<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="letter"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Form Res</journal-id><journal-id journal-id-type="publisher-id">formative</journal-id><journal-id journal-id-type="index">27</journal-id><journal-title>JMIR Formative Research</journal-title><abbrev-journal-title>JMIR Form Res</abbrev-journal-title><issn pub-type="epub">2561-326X</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">v10i1e89638</article-id><article-id pub-id-type="doi">10.2196/89638</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Letter</subject></subj-group></article-categories><title-group><article-title>A Survey of Primary Care Clinician Experiences With Electronic Health Record&#x2013;Based Clinical Decision Support to Improve HIV Pre-Exposure Prophylaxis Prescribing</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Agovi</surname><given-names>Afiba Manza-A</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Thompson</surname><given-names>Caitlin T</given-names></name><degrees>MPH, MS</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Li</surname><given-names>Wentao</given-names></name><degrees>MS</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Allard</surname><given-names>Jennifer</given-names></name><degrees>APRN, MSN-MPH</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Lee</surname><given-names>Nicole</given-names></name><degrees>MSW</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Fasanmi</surname><given-names>Esther</given-names></name><degrees>PharmD</degrees><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Ojha</surname><given-names>Rohit P</given-names></name><degrees>DrPH</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib></contrib-group><aff id="aff1"><institution>Center for Epidemiology &#x0026; Healthcare Delivery Research, JPS Health Network</institution><addr-line>1500 South Main Street</addr-line><addr-line>Fort Worth</addr-line><addr-line>TX</addr-line><country>United States</country></aff><aff id="aff2"><institution>True Worth Clinic, JPS Health Network</institution><addr-line>Fort Worth</addr-line><addr-line>TX</addr-line><country>United States</country></aff><aff id="aff3"><institution>Pharmacy Clinical Services Outpatient, JPS Health Network</institution><addr-line>Fort Worth</addr-line><addr-line>TX</addr-line><country>United States</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Mavragani</surname><given-names>Amaryllis</given-names></name></contrib><contrib contrib-type="editor"><name name-style="western"><surname>Steenstra</surname><given-names>Ivan</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Liu</surname><given-names>Yiyang</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Afiba Manza-A Agovi, PhD, Center for Epidemiology &#x0026; Healthcare Delivery Research, JPS Health Network, 1500 South Main Street, Fort Worth, TX, 76104, United States, 1 817 702 8201; <email>mmensah@jpshealth.org</email></corresp></author-notes><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>16</day><month>4</month><year>2026</year></pub-date><volume>10</volume><elocation-id>e89638</elocation-id><history><date date-type="received"><day>15</day><month>12</month><year>2025</year></date><date date-type="rev-recd"><day>18</day><month>03</month><year>2026</year></date><date date-type="accepted"><day>25</day><month>03</month><year>2026</year></date></history><copyright-statement>&#x00A9; Afiba Manza-A Agovi, Caitlin T Thompson, Wentao Li, Jennifer Allard, Nicole Lee, Esther Fasanmi, Rohit P Ojha. Originally published in JMIR Formative Research (<ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>), 16.4.2026. </copyright-statement><copyright-year>2026</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 (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://formative.jmir.org/2026/1/e89638"/><abstract><p>A survey of primary care clinicians suggests that a clinical decision support tool to support sexual risk assessment and prescribing of HIV pre-exposure prophylaxis was appropriate and useful for identifying at-risk patients, but uptake was hindered by workflow and usability barriers, which underscores the importance of postimplementation clinician feedback to improve the use of clinical decision support tools.</p></abstract><kwd-group><kwd>clinical decision support systems</kwd><kwd>HIV pre-exposure prophylaxis</kwd><kwd>PrEP prescribing</kwd><kwd>sexual history documentation</kwd><kwd>primary care clinicians</kwd><kwd>community health centers</kwd><kwd>electronic health records</kwd><kwd>implementation science</kwd><kwd>physician engagement</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Inadequate sexual history screening in US primary care limits identification of candidates for HIV pre-exposure prophylaxis (PrEP) and exacerbates inequities in PrEP uptake [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>]. Many electronic health record (EHR) systems lack standardized prompts for documenting sexual risk, which contributes to missed opportunities for sexual health discussions and HIV prevention. This documentation gap is compounded by limited provider knowledge of PrEP and the absence of validated tools to guide prescribing decisions [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref4">4</xref>].