{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T16:08:44Z","timestamp":1785514124287,"version":"3.56.0"},"reference-count":37,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Remote patient monitoring (RPM), including self-measured blood pressure monitoring with clinician review and telehealth-supported feedback, can support hypertension management. However, RPM use and related care continuity after switching from Medicare fee-for-service (FFS) to Medicare Advantage (MA) remain unclear.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To compare RPM adoption, clinician continuity, and hypertension-related acute care utilization among beneficiaries who remained in Medicare FFS vs switched to MA plans, categorized as value-based contract (VBC) proxy or non-VBC.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This cohort study with an observational difference-in-differences design with propensity score matching used data from 2016 to 2022 Medicare enrollment, FFS claims, and MA encounter data. Beneficiaries were aged 65 years or older with prevalent diagnosed hypertension in 2018 and continuous enrollment in Parts A and B in 2018. Treated groups switched from FFS to MA in January 2019 and remained enrolled through 2022; comparators remained in FFS. Follow-up extended from January 1, 2019, through December 31, 2022. Data analysis was conducted from April to July 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposure<\/jats:title>\n Switching from Medicare FFS to MA-VBC proxy or MA non-VBC in 2019.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The primary outcome was annual RPM adoption during hypertension-related visits; secondary outcomes included clinician loss without replacement, clinician switching or substitution, and hypertension-related emergency department (ED) visits and hospitalizations.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Matched samples included 281\u202f620 beneficiaries, with 46\u202f833 MA-VBC proxy plan switchers and 46\u202f833 FFS comparators (27\u202f920 [59.6%] aged 71 years or older and 27\u202f685 female [59.1%] in each group) and 93\u202f977 MA non-VBC switchers and 93\u202f977 FFS comparators (67\u202f188 [71.5%] aged 71 years or older; 53\u202f122 female [56.5%] in each group). Common comorbidities included diabetes, chronic kidney disease, and heart failure. Switching to MA was associated with lower RPM adoption in 2022 (MA-VBC proxy: odds ratio [OR], 0.55; 95% CI, 0.42-0.72; \u22120.63 percentage points; non-VBC: OR, 0.73; 95% CI, 0.54-0.99; \u22120.52 percentage points), greater clinician loss without replacement (MA-VBC proxy: OR, 1.27; 95% CI, 1.23-1.32; 3.41 percentage points; MA non-VBC: OR, 1.09; 95% CI, 1.06-1.12; 0.83 percentage points), and higher hypertension-related hospitalizations (MA-VBC proxy: OR, 1.75; 95% CI, 1.48-2.06; MA non-VBC: OR, 1.94; 95% CI 1.71-2.19; 1.56 percentage points in both comparisons). Event-study analyses showed postswitch divergence through 2022.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cohort study of older Medicare beneficiaries with hypertension, switching from FFS to MA was associated with lower RPM adoption, greater clinician discontinuity, and higher hypertension-related acute care use. These findings suggest that continuity safeguards and clearer payment or quality incentives during MA transitions may support remote monitoring and clinician follow-up for hypertension.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.26522","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T15:30:19Z","timestamp":1785511819000},"page":"e2626522","source":"Crossref","is-referenced-by-count":0,"title":["Remote Patient Monitoring Adoption for Hypertension Management Among Medicare Beneficiaries"],"prefix":"10.1001","volume":"9","author":[{"given":"Donglan S.","family":"Zhang","sequence":"first","affiliation":[{"name":"Division of Health Services Research, Department of Foundations of Medicine, New York University Grossman Long Island School of Medicine, Mineola"},{"name":"Department of Population Health, New York University Grossman School of Medicine, New 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and Prevention, Atlanta, Georgia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiling","family":"Ying","sequence":"additional","affiliation":[{"name":"Division of Health Services Research, Department of Foundations of Medicine, New York University Grossman Long Island School of Medicine, Mineola"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Johns Hopkins University School of Public Health, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoinette M.","family":"Schoenthaler","sequence":"additional","affiliation":[{"name":"Department of Population Health, New York University Grossman School of Medicine, New York"},{"name":"Institute for Excellence in Health Equity, New York University Langone Health, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharine","family":"Lawrence","sequence":"additional","affiliation":[{"name":"Department of Population Health, New York University Grossman School of Medicine, New York"},{"name":"Department of Medicine, New York University Grossman School of Medicine, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Devin","family":"Mann","sequence":"additional","affiliation":[{"name":"Department of Population Health, New York University Grossman School of Medicine, New York"},{"name":"Department of Medicine, New York University Grossman School of Medicine, New York"},{"name":"Medical Center Information Technology, New York University Langone Health, New 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