{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T23:45:17Z","timestamp":1793144717437,"version":"4.5.0"},"reference-count":59,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"<jats:sec><jats:title>Importance<\/jats:title><jats:p>More than 30% of pregnant people have at least 1 chronic medical condition, and nearly 20% develop gestational diabetes or pregnancy-related hypertension, increasing the risk of future chronic disease. While these individuals are often monitored closely during pregnancy, they face major barriers when transitioning to primary care following delivery, due in part to a lack of health care support for this transition.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>To evaluate the impact of an intervention designed to improve postpartum primary care engagement by reducing patient administrative burden and information gaps.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design, Setting, and Participants<\/jats:title><jats:p>An individual-level randomized clinical trial was conducted from November 3, 2022, to October 11, 2023, at 1 hospital-based and 5 community-based outpatient obstetric clinics affiliated with a large academic medical center. Participants included English- and Spanish-speaking pregnant or recently postpartum adults with obesity, anxiety, depression, diabetes, chronic hypertension, gestational diabetes, or pregnancy-related hypertension and a primary care practitioner (PCP) listed in their electronic health record.<\/jats:p><\/jats:sec><jats:sec><jats:title>Intervention<\/jats:title><jats:p>A behavioral economics\u2013informed intervention bundle, including default scheduling of postpartum PCP appointments and tailored messages.<\/jats:p><\/jats:sec><jats:sec><jats:title>Main Outcome and Measures<\/jats:title><jats:p>Completion of a PCP visit for routine or chronic condition care within 4 months of delivery was the primary outcome, ascertained directly by reviewing the patient\u2019s electronic health record approximately 5 months after their estimated due date. Intention-to-treat analysis was conducted.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 360 patients were randomized (control,\u2009176; intervention, 184). Individuals had a mean (SD) age of 34.1 (4.9) years and median gestational age of 36.3 (IQR, 34.0-38.6) weeks at enrollment. The distribution of self-reported race and ethnicity was 6.8% Asian, 7.4% Black, 68.6% White, and 15.0% multiple races or other. Most participants (75.4%) had anxiety or depression, 16.1% had a chronic or pregnancy-related hypertensive disorder, 19.5% had preexisting or gestational diabetes, and 40.8% had a prepregnancy body mass index of 30 or greater. Medicaid was the primary payer for 21.2% of patients. Primary care practitioner visit completion within 4 months occurred in 22.0% (95% CI, 6.4%-28.8%) of individuals in the control group and 40.0% (95% CI, 33.1%-47.4%) in the intervention group. In regression models accounting for randomization strata, the intervention increased PCP visit completion by 18.7 percentage points (95% CI, 9.1-28.2 percentage points). Intervention participants also had fewer postpartum readmissions (1.7% vs 5.8%) and increased receipt of the following services by a PCP: blood pressure screening (42.8% vs 28.3%), weight assessment (42.8% vs 27.7%), and depression screening (32.8% vs 16.8%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions and Relevance<\/jats:title><jats:p>The findings of this randomized clinical trial suggest that the current lack of support for postpartum transitions to primary care is a missed opportunity to improve recently pregnant individual\u2019s short- and long-term health. Reducing patient administrative burdens may represent relatively low-resource, high-impact approaches to improving postpartum health and well-being.<\/jats:p><\/jats:sec><jats:sec><jats:title>Trial Registration<\/jats:title><jats:p>ClinicalTrials.gov Identifier: <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/classic.clinicaltrials.gov\/ct2\/show\/NCT05543265\">NCT05543265<\/jats:ext-link><\/jats:p><\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2024.22500","type":"journal-article","created":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T16:09:21Z","timestamp":1721146161000},"page":"e2422500","source":"Crossref","is-referenced-by-count":29,"title":["Postpartum Primary Care Engagement Using Default Scheduling and Tailored Messaging"],"prefix":"10.1001","volume":"7","author":[{"given":"Mark A.","family":"Clapp","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston"},{"name":"Harvard Medical School, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alaka","family":"Ray","sequence":"additional","affiliation":[{"name":"Harvard Medical School, Boston, Massachusetts"},{"name":"Department of Medicine, Massachusetts General Hospital, Boston"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pichliya","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaitlyn E.","family":"James","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston"},{"name":"Harvard Medical School, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ishani","family":"Ganguli","sequence":"additional","affiliation":[{"name":"Harvard Medical School, Boston, Massachusetts"},{"name":"Department of Medicine, Brigham & Women\u2019s Hospital, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica L.","family":"Cohen","sequence":"additional","affiliation":[{"name":"Department of Global Health and Population, Harvard T. 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