</p><p>EHR-based clinical decision support (CDS) tools may address these gaps by facilitating sexual risk assessment and supporting PrEP prescribing [<xref ref-type="bibr" rid="ref5">5</xref>]. Prior studies suggest that CDS tools are acceptable and feasible [<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref7">7</xref>] and may improve PrEP prescribing [<xref ref-type="bibr" rid="ref5">5</xref>]. Nevertheless, clinician experiences using CDS tools for sexual risk assessment and PrEP prescribing in primary care remain poorly understood. Clinician feedback about such CDS tools may inform efforts to optimize use of these tools. Therefore, we aimed to describe primary care clinicians&#x2019; experiences using CDS tools implemented in urban community health clinics to support sexual risk assessment and PrEP prescribing.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Study Design</title><p>We followed the Checklist for Reporting of Survey Studies (CROSS) guidelines to structure this report. We surveyed primary care clinicians from 12 community health clinics at John Peter Smith Health Network (JPS), a publicly funded urban health system that serves as the health care safety net for Tarrant County, Texas. JPS implemented an EHR-based CDS tool comprising a sexual history questionnaire, a PrEP SmartSet, and a noninterruptive advisory alert (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). When clinicians complete the sexual history questionnaire during an outpatient visit, a noninterruptive PrEP advisory alert is triggered if documented responses indicate behavioral or sexual risk factors consistent with US Centers for Disease Control and Prevention PrEP eligibility criteria.</p></sec><sec id="s2-2"><title>Survey Administration and Data Collection</title><p>We conducted a cross-sectional survey using a 12-item questionnaire to assess clinician awareness, use, perceptions, and perceived barriers and facilitators to the implementation of the CDS tool. Eligible participants included attending physicians, residents, nurse practitioners, physician assistants, and clinical pharmacists providing primary care at one of 12 JPS community health clinics. Survey items were adapted from prior CDS research and informed by the Consolidated Framework for Implementation Research (<xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref>). The anonymous web-based questionnaire (Research Electronic Data Capture) was distributed by email from July 8 to 29, 2024, and included 11 closed-ended items in Likert-scale format and one open-ended question to identify perceived implementation barriers and facilitators (<xref ref-type="supplementary-material" rid="app3">Multimedia Appendix 3</xref>). The survey included core questions on tool awareness or use for all respondents and used branching (conditional) logic that prompted questions about tool perceptions only to respondents who reported awareness.</p></sec><sec id="s2-3"><title>Statistical Analysis</title><p>We summarized scores for closed-ended responses using medians and interquartile ranges (IQRs) and summarized frequencies of agreement with each item, where agreement reflects &#x201C;agree&#x201D; or &#x201C;strongly agree&#x201D; and disagreement reflects &#x201C;disagree&#x201D; or &#x201C;strongly disagree.&#x201D; Neutral responses were included in the denominator of these frequencies but not separately reported for easier contrast of extremes. We analyzed open-ended responses using conventional content analysis supported by a large language model (GPT-4 by ChatGPT) to identify recurring themes (<xref ref-type="supplementary-material" rid="app4">Multimedia Appendix 4</xref>).</p></sec><sec id="s2-4"><title>Ethical Considerations</title><p>The North Texas Regional Institutional Review Board approved this study (number 2023&#x2010;151). This study followed the ethical standards of the responsible committee on human experimentation and the World Medical Association Declaration of Helsinki. All participants provided informed consent before participation. The survey was accessible only after consent was obtained. We collected responses anonymously and did not link any personally identifiable information to the survey data, ensuring privacy and confidentiality. Clinicians who completed the survey were entered into a draw for one of eight US $50 Walmart e-gift cards as compensation.</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><p>Our study population comprised 33 clinicians (12% of 284 eligible). Participant characteristics are summarized in <xref ref-type="supplementary-material" rid="app5">Multimedia Appendix 5</xref>. Most respondents were physicians (MD/DO, n=20, 61%), followed by nurse practitioners (n=10, 30%). The majority were older than 30 years (n=29, 88%), identified as female (n=23, 70%), and were non-Hispanic White (n=19, 58%).</p><p>Fewer than half of respondents (n=15, 45%) were aware of the updated sexual history questionnaire. <xref ref-type="table" rid="table1">Table 1</xref> summarizes awareness, use, and perceptions of the CDS tool among respondents who reported awareness of the tool. Most clinicians who reported awareness or use of the tool agreed that the questionnaire was important to implement (n=10, 67%), helpful for identifying PrEP candidates (n=9, 60%), and appropriate for primary care (n=9, 60%). In contrast, clinicians reported concerns about increased patient interaction time (n=9, 60%) and workflow fit (n=7, 47%). Most clinicians agreed that the PrEP advisory alert was appropriate for primary care (n=12, 78%) and supported guideline-concordant care (n=11, 73%), although fewer reported that the alert fit within clinical workflows (n=6, 40%).