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<?covid-19-tdm?>
<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">v25i1e44188</article-id>
      <article-id pub-id-type="pmid">37262124</article-id>
      <article-id pub-id-type="doi">10.2196/44188</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>Facilitators of and Barriers to Accessing Hospital Medical Specialty Telemedicine Consultations During the COVID-19 Pandemic: Systematic 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>Baniasadi</surname>
            <given-names>Tayebeh</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Sarejloo</surname>
            <given-names>Shirin</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Pesälä</surname>
            <given-names>Samuli</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Mars</surname>
            <given-names>Maurice</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Cunha</surname>
            <given-names>Ana Soraia</given-names>
          </name>
          <degrees>MSc</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution>NOVA National School of Public Health</institution>
            <institution>Public Health Research Centre</institution>
            <institution>Universidade NOVA de Lisboa</institution>
            <addr-line>Avenida Padre Cruz</addr-line>
            <addr-line>Lisbon, 1600-560</addr-line>
            <country>Portugal</country>
            <phone>351 217 512 100</phone>
            <email>asr.cunha@ensp.unl.pt</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-6410-2557</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Pedro</surname>
            <given-names>Ana Rita</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-9197-7129</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author">
          <name name-style="western">
            <surname>Cordeiro</surname>
            <given-names>João V</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <xref rid="aff3" ref-type="aff">3</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-4605-1615</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>NOVA National School of Public Health</institution>
        <institution>Public Health Research Centre</institution>
        <institution>Universidade NOVA de Lisboa</institution>
        <addr-line>Lisbon</addr-line>
        <country>Portugal</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, NOVA University Lisbon</institution>
        <addr-line>Lisbon</addr-line>
        <country>Portugal</country>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution>Interdisciplinary Centre of Social Sciences, NOVA University Lisbon</institution>
        <addr-line>Lisbon</addr-line>
        <country>Portugal</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Ana Soraia Cunha <email>asr.cunha@ensp.unl.pt</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2023</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>10</day>
        <month>7</month>
        <year>2023</year>
      </pub-date>
      <volume>25</volume>
      <elocation-id>e44188</elocation-id>
      <history>
        <date date-type="received">
          <day>9</day>
          <month>11</month>
          <year>2022</year>
        </date>
        <date date-type="rev-request">
          <day>15</day>
          <month>2</month>
          <year>2023</year>
        </date>
        <date date-type="rev-recd">
          <day>31</day>
          <month>3</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>3</day>
          <month>5</month>
          <year>2023</year>
        </date>
      </history>
      <copyright-statement>©Ana Soraia Cunha, Ana Rita Pedro, João V Cordeiro. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.07.2023.</copyright-statement>
      <copyright-year>2023</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 https://www.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://www.jmir.org/2023/1/e44188" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>The COVID-19 pandemic accelerated the digital transition in health care, which required a rapid adaptation for stakeholders. Telemedicine has emerged as an ideal tool to ensure continuity of care by allowing remote access to specialized medical services. However, its rapid implementation has exacerbated disparities in health care access, especially for the most susceptible populations.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>We aimed to characterize the determinant factors (facilitators and barriers) of access to hospital medical specialty telemedicine consultations during the COVID-19 pandemic and to identify the main opportunities and challenges (technological, ethical, legal, and social) generated by the use of telemedicine in the context of the COVID-19 pandemic.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We conducted a systematic review according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases (Scopus, Web of Science, PubMed, and Cochrane COVID-19 Study Register) were searched for empirical studies published between January 3, 2020, and December 31, 2021, using established criteria. The protocol of this review was registered and published in PROSPERO (CRD42022302825). A methodological quality assessment was performed, and the results were integrated into a thematic synthesis. The identification of the main opportunities and challenges was done by interpreting and aggregating the thematic synthesis results.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>Of the 106 studies identified, 9 met the inclusion criteria and the intended quality characteristics. All studies were originally from the United States. The following facilitating factors of telemedicine use were identified: health insurance coverage; prevention of SARS-CoV-2 infection; access to internet services; access to technological devices; better management of work-life balance; and savings in travel costs. We identified the following barriers to telemedicine use: lack of access to internet services; lack of access to technological devices; racial and ethnic disparities; low digital literacy; low income; age; language barriers; health insurance coverage; concerns about data privacy and confidentiality; geographic disparities; and the need for complementary diagnostic tests or the delivery of test results.</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>The facilitating factors and barriers identified in this systematic review present different opportunities and challenges, including those of a technological nature (access to technological devices and internet services and level of digital literacy), a sociocultural and demographic nature (ethnic and racial disparities, geographic disparities, language barriers, and age), a socioeconomic nature (income level and health insurance coverage), and an ethical and legal nature (data privacy and confidentiality). To expand telemedicine access to hospital-based specialty medical consultations and provide high-quality care to all, including the most susceptible communities, the challenges identified must be thoroughly researched and addressed with informed and dedicated responses.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>health services accessibility</kwd>
        <kwd>COVID-19</kwd>
        <kwd>hospitals</kwd>
        <kwd>barriers</kwd>
        <kwd>facilitators</kwd>
        <kwd>telemedicine</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <sec>
        <title>Background</title>
        <p>The COVID-19 pandemic, declared on March 11, 2020, by the World Health Organization (WHO), has drastically impacted health care delivery [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>]. Health care professionals, patients, and other stakeholders in the health sector had to adapt to a new reality to try to contain viral spread and prevent disease [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref4">4</xref>]. Furthermore, governments have implemented containment measures and infection control strategies, including social distancing and isolation [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref5">5</xref>].</p>
