits are equitable</td>
                <td>Continued examination of public needs, attitudes, beliefs, and knowledge about participating in research and clinical trials, especially at a systemic level of health research and care data agglomeration and learning cycles</td>
              </tr>
              <tr valign="top">
                <td>Consequences of underinvestment</td>
                <td>The literature suggests that the emergence of networks and platforms, as well as the increasing use of the EHR<sup>a</sup> has facilitated investment in evidence-based research. However, there is a need for ensuring that data are interoperable and meaningful, that studies and data are reliable and valid, and that the public is better able to envision its role in research</td>
                <td>Need for an enhanced design of the EHR to increase interoperability, standardization, and quality of data to ensure that findings are translatable and generalizable. Ensuring adequate regulation of research and informed consent for participants</td>
              </tr>
              <tr valign="top">
                <td>Genetics and genomics-based medicine</td>
                <td>Data quality, reliability, and validity are critical to genetics and genomics-based medicine. The literature primarily discusses a need for ensuring the just and equitable distribution of benefits and minimization of risks</td>
                <td>Sampling must include patient populations beyond the socioeconomic environment of a hospital or region, and rigorous inclusion and exclusion criteria</td>
              </tr>
              <tr valign="top">
                <td>Overall system performance</td>
                <td>The literature extensively discusses the EHR as a resource for improving quality; several articles urge for a consideration of research vs quality improvement. In addition, there is a need for improving and developing curricula in academic medical centers on research and clinical safety and quality</td>
                <td>Moving the LHS<sup>b</sup> forward requires further theoretical consideration of research vs quality improvement. The literature is mixed and defining boundaries will be beneficial to examining the policy and practice implications of rapid learning</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table3fn1">
              <p><sup>a</sup>EHR: electronic health record.</p>
            </fn>
            <fn id="table3fn2">
              <p><sup>b</sup>LHS: Learning Health System.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Several authors have theorized and advocated the need and potential for the LHS to enhance patient safety and social justice. However, few empirical studies have actually examined the effects of immersing in an LHS culture on the patient-doctor relationship, on professional relationships in health systems, or on public accountability and governance. Generally, only a small subset of publications is acutely engaged with key ethical concerns such as trust, solidarity, equity, or privacy. Those that are engaged with these ethical concerns primarily do so from the perspective of calling attention to these concepts as potential rather than actual concerns. Given the ideal of a technical infrastructure that supports and is supported by a social and cultural learning system, it is important for studies to examine whether and how, eg, relationships between providers and administrative leaders may be different in institutions that have implemented an LHS-based technical framework. As such, we suggest that rather than considering concepts such as trust as a challenge, burden, or barrier necessary to master or overcome, the LHS discourse requires studies on how trust affects and is affected by the LHS context to understand its potential to enhance the LHS, if strengthened.</p>
        <p>Many cited challenges and needs in our review align with governance concerns—eg, limitations of data safety and reliability, validity of data, or validity of the algorithmic outputs of data in an LHS. While this literature appears to focus on <italic>overcoming these hurdles</italic> through consideration of the moral obligation of researchers and participants, there was little indication of future research specifically examining the ethical and social aspects of health care and clinical research, eg, through the lens of dignity, equity, equality, and social justice. We suggest that future research needs to examine recruitment and participation in research with a particular focus on the moral imperative, to better understand implications of various approaches to enhancing participation in research on the LHS. Furthermore, the discourse around the LHS needs to attend more to the ethical implications of such systems on patients, participants, and their data and those who may share patient or participant data from both technical and ethical perspectives (eg, physicians, hospitals, public health departments, and payers). For example, it would be important to clearly understand and present practical (eg, economic and therapeutic), social, and ethical rationales for patient participation in clinical research at a systemic level of data agglomeration and analysis, outputs of which may be subject to commercial interests.</p>