</p><p>Qualitative analysis of open-ended responses from 10 clinicians identified 5 themes: workflow disruption and time burden, alert fatigue, discomfort with the sexual history questionnaire, limited understanding of CDS functionality, and perceived usefulness for identifying at-risk patients. <xref ref-type="table" rid="table2">Table 2</xref> summarizes illustrative quotes from these themes.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Awareness, use, and perceptions of the CDS<sup><xref ref-type="table-fn" rid="table1fn1">a</xref></sup> tool among clinicians who completed both awareness and use questions (N=15).<sup><xref ref-type="table-fn" rid="table1fn2">b</xref></sup></p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="top"/><td align="left" valign="top">Median (IQR)</td><td align="left" valign="top">Agreement<sup><xref ref-type="table-fn" rid="table1fn3">c</xref></sup>, n (%)</td><td align="left" valign="top">Disagreement<sup><xref ref-type="table-fn" rid="table1fn3">c</xref></sup>, n (%)</td></tr></thead><tbody><tr><td align="left" valign="top" colspan="4">Clinician attitudes and perceptions of the sexual history questionnaire</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>I like this tool</td><td align="left" valign="top">3.0 (2.0&#x2010;4.0)</td><td align="left" valign="top">5 (33)</td><td align="left" valign="top">5 (33)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Suitable for my patients</td><td align="left" valign="top">4.0 (2.5&#x2010;4.0)</td><td align="left" valign="top">8 (53)</td><td align="left" valign="top">4 (27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>The tool is easy to use</td><td align="left" valign="top">3.0 (2.5&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">4 (27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Trust evidence quality and validity</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">9 (60)</td><td align="left" valign="top">2 (13)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Good option to identify sexual risk factors</td><td align="left" valign="top">3.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">2 (13)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Facilitates sexual history-taking</td><td align="left" valign="top">3.0 (2.0&#x2010;4.0)</td><td align="left" valign="top">6 (40)</td><td align="left" valign="top">6 (40)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Meets needs to provide resources to patients</td><td align="left" valign="top">3.0 (2.5&#x2010;4.0)</td><td align="left" valign="top">5 (33)</td><td align="left" valign="top">4 (27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Important to implement</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">10 (67)</td><td align="left" valign="top">1 (6.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Appropriate for primary care</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">9 (60)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Fits within workflow</td><td align="left" valign="top">3.0 (2.0&#x2010;4.0)</td><td align="left" valign="top">5 (33)</td><td align="left" valign="top">7 (47)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Does not increase patient time</td><td align="left" valign="top">2.0 (1.0&#x2010;3.0)</td><td align="left" valign="top">3 (20)</td><td align="left" valign="top">9 (60)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Easy to access and incorporate in workflow</td><td align="left" valign="top">3.0 (2.0&#x2010;4.0)</td><td align="left" valign="top">6 (40)</td><td align="left" valign="top">5 (33)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Valuable for primary care</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">10 (67)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Helps identify PrEP<sup><xref ref-type="table-fn" rid="table1fn4">d</xref></sup> candidates</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">9 (60)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top" colspan="4">Clinician attitudes and perceptions of the PrEP advisory alert</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>I like this alert</td><td align="left" valign="top">3.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">1 (6.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Suitable for my patients</td><td align="left" valign="top">3.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">2 (13)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Useful and actionable</td><td align="left" valign="top">3.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Trust evidence quality and validity</td><td align="left" valign="top">3.