        <p>Information and communication technologies have played a fundamental role in facilitating contact between people, enabling access to work, education, and health care services during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref7">7</xref>]. In the health care field, as preventive measures were put in place, the number of consultations and face-to-face contacts between patients and health professionals have decreased [<xref ref-type="bibr" rid="ref8">8</xref>,<xref ref-type="bibr" rid="ref9">9</xref>]. Therefore, telemedicine has established itself as a definitive digital solution to address the challenges posed by COVID-19–related isolation measures [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref10">10</xref>-<xref ref-type="bibr" rid="ref12">12</xref>]. The WHO defines telemedicine as “the delivery of health services, where distance is a critical factor, by all health professionals using information and communication technologies for the exchange of valid information for the diagnosis, treatment and prevention of disease and injury, research and evaluation, and for the continuing education of health care providers, all in the interest of advancing the health of individuals and their communities” [<xref ref-type="bibr" rid="ref13">13</xref>]. Telemedicine is recognized as one of the main tools for the development of current health systems, with interventional potential in diagnosing, treating, and preventing diseases [<xref ref-type="bibr" rid="ref14">14</xref>-<xref ref-type="bibr" rid="ref16">16</xref>]. Originally designed to improve health care access in remote communities or across distant geographic locations, telemedicine has been gradually implemented in health care organizations over the last decade [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref17">17</xref>]. Different reasons explain telemedicine’s slow uptake, including limitations in administrative regulations, the absence of solid legal frameworks, low investment in technological resources, and the reluctance of professionals and users to adopt digital solutions [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref19">19</xref>]. The COVID-19 pandemic significantly accelerated the implementation of telemedicine [<xref ref-type="bibr" rid="ref20">20</xref>-<xref ref-type="bibr" rid="ref23">23</xref>]. In the last 2 years alone, telemedicine has been implemented in primary and secondary care across several medical specialties and has assisted in screening, diagnosis, consultations, follow-up visits, access to laboratory results, and medical advice [<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref19">19</xref>,<xref ref-type="bibr" rid="ref24">24</xref>-<xref ref-type="bibr" rid="ref27">27</xref>].</p>
        <p>In parallel, the most susceptible populations have been largely left out of telemedicine adoption during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref28">28</xref>]. Older patients, those of lower socioeconomic status, and those who live with chronic diseases and reside in rural or remote areas have been known to have lower access to health care [<xref ref-type="bibr" rid="ref29">29</xref>]. Such characteristics, combined with lower literacy levels and access to technologies and internet services, have limited even more telemedicine-mediated health care access, reinforcing preexisting disparities [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref30">30</xref>-<xref ref-type="bibr" rid="ref32">32</xref>].</p>
        <p>Since the beginning of the pandemic, different studies have characterized the impact of telemedicine on health care access and identified related opportunities and challenges in various medical settings [<xref ref-type="bibr" rid="ref26">26</xref>,<xref ref-type="bibr" rid="ref33">33</xref>-<xref ref-type="bibr" rid="ref42">42</xref>]. Considering the challenges of telemedicine adoption, particularly during the COVID-19 pandemic, it is crucial that future research focuses on identifying the facilitating factors and addressing the barriers to its widespread use. Identifying these factors and reviewing and systematizing the related evidence are essential steps toward providing a basis for future recommendations aimed at promoting the equitable adoption of telemedicine solutions.</p>
      </sec>
      <sec>
        <title>Objectives</title>
        <p>This systematic review aims to characterize the determinants (facilitators and barriers) of telemedicine use regarding access to hospital medical specialty consultations and to identify the main opportunities and challenges (technological, ethical, legal, and social) generated by the use of telemedicine in the context of the COVID-19 pandemic.</p>
      </sec>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>The methodology for this systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>) [<xref ref-type="bibr" rid="ref43">43</xref>]. The study protocol was registered and published in PROSPERO (CRD42022302825) [<xref ref-type="bibr" rid="ref44">44</xref>].</p>
      <sec>
        <title>Search Strategy</title>
        <p>Primary study collection occurred between October 15, 2021, and January 17, 2022, in PubMed, Scopus, Web of Science, and Cochrane COVID-19 Study Register databases, using the following search keys and Medical Subject Headings (MeSH) terms:</p>
        <list list-type="bullet">
          <list-item>
            <p>PubMed–(“Telemedicine” [Mesh]) AND (“Health Services Accessibility” [Mesh]) AND (“COVID-19” [Mesh] OR “SARS-CoV-2” [Mesh]) AND “Healthcare Disparities” [Mesh].</p>
          </list-item>
          <list-item>
            <p>Scopus, Web of Science, and the Cochrane COVID-19 Study Register–"Telemedicine" AND "Health Services Accessibility" AND "COVID-19" OR "SARS-CoV-2" AND "Healthcare Disparities."</p>
          </list-item>
        </list>
      </sec>
      <sec>
        <title>Eligibility Criteria</title>
        <p>General eligibility criteria included date of publication (from January 3, 2020, to December 31, 2021); language of the article (English, Spanish, and Portuguese); and article type (peer-reviewed original research articles, qualitative, quantitative, and mixed methods evidence published in indexed scientific journals; full-text access to the manuscript).</p>
        <p>Inclusion and exclusion criteria were defined according to the PICOS (Population, Intervention, Comparison, Outcome, and Study Design) strategy [<xref ref-type="bibr" rid="ref45">45</xref>], as shown in <xref ref-type="boxed-text" rid="box1">Textboxes 1</xref> and <xref ref-type="boxed-text" rid="box2">2</xref>.</p>
        <boxed-text id="box1" position="float">
          <title>PICOS (Population, Intervention, Comparison, Outcome, and Study Design [<xref ref-type="bibr" rid="ref45">45</xref>]) inclusion criteria.</title>
          <p>
            <bold>Population (P)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Users of hospital medical specialty consultations via telemedicine during the COVID-19 pandemic.</p>
            </list-item>
            <list-item>
              <p>Adult and pediatric population.</p>
            </list-item>
          </list>
          <p>
            <bold>Intervention (I)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Studies analyzing the effect of telemedicine on access to hospital medical specialty consultations during the COVID-19 pandemic.</p>
            </list-item>
            <list-item>
              <p>Studies characterizing the potential and obstacles to accessing telemedicine services during the COVID-19 pandemic.</p>
            </list-item>
            <list-item>
              <p>Studies identifying challenges (technological, ethical, legal, and social) generated by telemedicine in accessing hospital medical specialty consultations during the COVID-19 pandemic.</p>
            </list-item>
          </list>
          <p>
            <bold>Comparison (C)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Not applicable</p>
            </list-item>
          </list>
          <p>
            <bold>Outcome (O)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Studies that analyze dimensions of hospital medical specialty consultations where telemedicine can be a key aid to improving access to care during a public health emergency.</p>