        <p>The EHR is considered a valuable resource in publications in our review, a number of articles also point specifically to this resource as requiring improvements to effectively and ethically carry through the LHS vision. Notably, EHRs are financially incentivized in the United States, making the local context ideal for implementing the LHS nationally. At the time Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] made his call for the LHS, the Health Information Technology for Economic and Clinical Health (HITECH) Act and the US $35 billion investment in the adoption and meaningful use of EHRs had yet to materialize [<xref ref-type="bibr" rid="ref68">68</xref>]. Since the HITECH Act, adoption and use of the EHR has continued to increase with evidence of better health outcomes after systems have had time to mature [<xref ref-type="bibr" rid="ref67">67</xref>,<xref ref-type="bibr" rid="ref69">69</xref>]. However, studies have also suggested consequences of EHR use on user (patient and provider) satisfaction, calling to attention the need for considering and understanding implications of the LHS on patients, and the ways in which their embeddedness in the LHS is influenced by the systemic pressures driving health information technology [<xref ref-type="bibr" rid="ref70">70</xref>-<xref ref-type="bibr" rid="ref72">72</xref>]. In addition, there is a need to improve ethical governance, and that continues to include necessary progress on enabling data security. Importantly, improving security does not necessarily mean restricting data from leaving the environment of a screen in an office room at a particular institution; however, there is a need to better understand the boundaries of data as understood by stakeholders including patients, clinicians, and researchers, and their rights and views on how data are retained and used. Furthermore, the information that is stored on the EHR is not always in a standardized format—eg, some data may be in the form of narrative text, whereas others may be more easily coded. For information to be usable, it is necessary to identify ways to make EHRs interoperable and, further, the information on them interpretable in a consistent and standardized way, eg, by using natural language processing techniques [<xref ref-type="bibr" rid="ref73">73</xref>,<xref ref-type="bibr" rid="ref74">74</xref>].</p>
        <p>Although our review primarily focused on papers based in the United States, there is a need to examine the role and implications of an LHS in other health care system contexts. For example, the expectations and incentives for EHR use may vary across contexts. The procedures for recruitment and enrollment in research may also vary, and the principles governing use and sharing of data and health information may be different. In the US context, historical injustices in the research domain have brought to the forefront regulatory principles such as the Belmont Report describing the ethical foundations of research [<xref ref-type="bibr" rid="ref75">75</xref>]. In addition, the influx of new actors within the LHS and big data practices expands questions related to who is doing research and innovation, including sources of funding and commercial interests. These evolutions are likely to guide the direction of work related to developing, implementing, and attending to the ethical and social considerations of an LHS [<xref ref-type="bibr" rid="ref76">76</xref>]. As other countries and health care contexts envision and implement the LHS, it will be important to study how the histories and policies of these countries influence the LHS and how key stakeholders perceive and have expectations for what an LHS can deliver.</p>
        <p>Finally, our sample of publications is indicative of the successes or anticipated challenges with the LHS; however, learning also results from an understanding of what goes wrong. Attempts at implementing an LHS along with evaluations of the process should be disseminated as well, for a more robust understanding of what might be optimal conditions for an LHS and what contexts may need more malleability to adopt an LHS framework and culture. For example, future studies may seek to identify the conditions under which the use of emerging technologies and delivery models achieve the goals of an LHS. For example, are the adoption of telemedicine and the use of patient-generated data via health apps and wearable devices contributing to systems that are also engaged in learning and/or feedback? Furthermore, how are the technical, social, and ethical implications of learning from clinical care delivered through telemedicine different from learning and knowledge generation that occurs through traditional, face-to-face care delivery?</p>
      </sec>
      <sec>
        <title>Conclusions</title>
        <p>The past decade has observed tremendous progress in the technical infrastructure and innovative spirit of advancing the framework and implementation of the LHS. However, there are opportunities to continue to examine and develop policies ensuring the cultural and ethical imperatives for an LHS. Since Etheredge [<xref ref-type="bibr" rid="ref1">1</xref>] presented an initial vision of the LHS in 2007, the growing implementation of the EHR and emergence of networks and platforms have contributed to the initial stages of understanding the LHS framework. However, to continue to define and realize the aims of an LHS, there is a need to consider the boundaries of research, practice, and QI. Furthermore, there is a need for engaging with various stakeholders including patients, participants, providers, and organizational leaders in clinical, technical, administrative, and research domains to understand the broader implications of an LHS.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group/>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">EHR</term>
          <def>
            <p>electronic health record</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">HITECH</term>
          <def>
            <p>Health Information Technology for Economic and Clinical Health</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">ICN</term>
          <def>
            <p>ImproveCareNow</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">LHS</term>
          <def>
            <p>Learning Health System</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb5">QI</term>
          <def>
            <p>quality improvement</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>The authors thank M Grace Trinidad for developing <xref rid="figure1" ref-type="fig">Figure 1</xref> that illustrates the areas critical to the realization of an LHS.</p>
    </ack>
    <fn-group>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
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