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (47)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Good for guideline-concordant care for PrEP</td><td align="left" valign="top">4.0 (3.5&#x2010;4.0)</td><td align="left" valign="top">11 (73)</td><td align="left" valign="top">0 (0)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Facilitates PrEP assessment</td><td align="left" valign="top">3.5 (3.0&#x2010;4.0)</td><td align="left" valign="top">7 (50)</td><td align="left" valign="top">2 (14)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Easy to access and incorporate in workflow</td><td align="left" valign="top">3.0 (2.5&#x2010;4.0)</td><td align="left" valign="top">6 (40)</td><td align="left" valign="top">4 (27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Appropriate for primary care</td><td align="left" valign="top">4.0 (4.0&#x2010;4.0)</td><td align="left" valign="top">12 (79)</td><td align="left" valign="top">0 (0)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Fits within existing workflow</td><td align="left" valign="top">3.0 (2.5&#x2010;4.0)</td><td align="left" valign="top">6 (40)</td><td align="left" valign="top">4 (27)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Does not increase patient time</td><td align="left" valign="top">2.0 (2.0&#x2010;3.0)</td><td align="left" valign="top">2 (13)</td><td align="left" valign="top">8 (53)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Adds value to practice</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">8 (53)</td><td align="left" valign="top">3 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Valuable for primary care</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">9 (64)</td><td align="left" valign="top">1 (6.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Helps identify PrEP candidates</td><td align="left" valign="top">4.0 (3.0&#x2010;4.0)</td><td align="left" valign="top">8 (53)</td><td align="left" valign="top">0 (0)</td></tr></tbody></table><table-wrap-foot><fn id="table1fn1"><p><sup>a</sup>CDS: clinical decision support.</p></fn><fn id="table1fn2"><p><sup>b</sup>Clinician level of awareness and use frequency of the sexual history questionnaire: n=6, 40% aware, no use; n=9, 60% aware, used at least once.</p></fn><fn id="table1fn3"><p><sup>c</sup>Agreement reflects &#x201C;agree&#x201D; or &#x201C;strongly agree.&#x201D; Disagreement reflects &#x201C;disagree&#x201D; or &#x201C;strongly disagree.&#x201D; Neutral responses were included in the denominator but not separately reported.</p></fn><fn id="table1fn4"><p><sup>d</sup>PrEP: pre-exposure prophylaxis.</p></fn></table-wrap-foot></table-wrap><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Themes and illustrative quotes from clinician responses to open-ended questions regarding the use of the clinical decision support tool (sexual history questionnaire and PrEP<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup> advisory alert).</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Theme</td><td align="left" valign="bottom">Illustrative quotes (participant ID)</td></tr></thead><tbody><tr><td align="left" valign="top">Concern about time and workflow</td><td align="left" valign="top"><list list-type="bullet"><list-item><p>The questionnaire is long; typical workflow is that MA [medical assistant] does questions, but then I do not see this information flagged for review if risks identified, so not sure if MA filling out correctly. (#3)</p></list-item><list-item><p>It does take some time to complete the advanced sexual history and can be cumbersome if patient has other medical issues to discuss. (#10)</p></list-item><list-item><p>Lack of time, patients and I both feel uncomfortable. I don&#x2019;t even know how to find the questionnaire and was not aware I should be using it. (#11)</p></list-item></list></td></tr><tr><td align="left" valign="top">Time and reducing alert fatigue as a facilitator</td><td align="left" valign="top"><list list-type="bullet"><list-item><p>If it doesn&#x2019;t increase time during visits. There are already so many screenings we are doing. Many of the patients have multiple comorbid conditions that take time to address. The language and cultural barrier all add up to long visit times. (#14)</p></list-item><list-item><p>Time. Along with all of the mandatory screening tools. I feel we &#x2018;screen&#x2019; our patients to death. (#2)</p></list-item><list-item><p>It might be easy to think that a BPA [Best Practice Alert] is helpful, and it may be, but we are subjected to easily 3 to 5 BPAs that each add minutes to our workflow for each patient we see. Please help us reduce time spent with a computer rather than add to it. (#15)</p></list-item></list></td></tr><tr><td align="left" valign="top">Patient and provider comfort and appropriateness as a barrier</td><td align="left" valign="top"><list list-type="bullet"><list-item><p>There needs to be some sensitivity in how the questions are asked for refugee patients. I mostly work with refugees who are low risk. (#14)</p></list-item><list-item><p>For the right patient history on initial screen this would be useful&#x2014;not on every patient. (#6)</p></list-item><list-item><p>This is not for every patient (#9)</p></list-item><list-item><p>This can [be a] very intrusive questionnaire (#2)</p></list-item></list></td></tr><tr><td align="left" valign="top">Training</td><td align="left" valign="top"><list list-type="bullet"><list-item><p>I have no experience prescribing PrEP and have not seen others do it. I feel uncomfortable with PreP. (#11)</p></list-item><list-item><p>Training on tool...to understand how it is triggered. (#3)</p></list-item></list></td></tr><tr><td align="left" valign="top">Perceived utility of tool</td><td align="left" valign="top"><list list-type="bullet"><list-item><p>The tool works well...if a patient is identified as being at risk for HIV based on the brief sexual screening, I use this tool. (#10)</p></list-item><list-item><p>I think it is a good tool; however, our patients complete many required screening tools every time they come to the office... (#11)</p></list-item><list-item><p>Useful for specific patients. (#6)</p></list-item></list></td></tr></tbody></table><table-wrap-foot><fn id="table2fn1"><p><sup>a</sup>PrEP: pre-exposure prophylaxis.