            </list-item>
            <list-item>
              <p>Studies that identify facilitators and barriers to the implementation of telemedicine in health care.</p>
            </list-item>
            <list-item>
              <p>Studies that are grounds for future recommendations related to the adoption of telemedicine in a medical specialty setting.</p>
            </list-item>
          </list>
          <p>
            <bold>Study design (S)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Observational studies (cohort, case-control, cross-sectional, prospective longitudinal studies).</p>
            </list-item>
            <list-item>
              <p>Descriptive studies (case studies).</p>
            </list-item>
            <list-item>
              <p>Randomized controlled trials.</p>
            </list-item>
          </list>
        </boxed-text>
        <boxed-text id="box2" position="float">
          <title>PICOS (Population, Intervention, Comparison, Outcome, and Study Design [<xref ref-type="bibr" rid="ref45">45</xref>]) exclusion criteria.</title>
          <p>
            <bold>Population (P)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Users of primary health care consultations.</p>
            </list-item>
            <list-item>
              <p>Users of addictive behavior consultations.</p>
            </list-item>
            <list-item>
              <p>Users of vaccination consultations.</p>
            </list-item>
          </list>
          <p>
            <bold>Intervention (I)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Studies in which telemedicine is not the main intervention.</p>
            </list-item>
            <list-item>
              <p>Studies in which telemedicine is not related to access to health care.</p>
            </list-item>
            <list-item>
              <p>Studies in which the intervention was not carried out between January 3, 2020, and December 31, 2021.</p>
            </list-item>
          </list>
          <p>
            <bold>Comparison (C)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Not applicable</p>
            </list-item>
          </list>
          <p>
            <bold>Outcome (O)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Studies that analyze how telemedicine can improve health care access exclusively outside the hospital medical specialty setting.</p>
            </list-item>
          </list>
          <p>
            <bold>Study design (S)</bold>
          </p>
          <list list-type="bullet">
            <list-item>
              <p>Systematic reviews, narrative reviews, or meta-analyses.</p>
            </list-item>
            <list-item>
              <p>Commentary or perspective articles.</p>
            </list-item>
          </list>
        </boxed-text>
      </sec>
      <sec>
        <title>Selection Process and Quality Appraisal</title>
        <p>Articles resulting from the application of the search strategy were transferred to Rayyan software (Rayyan), which was used throughout the selection process [<xref ref-type="bibr" rid="ref46">46</xref>]. Subsequently, all duplicate articles were eliminated. Afterward, the 3 reviewers (ASC, ARP, and JVC) decided on article inclusion and exclusion based on the application of the eligibility criteria, first by analyzing the title, then by analyzing the abstract, and finally by reading the full article. In these 3 phases, selection was made independently and blindly among reviewers.</p>
        <p>Following article selection, anonymity was lifted, and discrepancies were discussed and resolved unanimously, according to the eligibility criteria. Thereafter, selected articles were independently assessed for their quality by 2 reviewers (ARP and JVC). Considering the study designs and methodologies included in this review, quality assessment was performed using the Mixed Methods Appraisal Tool (version 2018; Canadian Intellectual Property Institute), which aims to critically analyze the methodological reliability and validity of 5 categories of studies (qualitative studies, quantitative studies [randomized and nonrandomized], quantitative descriptive studies, and mixed methods studies) [<xref ref-type="bibr" rid="ref47">47</xref>-<xref ref-type="bibr" rid="ref50">50</xref>]. Following individual quality assessments, discrepancies were resolved unanimously among reviewers.</p>
      </sec>
      <sec>
        <title>Data Extraction and Synthesis</title>
        <p>In accordance with the Cochrane Collaboration guidelines [<xref ref-type="bibr" rid="ref51">51</xref>], data from individual articles were extracted by the first reviewer (ASC) into a data extraction table, including the following characteristics: title and author; publication date; country of publication; period of data collection; study design; sample; setting; study objective; medical specialty identification; description of intervention; and main results.</p>
        <p>Following data extraction, data synthesis proceeded in 2 stages. First, considering that the aim of this review is directed toward a qualitative answer, quantitative results were transformed into qualitative ones (qualitizing), as proposed by Popay et al [<xref ref-type="bibr" rid="ref47">47</xref>,<xref ref-type="bibr" rid="ref52">52</xref>,<xref ref-type="bibr" rid="ref53">53</xref>]. Second, in line with the methodology proposed by Thomas and Harden [<xref ref-type="bibr" rid="ref54">54</xref>], a thematic synthesis of the results was performed in the following sequential steps: text coding, construction of descriptive themes, and creation of analytical themes [<xref ref-type="bibr" rid="ref50">50</xref>,<xref ref-type="bibr" rid="ref54">54</xref>-<xref ref-type="bibr" rid="ref56">56</xref>]. Thematic synthesis was performed and double-checked by the first reviewer (ASC) and checked and validated by the second and third reviewers (ARP and JVC).</p>
        <p>Text coding and the construction of descriptive themes were performed by identifying the main topics presented in the descriptions of results, discussion, and conclusions of the included studies and aggregating similarities between studies. Thereafter, the descriptive themes were grouped into 2 main analytical themes—facilitators of telemedicine and barriers to telemedicine use—which were then subdivided into smaller topics.</p>
        <p>The characterization of the main challenges and opportunities posed by the adoption of telemedicine services was performed by interpreting the results of the thematic synthesis.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <sec>
        <title>Included Studies</title>
        <p>We obtained 106 references resulting from the literature search: 28 from PubMed, 42 from Scopus, 28 from Web of Science, and 8 from the Cochrane COVID-19 Study Register (<xref rid="figure1" ref-type="fig">Figure 1</xref>). Of these, 24 duplicate references were removed and 82 advanced to title and abstract analysis. Therefore, 62 (N=106, 58.5%) articles were excluded for not meeting the eligibility criteria, and 20 (N=106, 18.9%) advanced to full reading analysis. At this stage, 10 (N=106, 9.4%) articles were excluded for not meeting the eligibility criteria and 10 (N=106, 9.4%) articles were subject to quality assessment (<xref rid="figure1" ref-type="fig">Figure 1</xref>). Quality assessment resulted in the rejection of 1 of the selected articles [<xref ref-type="bibr" rid="ref57">57</xref>] because of insufficient methodological robustness (<xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref>). Although this review initially aimed to search for qualitative and quantitative evidence, the 9 articles selected presented a descriptive quantitative approach. Therefore, all selected articles were evaluated under the quantitative descriptive studies category of the quality assessment of the included articles based on the Mixed Methods Appraisal Tool (<xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref>).</p>
        <fig id="figure1" position="float">
          <label>Figure 1</label>
          <caption>
