Evidence map›Paper›PMID 40827414›Full record

ArticleCirculation. Cardiovascular quality and outcomes2025

National Patterns of Remote Patient Monitoring Service Availability at US Hospitals.

Aline F Pedroso, Zhenqiu Lin, Joseph S Ross, