{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T01:36:08Z","timestamp":1775180168558,"version":"3.50.1"},"reference-count":34,"publisher":"American Medical Association (AMA)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Intern Med"],"published-print":{"date-parts":[[2024,10,1]]},"abstract":"<jats:sec id=\"ab-ioi240050-4\"><jats:title>Importance<\/jats:title><jats:p>Clinicians are a key component of preexposure prophylaxis (PrEP) care. Yet, no prior studies have quantitatively investigated how PrEP adherence differs by clinician specialty.<\/jats:p><\/jats:sec><jats:sec id=\"ab-ioi240050-5\"><jats:title>Objective<\/jats:title><jats:p>To understand the association between prescribing clinician specialty and patients not picking up (reversal\/abandonment) their initial PrEP prescription.<\/jats:p><\/jats:sec><jats:sec id=\"ab-ioi240050-6\"><jats:title>Design, Setting, and Participants<\/jats:title><jats:p>This cross-sectional study of patients who were 18 years or older used pharmacy claims data from 2015 to 2019 on new insurer-approved PrEP prescriptions that were matched with clinician data from the US National Plan and Provider Enumeration System. Data were analyzed from January to May 2022.<\/jats:p><\/jats:sec><jats:sec id=\"ab-ioi240050-7\"><jats:title>Main Outcomes and Measures<\/jats:title><jats:p>Clinician specialties included primary care practitioners (PCPs), infectious disease (ID), or other specialties. Reversal was defined as a patient not picking up their insurer-approved initial PrEP prescription. Abandonment was defined as a patient who reversed and still did not pick their prescription within 365 days.<\/jats:p><\/jats:sec><jats:sec id=\"ab-ioi240050-8\"><jats:title>Results<\/jats:title><jats:p>Of the 37\u202f003 patients, 4439 (12%) were female and 32\u202f564 (88%) were male, and 77% were aged 25 to 54 years. A total of 24\u202f604 (67%) received prescriptions from PCPs, 3571 (10%) from ID specialists, and 8828 (24%) from other specialty clinicians. The prevalence of reversals for patients of PCPs, ID specialists, and other specialty clinicians was 18%, 18%, and 25%, respectively, and for abandonments was 12%, 12%, and 20%, respectively. After adjusting for confounding, logistic regression models showed that, compared with patients who were prescribed PrEP by a PCP, patients prescribed PrEP by ID specialists had 10% lower odds of reversals (odds ratio [OR], 0.90; 95% CI, 0.81-0.99) and 12% lower odds of abandonment (OR, 0.88; 95% CI, 0.78-0.98), while patients prescribed by other clinicians had 33% higher odds of reversals (OR, 1.33; 95% CI, 1.25-1.41) and 54% higher odds of abandonment (OR, 1.54; 95% CI, 1.44-1.65).<\/jats:p><\/jats:sec><jats:sec id=\"ab-ioi240050-9\"><jats:title>Conclusion<\/jats:title><jats:p>The results of this cross-sectional study suggest that PCPs do most of the new PrEP prescribing and are a critical entry point for patients. PrEP adherence differs by clinician specialties, likely due to the populations served by them. Future studies to test interventions that provide adherence support and education are needed.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamainternmed.2024.3998","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T15:04:21Z","timestamp":1724079861000},"page":"1204","source":"Crossref","is-referenced-by-count":10,"title":["Clinician Specialty and HIV PrEP Prescription Reversals and Abandonments"],"prefix":"10.1001","volume":"184","author":[{"given":"Shivani","family":"Bakre","sequence":"first","affiliation":[{"name":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsien-Yen","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jalpa A.","family":"Doshi","sequence":"additional","affiliation":[{"name":"Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William C.","family":"Goedel","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parya","family":"Saberi","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of California, San Francisco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip A.","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of Medicine, Brown University and Rhode Island Public Health Institute, Providence, Rhode 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