            <p>PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; 2020) flowchart.</p>
          </caption>
          <graphic xlink:href="jmir_v25i1e44188_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <p>In this review, we selected 9 (N=106, 8.5%) articles [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref66">66</xref>]. <xref rid="figure1" ref-type="fig">Figure 1</xref> illustrates the selection process, including the reasons for article exclusion, according to the PRISMA flowchart [<xref ref-type="bibr" rid="ref43">43</xref>].</p>
      </sec>
      <sec>
        <title>Study Characteristics</title>
        <p>Regarding publication date, 2 (N=9, 22%) articles were published in 2020 [<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>], 5 (N=9, 56%) articles in 2021 [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref65">65</xref>], and 2 (N=9, 22%) articles in 2022 [<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]. All articles were published in the English language and were conducted in the United States, comprising 3 (N=9, 33%) cross-sectional studies [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref66">66</xref>], 1 (N=9, 11%) cohort study [<xref ref-type="bibr" rid="ref60">60</xref>], 3 (N=9, 33%) retrospective cohort studies [<xref ref-type="bibr" rid="ref62">62</xref>-<xref ref-type="bibr" rid="ref64">64</xref>], 1 (N=9, 11%) cross-sectional study with comparative analysis [<xref ref-type="bibr" rid="ref61">61</xref>], and 1 (N=9, 11%) mixed methods study [<xref ref-type="bibr" rid="ref65">65</xref>] (<xref ref-type="supplementary-material" rid="app3">Multimedia Appendix 3</xref>).</p>
      </sec>
      <sec>
        <title>Facilitating Factors in the Use of Telemedicine Services</title>
        <p>We identified 6 factors that facilitated the use of telemedicine services, which were mentioned in 8 (89%) of the 9 reviewed studies [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>] (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
        <p>The level of health insurance coverage was identified as a facilitating factor for the use of telemedicine in 6 reviewed studies. In the study conducted by Chen et al [<xref ref-type="bibr" rid="ref62">62</xref>], people with Medicare coverage were more likely to have telemedicine consultations via telephone or video than those who used their private health insurance or those who had no insurance associated [<xref ref-type="bibr" rid="ref62">62</xref>]. Other studies included in this systematic review [<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>] also found that patients with insurance coverage for telemedicine services, or those who accessed these services using their private health insurance (vs employer or state health insurance), were more likely to have an internet-based consultation (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
        <table-wrap position="float" id="table1">
          <label>Table 1</label>
          <caption>
            <p>List of barriers to the use of telemedicine services to access medical specialty consultations during the COVID-19 pandemic (N=9).</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="360"/>
            <col width="440"/>
            <col width="200"/>
            <thead>
              <tr valign="top">
                <td>Facilitating factors</td>
                <td>Studies where facilitating factors were addressed or mentioned</td>
                <td>Total, n (%)</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Health insurance coverage</td>
                <td>[<xref ref-type="bibr" rid="ref60">60</xref>-<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>]</td>
                <td>6 (67)</td>
              </tr>
              <tr valign="top">
                <td>Prevention of SARS-CoV-2 infection</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]</td>
                <td>3 (33)</td>
              </tr>
              <tr valign="top">
                <td>Access to internet services</td>
                <td>[<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]</td>
                <td>3 (33)</td>
              </tr>
              <tr valign="top">
                <td>Access to technological devices</td>
                <td>[<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]</td>
                <td>3 (33)</td>
              </tr>
              <tr valign="top">
                <td>Better management of work-life balance</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>]</td>
                <td>1 (11)</td>
              </tr>
              <tr valign="top">
                <td>Travel cost savings</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>]</td>
                <td>1 (11)</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>The prevention of SARS-CoV-2 infection was also identified as a facilitating factor for telemedicine use. Albon et al [<xref ref-type="bibr" rid="ref58">58</xref>] and Chen et al [<xref ref-type="bibr" rid="ref62">62</xref>] identified that one of the reasons why patients used telemedicine services was to avoid personal contacts that could potentially lead to illness from COVID-19. This factor was more important for patients with regular follow-up appointments [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]. In addition, Ng and Park [<xref ref-type="bibr" rid="ref59">59</xref>] also observed that the presence of patient comorbidities was associated with greater accessibility to telemedicine services as a replacement for regularly scheduled appointments to prevent and reduce the risk of contracting COVID-19 (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
        <p>Lattimore et al [<xref ref-type="bibr" rid="ref60">60</xref>], Elam et al [<xref ref-type="bibr" rid="ref61">61</xref>], and Ng and Park [<xref ref-type="bibr" rid="ref59">59</xref>] highlighted the relevance of access to internet services and technological devices as key factors in accessing telemedicine services. People who lived in areas with faster internet services and those who had technological devices at their disposal, such as smartphones, tablets, or computers, were more likely to perform and choose telemedicine consultations [<xref ref-type="bibr" rid="ref59">59</xref>-<xref ref-type="bibr" rid="ref61">61</xref>] (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
        <p>The reviewed studies also identified management of work-life balance and savings on travel costs as facilitating factors for telemedicine use. According to Albon et al [<xref ref-type="bibr" rid="ref58">58</xref>], about half of the care programs for people with cystic fibrosis (49%) identified reduced travel costs and easier management of family and professional life as the main factors facilitating the use of telemedicine compared with face-to-face consultations (<xref ref-type="table" rid="table1">Table 1</xref>).</p>
      </sec>
      <sec>
        <title>Barriers to the Use of Telemedicine Services</title>
        <p>The lack of necessary technological conditions or equipment and the lack of home internet service, including broadband internet service, were identified as barriers to telemedicine specialty consultations during the COVID-19 pandemic in 8 reviewed studies [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref65">65</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). Regarding the lack of technological conditions or equipment needed, the authors specifically highlighted the lack of access to smartphones and the fact that some people do not have devices with an incorporated camera [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref65">65</xref>].</p>
        <table-wrap position="float" id="table2">
          <label>Table 2</label>
          <caption>
            <p>List of barriers to the use of telemedicine services to access medical specialty consultations during the COVID-19 pandemic (N=9).</p>
          </caption>
          <table border="1" rules="groups" cellpadding="5" frame="hsides" width="1000" cellspacing="0">
            <col width="500"/>
            <col width="370"/>
            <col width="130"/>
            <thead>
              <tr valign="top">