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>Our findings suggest suboptimal awareness of the CDS tool among primary care clinicians, and uptake was limited even among clinicians who reported awareness. Clinicians who used the tool generally endorsed the value of the sexual history questionnaire and PrEP advisory alert but reported concerns regarding usability and workflow integration, particularly increased time burden during patient visits. Open-ended responses revealed workflow disruption, alert fatigue, discomfort with the sexual history questionnaire, and limited understanding of tool functionality.</p><p>Our findings should be considered in the context of a key limitation. Despite a structured reminder strategy, financial incentives, and peer-led outreach, only 12% of eligible clinicians completed the survey, and thus our findings are likely sensitive to selection bias. Low response proportions are a persistent challenge when using provider surveys and may reflect competing clinical demands or survey fatigue [<xref ref-type="bibr" rid="ref8">8</xref>]. We were unable to apply quantitative approaches to explore the effects of this selection bias [<xref ref-type="bibr" rid="ref9">9</xref>] because we lacked data about clinicians who did not respond to the survey. Nevertheless, we likely overestimated CDS tool awareness among our primary care clinicians, and responses among tool users likely reflect the perspectives of a highly select group of early adopters, which could overestimate favorable impressions of the CDS tool compared with the overall eligible population.</p><p>Despite the key limitation, our findings align with prior studies of CDS implementation in primary care [<xref ref-type="bibr" rid="ref10">10</xref>] that report low awareness and barriers related to workflow integration, time constraints, alert fatigue, and limited stakeholder engagement. Clinicians in our study endorsed the potential value of the CDS tool for identifying patients who may benefit from PrEP, but perceived workflow burdens may limit adoption. These findings reinforce the importance of aligning CDS tools with clinical workflows and eliciting postimplementation clinician feedback to improve the use of CDS tools.</p></sec></body><back><ack><p>The authors did not use generative artificial intelligence in the writing of this research letter. Open-ended survey responses were analyzed using conventional content analysis supported by a large language model (GPT-4) to identify recurring themes.</p></ack><notes><sec><title>Funding</title><p>This study received no external funding.</p></sec><sec><title>Data Availability</title><p>The datasets generated and analyzed during this study are available from the corresponding author on reasonable request.</p></sec></notes><fn-group><fn fn-type="con"><p>Conceptualization: AMA</p><p>Methodology: RPO, AMA, CTT, WL, JA, NL, EF</p><p>Investigation: AMA, CTT, WL</p><p>Data curation: AMA, WL, CTT, JA</p><p>Formal analysis: AMA, WL</p><p>Writing &#x2013; original draft: AMA</p><p>Writing &#x2013; review &#x0026; editing: RPO, AMA, CTT, WL, JA, NL, EF</p><p>Supervision: RPO, AMA</p><p>Project administration: AMA</p></fn><fn fn-type="conflict"><p>EF reports serving on an advisory board for Merck. 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Epic.</p><media xlink:href="formative_v10i1e89638_app1.docx" xlink:title="DOCX File, 1352 KB"/></supplementary-material><supplementary-material id="app2"><label>Multimedia Appendix 2</label><p>Survey measures mapped to implementation constructs by Weiner et al [<xref ref-type="bibr" rid="ref11">11</xref>] and the Consolidated Framework for Implementation Research (CFIR).</p><media xlink:href="formative_v10i1e89638_app2.docx" xlink:title="DOCX File, 19 KB"/></supplementary-material><supplementary-material id="app3"><label>Multimedia Appendix 3</label><p>Description of the survey instrument assessing clinician perceptions and use of the pre-exposure prophylaxis clinical decision support tool.</p><media xlink:href="formative_v10i1e89638_app3.docx" xlink:title="DOCX File, 28 KB"/></supplementary-material><supplementary-material id="app4"><label>Multimedia Appendix 4</label><p>ChatGPT input prompts used to support qualitative analysis.</p><media xlink:href="formative_v10i1e89638_app4.docx" xlink:title="DOCX File, 17 KB"/></supplementary-material><supplementary-material id="app5"><label>Multimedia Appendix 5</label><p>Characteristics of primary care clinicians who responded to a survey on an electronic health record&#x2013;based clinical decision support tool for pre-exposure prophylaxis, stratified by awareness of the intervention.</p><media xlink:href="formative_v10i1e89638_app5.docx" xlink:title="DOCX File, 19 KB"/></supplementary-material></app-group></back></article>