                <td>Barriers</td>
                <td>Studies where barriers were addressed or mentioned</td>
                <td>Total, n (%)</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Lack of access to internet services</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref65">65</xref>]</td>
                <td>8 (89)</td>
              </tr>
              <tr valign="top">
                <td>Lack of access to technological devices</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref65">65</xref>]</td>
                <td>8 (89)</td>
              </tr>
              <tr valign="top">
                <td>Racial and ethnic disparities</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>]</td>
                <td>6 (67)</td>
              </tr>
              <tr valign="top">
                <td>Low level of digital literacy</td>
                <td>[<xref ref-type="bibr" rid="ref60">60</xref>-<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>-<xref ref-type="bibr" rid="ref66">66</xref>]</td>
                <td>6 (67)</td>
              </tr>
              <tr valign="top">
                <td>Low income</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>]</td>
                <td>6 (67)</td>
              </tr>
              <tr valign="top">
                <td>Age (years)</td>
                <td>[<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>-<xref ref-type="bibr" rid="ref64">64</xref>]</td>
                <td>5 (56)</td>
              </tr>
              <tr valign="top">
                <td>Language barriers</td>
                <td>[<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref65">65</xref>]</td>
                <td>4 (44)</td>
              </tr>
              <tr valign="top">
                <td>Health insurance coverage</td>
                <td>[<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>]</td>
                <td>2 (22)</td>
              </tr>
              <tr valign="top">
                <td>Data privacy and confidentiality concerns</td>
                <td>[<xref ref-type="bibr" rid="ref64">64</xref>]</td>
                <td>1 (11)</td>
              </tr>
              <tr valign="top">
                <td>Geographic disparities (area of residence)</td>
                <td>[<xref ref-type="bibr" rid="ref59">59</xref>]</td>
                <td>1 (11)</td>
              </tr>
              <tr valign="top">
                <td>Need to perform complementary diagnostic tests or receive test results</td>
                <td>[<xref ref-type="bibr" rid="ref65">65</xref>]</td>
                <td>1 (11)</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>Several reviewed studies [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>] identified belonging to racial and ethnic minority groups as an obstacle to accessing telemedicine consultations (<xref ref-type="table" rid="table2">Table 2</xref>). Eberly et al [<xref ref-type="bibr" rid="ref64">64</xref>] mentioned that people belonging to racial and ethnic minority groups generally have more difficulties accessing health care, have developed weaker relationships with health care professionals, and have reported more negative experiences in health care in the past. These factors were identified by the authors as leading to more difficulties in accessing telemedicine consultations or leading to less referrals [<xref ref-type="bibr" rid="ref64">64</xref>]. Similarly, Albon et al [<xref ref-type="bibr" rid="ref58">58</xref>] reported that people from racial and ethnic minority groups were less referred to telemedicine consultations, had more concerns about associated copayments, and presented language barriers.</p>
        <p>A lower level of digital literacy was also identified in reviewed studies as an obstacle for telemedicine consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>-<xref ref-type="bibr" rid="ref66">66</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). Furthermore, this obstacle has been associated with other circumstances. Lattimore et al [<xref ref-type="bibr" rid="ref60">60</xref>] and Chen et al [<xref ref-type="bibr" rid="ref62">62</xref>] associated low digital literacy with lower use of telemedicine services, especially among older people. Lattimore et al [<xref ref-type="bibr" rid="ref60">60</xref>] also associated low literacy with a lower socioeconomic level and less access to technological resources. Nonetheless, Haynes et al [<xref ref-type="bibr" rid="ref65">65</xref>] reported that digital literacy can be low even in groups with access to technology.</p>
        <p>Some reviewed studies also identified low income as an obstacle to telemedicine consultation access during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). Eberly et al [<xref ref-type="bibr" rid="ref64">64</xref>], Darrat et al [<xref ref-type="bibr" rid="ref63">63</xref>], and Lattimore et al [<xref ref-type="bibr" rid="ref60">60</xref>] showed that people with lower household incomes were less likely to access internet services and technologies and were less associated with telemedicine consultations [<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>]. Ng and Park [<xref ref-type="bibr" rid="ref59">59</xref>] reported that disparities in accessibility to telemedicine services by income level were also observed. Those with lower incomes were referred less frequently to telemedicine consultations by health professionals [<xref ref-type="bibr" rid="ref59">59</xref>]. In the study by Albon et al [<xref ref-type="bibr" rid="ref58">58</xref>], people who reported experiencing financial problems during the study period found it more difficult to use telemedicine services. Whaley et al [<xref ref-type="bibr" rid="ref66">66</xref>] also observed that people who lived in locations associated with lower income levels experienced smaller reductions in in-person visits while also experiencing lower rates of telemedicine adoption than people living in higher-income zip codes.</p>
        <p>Age is highlighted in 5 reviewed articles as a barrier to the adoption of telemedicine medical specialty consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>-<xref ref-type="bibr" rid="ref64">64</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). In particular, patients aged &#62;55 years had fewer telemedicine consultations [<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>]. Eberly et al [<xref ref-type="bibr" rid="ref64">64</xref>] indicated that older users feel more concerned about privacy violations and the insecurity of their personal data. This factor led to more resistance to telemedicine consultations (<xref ref-type="table" rid="table2">Table 2</xref>).</p>
        <p>The existence of language barriers was also recognized as a limitation in accessing telemedicine specialty consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref65">65</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). The studies conducted by Albon et al [<xref ref-type="bibr" rid="ref58">58</xref>], Haynes et al [<xref ref-type="bibr" rid="ref65">65</xref>], and Eberly et al [<xref ref-type="bibr" rid="ref64">64</xref>] revealed that people who were not native language speakers were less likely to undergo an internet-based appointment and were more likely to undergo face-to-face consultations. Chen et al [<xref ref-type="bibr" rid="ref62">62</xref>] also reported similar findings.</p>
        <p>In coherence with the identification of health insurance coverage as a facilitating factor, the lack of such coverage was identified as a barrier to accessing telemedicine medical consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). Eberly et al [<xref ref-type="bibr" rid="ref64">64</xref>] found that Medicaid insurance beneficiaries used fewer telemedicine consultations than private health insurance users and discussed the need to have parameterization in telemedicine consultation payments between insurers through permanent legislative action.</p>
        <p>In the study by Ng and Park [<xref ref-type="bibr" rid="ref59">59</xref>], disparities in access to telemedicine specialty consultations during the COVID-19 pandemic were found according to area of residence. People who lived outside metropolitan areas reported being referred less often for telemedicine consultations by health professionals [<xref ref-type="bibr" rid="ref59">59</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>).</p>
        <p>Other obstacles to accessing telemedicine specialty consultations during the COVID-19 pandemic were also found. In particular, the need to perform complementary diagnostic tests or to deliver medical test results was identified by Haynes et al [<xref ref-type="bibr" rid="ref65">65</xref>] (<xref ref-type="table" rid="table2">Table 2</xref>). This study specifically mentioned the need to undergo laboratory tests or personally receive clinical records of insulin levels as reasons why some people opted for in-person appointments as an alternative to telemedicine [<xref ref-type="bibr" rid="ref65">65</xref>].</p>
        <p>Overall, results from the reviewed studies showed that opportunities and challenges to access telemedicine specialty consultations during the COVID-19 pandemic are broad and multifactorial (<xref rid="figure2" ref-type="fig">Figure 2</xref>).</p>
        <fig id="figure2" position="float">
          <label>Figure 2</label>
          <caption>
            <p>Opportunities and challenges to the adoption of telemedicine services to access medical specialty consultations during the COVID-19 pandemic.</p>
          </caption>
          <graphic xlink:href="jmir_v25i1e44188_fig2.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Interpretation of Results</title>
        <p>Thematic synthesis of the reviewed studies identified more barriers to the use of telemedicine than facilitating factors (11 barriers and 6 facilitating factors). This finding may suggest that the existing conditions for the use of telemedicine before the COVID-19 pandemic were not ready to respond to the rapid transition to a new reality of medical care delivery based on physical distancing. This transition might, in turn, have worsened preexisting disparities in health care delivery [<xref ref-type="bibr" rid="ref25">25</xref>,<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref33">33</xref>].</p>
        <p>Management of work-life balance, saving travel costs, and prevention of SARS-CoV-2 infection were the factors that, according to reviewed evidence, most encouraged the use of telemedicine for specialty consultations during the pandemic period [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref62">62</xref>]. Remote medical appointments can be more comfortable for patients by allowing them to avoid traveling to the appointment locations and reducing the associated costs [<xref ref-type="bibr" rid="ref16">16</xref>,<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref67">67</xref>]. Telemedicine can also adapt medical appointment timings to personal and professional routines and provide more flexibility [<xref ref-type="bibr" rid="ref16">16</xref>,<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref67">67</xref>]. In addition, and given the context under analysis, the reduction of in-person consultations as a COVID-19 prevention measure has forced people to access health care by alternative means, and telemedicine is one of the most appropriate digital solutions for that purpose [<xref ref-type="bibr" rid="ref27">27</xref>,<xref ref-type="bibr" rid="ref68">68</xref>,<xref ref-type="bibr" rid="ref69">69</xref>]. These 2 results are consistent with the systematic review conducted by Almathami et al [<xref ref-type="bibr" rid="ref30">30</xref>], which also identified time savings, patient convenience, management, accessibility, and cost reductions as facilitating factors for making home health care appointments web based [<xref ref-type="bibr" rid="ref30">30</xref>]. Furthermore, telemedicine consultations can proceed synchronously (in real time or through video consultation) or asynchronously (through the transmission of data and information indirectly, via digital platforms), providing individual advantages not only in terms of time, costs, and travel savings but also in terms of reducing costs and expenses for health systems [<xref ref-type="bibr" rid="ref17">17</xref>,<xref ref-type="bibr" rid="ref27">27</xref>].</p>
        <p>This review also showed that patients whose insurance had coverage for telemedicine services, accessed more virtual consultations [<xref ref-type="bibr" rid="ref60">60</xref>-<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>]. Conversely, people with more concerns about associated copayments, users of public health insurance, and those whose insurance did not cover telemedicine services accessed this type of consultation less [<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>].</p>
        <p>These findings are closely related to inequalities in access to telemedicine across income levels, which we also identified to be a barrier to telemedicine specialty consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref60">60</xref>,<xref ref-type="bibr" rid="ref63">63</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>]. These findings are in line with results from other studies [<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref17">17</xref>,<xref ref-type="bibr" rid="ref70">70</xref>-<xref ref-type="bibr" rid="ref75">75</xref>]. In the narrative review by Shaw et al [<xref ref-type="bibr" rid="ref70">70</xref>], reduced telemedicine access was observed in lower-income communities. Furthermore, Barbosa et al [<xref ref-type="bibr" rid="ref17">17</xref>] and Adigwu et al [<xref ref-type="bibr" rid="ref71">71</xref>] found that patients from lower-income areas also had less access to medical specialty consultations during the pandemic period. Moreover, Lesher et al [<xref ref-type="bibr" rid="ref72">72</xref>] found that lower income levels were associated with lower use of internet-based surgical consultations.</p>
        <p>Regarding technological factors, according to reviewed studies, expanded access to internet services and technological devices can increase the chance of accessing telemedicine consultations [<xref ref-type="bibr" rid="ref59">59</xref>-<xref ref-type="bibr" rid="ref61">61</xref>]. Conversely, not having access to digital devices or the internet can limit access to telemedicine services or even make it impossible [<xref ref-type="bibr" rid="ref58">58</xref>-<xref ref-type="bibr" rid="ref65">65</xref>]. The lack of access to internet and broadband services, poor signal coverage, a lack of technological devices suitable for conducting internet-based consultations, the absence of built-in cameras, or devices with poor video and audio transmission are some of the barriers to the use of telemedicine also identified by Almathami et al [<xref ref-type="bibr" rid="ref30">30</xref>] and Shaw et al [<xref ref-type="bibr" rid="ref70">70</xref>]. Other studies have also identified technological barriers as a major problem for telemedicine implementation during the pandemic period [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref76">76</xref>-<xref ref-type="bibr" rid="ref78">78</xref>].</p>
        <p>In parallel, low levels of digital literacy imply reduced access to telemedicine consultations because the lack of familiarization and knowledge about technology is strongly related to mistrust and fear, leading to resistance [<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>-<xref ref-type="bibr" rid="ref66">66</xref>]. Digital literacy is a widely studied topic and is extremely important for the success of the digital transition in all areas of society [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref79">79</xref>-<xref ref-type="bibr" rid="ref84">84</xref>]. Globally, there are several initiatives and recommendations generated to promote digital health literacy education, mainly targeting the most susceptible populations [<xref ref-type="bibr" rid="ref85">85</xref>].</p>
        <p>Regarding sociocultural and demographic challenges, this systematic review identified 1 study that noted geographic disparities in referrals to telemedicine consultations [<xref ref-type="bibr" rid="ref59">59</xref>]. In this study, people living in metropolitan areas were more often referred to telemedicine consultations than people living in nonmetropolitan or rural areas [<xref ref-type="bibr" rid="ref59">59</xref>]. Although telemedicine was originally designed to respond to the challenges of health care access in remote locations, people living in rural areas are more likely to have lower income levels, less access to broadband internet services and technological infrastructure, and potentially lower levels of digital literacy, which constitute barriers to accessing digital care [<xref ref-type="bibr" rid="ref28">28</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref80">80</xref>,<xref ref-type="bibr" rid="ref86">86</xref>]. In parallel, according to Ng and Park [<xref ref-type="bibr" rid="ref59">59</xref>], the low referral rate to telemedicine consultations in rural areas during the pandemic may also be related to the fact that, in these places, COVID-19 containment measures were implemented later and were less restrictive.</p>
        <p>Disparities among people belonging to racial and ethnic minority groups were also identified as a barrier to telemedicine access during the COVID-19 pandemic. Six studies included in this review [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref66">66</xref>] identified that patients belonging to minority groups were the most fragile in terms of access to telemedicine. This observation is not surprising, as these patients have been previously shown to face more difficulties in accessing medical care in general. Furthermore, it illustrates that besides being an effective tool to minimize disparities, telemedicine adoption can also deepen existing inequalities [<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref86">86</xref>-<xref ref-type="bibr" rid="ref89">89</xref>]. The main reasons for racial and ethnic disparities in access to telemedicine consultations during the COVID-19 pandemic were the lack of technological resources, less familiarity with these technologies, less referral by health professionals, fear of the possible associated copayments, and the existence of language barriers [<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref70">70</xref>,<xref ref-type="bibr" rid="ref90">90</xref>].</p>
        <p>Importantly, the existence of language limitations was also identified in 4 studies in this review [<xref ref-type="bibr" rid="ref58">58</xref>,<xref ref-type="bibr" rid="ref62">62</xref>,<xref ref-type="bibr" rid="ref64">64</xref>,<xref ref-type="bibr" rid="ref65">65</xref>] as a barrier to the use of telemedicine during the COVID-19 pandemic. People with less proficiency in the language of the country they lived in recurred more to face-to-face consultations [<xref ref-type="bibr" rid="ref64">64</xref>]. Other studies have identified this barrier and reinforced the importance of including translation services in all stages of the health care interaction to increase adherence to health guidance [<xref ref-type="bibr" rid="ref25">25</xref>,<xref ref-type="bibr" rid="ref76">76</xref>,<xref ref-type="bibr" rid="ref79">79</xref>,<xref ref-type="bibr" rid="ref90">90</xref>-<xref ref-type="bibr" rid="ref92">92</xref>]. The study conducted by Tatemoto et al [<xref ref-type="bibr" rid="ref93">93</xref>] identified communication barriers as the main obstacle to telerehabilitation therapy, emphasizing the importance of education for the use of telemedicine, along with language translation during the interaction. Another inclusive measure could be to provide educational training for the use of telemedicine in several languages [<xref ref-type="bibr" rid="ref94">94</xref>].</p>
        <p>This review also identified that different studies described that patients aged &#62;55 years had fewer medical specialty consultations via telemedicine during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref59">59</xref>,<xref ref-type="bibr" rid="ref61">61</xref>-<xref ref-type="bibr" rid="ref64">64</xref>]. This age-related barrier has been shown to be linked with low digital literacy levels, which leads to reluctance in technological adoption [<xref ref-type="bibr" rid="ref80">80</xref>,<xref ref-type="bibr" rid="ref95">95</xref>-<xref ref-type="bibr" rid="ref97">97</xref>]. Furthermore, older patients tend to accumulate more comorbidities and general physical limitations, which complicate remote medical consultations, such as a difficulty to see or hear and poor manual dexterity [<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref98">98</xref>]. These limiting factors often lead to frustration and demotivation to use technology, requiring the assistance of caregivers [<xref ref-type="bibr" rid="ref99">99</xref>,<xref ref-type="bibr" rid="ref100">100</xref>]. However, the higher disease burdens in older patients translate into the need for more medical consultations. Therefore, overcoming age-associated barriers to telemedicine adoption is fundamental so that older patients benefit from remote medical appointments, thereby reducing travel costs and risks while providing more comfort [<xref ref-type="bibr" rid="ref101">101</xref>].</p>
        <p>Performing complementary diagnostic tests and delivering medical results were also factors that, according to Haynes et al [<xref ref-type="bibr" rid="ref65">65</xref>], have led patients to opt for in-person consultations. Nevertheless, the execution of laboratory tests or other complementary tests should not be automatically considered a barrier to the use of telemedicine solely based on the assumption that they require in-person attendance [<xref ref-type="bibr" rid="ref102">102</xref>-<xref ref-type="bibr" rid="ref104">104</xref>]. An increasing number of medical devices (hardware) remotely register and collect vital and anthropometric signs (pulse, glycemia, temperature, body fat, etc) and perform diagnostic tests, such as an electrocardiogram [<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref105">105</xref>-<xref ref-type="bibr" rid="ref108">108</xref>]. Furthermore, the delivery of medical records can already be done by the patient through dedicated digital platforms (software) [<xref ref-type="bibr" rid="ref109">109</xref>]. However, digital health integration does not work per se and should consider the limitations related to technology access and use, as previously discussed [<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref110">110</xref>].</p>
        <p>Data privacy and confidentiality concerns have also been identified as an ethical and legal challenge to telemedicine specialty consultations during the COVID-19 pandemic [<xref ref-type="bibr" rid="ref64">64</xref>]. Results suggest that certain patients may feel insecure about scheduling medical appointments using digital platforms, as they have concerns about their privacy [<xref ref-type="bibr" rid="ref111">111</xref>-<xref ref-type="bibr" rid="ref115">115</xref>]. Health data are sensitive, confidential, and private [<xref ref-type="bibr" rid="ref116">116</xref>]. To provide medical care, health data must be accessed by different professionals and sometimes institutions and across different devices [<xref ref-type="bibr" rid="ref117">117</xref>]. As accumulating evidence suggests that health digital data systems are vulnerable and outdated, the treatment of health data in digital spaces can sometimes pose a higher risk of breaches and damages [<xref ref-type="bibr" rid="ref118">118</xref>-<xref ref-type="bibr" rid="ref122">122</xref>]. Telemedicine consultations must preserve the patient-physician relationship, which requires the implementation of data protection safeguards and respect for medical confidentiality [<xref ref-type="bibr" rid="ref123">123</xref>-<xref ref-type="bibr" rid="ref127">127</xref>]. Therefore, it is crucial to continue implementing strategies at institutional, national, and international levels that promote the responsible use of medical data, including the adoption of telemedicine-specific safeguards [<xref ref-type="bibr" rid="ref119">119</xref>,<xref ref-type="bibr" rid="ref125">125</xref>-<xref ref-type="bibr" rid="ref127">127</xref>]. These might involve implementing codes of conduct, optimizing ethical rules, establishing fair procedures, and imposing dissuasive sanctions (disciplinary, legal, and social) for misconduct [<xref ref-type="bibr" rid="ref119">119</xref>].</p>
      </sec>
      <sec>
        <title>Strengths and Limitations</title>
        <p>Similar to any other study, this review is not completely free of limitations. First, all the studies that were included in this review originate from the United States. Therefore, it is important to exercise caution when extrapolating the conclusions to different contexts. Furthermore, only articles written in English, Spanish, and Portuguese were searched, which could be a potential limitation as relevant results from other studies written in different languages may have been excluded from this systematic review. Most of the included studies are retrospective and used large-volume databases to extract relevant information. The possibility of errors in coding during data input or failures in the analysis and interpretation of statistical associations could not be excluded. Moreover, another aspect that should be considered is that this review did not include any “gray literature,” which could have limited access to contrasting or unknown information. In addition, the collection of primary studies only involved searches using MeSH terms, which could have impacted the number of articles identified through our search. In parallel, the fact that this systematic review relied on a synthesis of qualitative evidence may also have been subject to possible interpretation biases. In this review, an objective assessment of study bias was made in the selection process. However, the results are not completely free of human judgment.</p>
        <p>Nonetheless, this systematic review adds a body of evidence-based knowledge about the facilitating factors and barriers to telemedicine use for hospital medical specialty consultations in the context of the COVID-19 pandemic. The protocol of our review was also previously submitted and published in PROSPERO to ensure transparency [<xref ref-type="bibr" rid="ref44">44</xref>]. This review searched 4 well-known databases using key terms registered in MeSH and included only indexed and peer-reviewed articles. A total of 3 reviewers were involved in this study throughout the execution process. Article selection was performed blindly and independently, and study quality was thoroughly assessed. All included studies involved large sample numbers, which is indicative of scientific robustness.</p>
      </sec>
      <sec>
        <title>Implications of the Results for Clinical Practice, Policy, and Future Research</title>
        <p>By examining the facilitating factors of and barriers to telemedicine adoption during a time when in-person health care was limited by the existence of a public health emergency, the results of this systematic review highlight the need to continue rethinking how distance health care is delivered.</p>
        <p>Several challenges need to be overcome to take advantage of the full potential of digital technology in health care. In particular, this review highlights the importance of paying special attention to the needs of the most susceptible and underprivileged individuals in digital care. It also underscores the necessity of ensuring fair and equitable access to technological resources, providing adequate incentives for medical referrals, and strengthening public health policies that promote digital health literacy. In addition, at the clinical level, it is crucial to establish standards that dictate the appropriate use of telemedicine services, accredit professionals and institutions to provide these services, reinforce administrative regulations, and establish robust legal frameworks that safeguard users and institutions against potential breaches in data system security.</p>
        <p>Future research should examine whether the identified opportunities and challenges in accessing telemedicine services during the pandemic period in the United States apply to other international contexts. In addition, research should explore how these opportunities and challenges apply to nonpandemic settings and different populations, as well as strategies to optimize the benefits and minimize the risks of using telemedicine for medical specialty consultations across various settings.</p>
      </sec>
      <sec>
        <title>Conclusions</title>
        <p>In the last few years, telemedicine adoption has been increasing. More recently, telemedicine has emerged as a powerful ally for safe and effective health care delivery during a public health emergency. However, the COVID-19 pandemic exacerbated disparities in telemedicine access.</p>
        <p>We found that health insurance coverage was a primary factor that facilitated the use of telemedicine services, although limited access to technology and internet services were the most significant barriers to adherence to this mode of care. To expand health care access and provide high-quality care for all, including the most susceptible communities, the determinants of the technological, sociocultural, demographic, socioeconomic, ethical, and legal challenges identified in this systematic review must be researched and met with informed and dedicated responses. These results underscore the importance of rethinking how remote health care is delivered to ensure fair and equitable access, especially during a public health crisis when digital health care is crucial.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group>
      <supplementary-material id="app1">
        <label>Multimedia Appendix 1</label>
        <p>PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; 2020) checklist.</p>
        <media xlink:href="jmir_v25i1e44188_app1.pdf" xlink:title="PDF File  (Adobe PDF File), 203 KB"/>
      </supplementary-material>
      <supplementary-material id="app2">
        <label>Multimedia Appendix 2</label>
        <p>Results of the quality assessment of the included articles based on the Mixed Methods Appraisal Tool (version 2018).</p>
        <media xlink:href="jmir_v25i1e44188_app2.docx" xlink:title="DOCX File , 22 KB"/>
      </supplementary-material>
      <supplementary-material id="app3">
        <label>Multimedia Appendix 3</label>
        <p>Data extraction table: characterization of the included studies.</p>
        <media xlink:href="jmir_v25i1e44188_app3.docx" xlink:title="DOCX File , 25 KB"/>
      </supplementary-material>
    </app-group>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">MeSH</term>
          <def>
            <p>Medical Subject Headings</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">PICOS</term>
          <def>
            <p>Population, Intervention, Comparison, Outcome, and Study Design</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">PRISMA</term>
          <def>
            <p>Preferred Reporting Items for Systematic Reviews and Meta-Analyses</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">WHO</term>
          <def>
            <p>World Health Organization</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>This publication was funded by Fundação Ciência e Tecnologia, IP national support through the Comprehensive Health Research Centre (UIDP/04923/2020).</p>
    </ack>
    <fn-group>
      <fn fn-type="con">
        <p>ASC contributed to the study design, selection process, data extraction, conduction and verification of the thematic synthesis, interpretation of the results of the thematic synthesis, and drafting of the paper. ARP contributed to the study design, selection process, quality assessment of the included studies, verification and validation of the results of the thematic synthesis, interpretation of the thematic synthesis, and drafting of the paper. JVC contributed to the study design, selection process, quality assessment of the included studies, verification and validation of the results of the thematic synthesis, interpretation of the thematic synthesis, and drafting of the paper. All the authors approved the submitted paper.</p>
      </fn>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
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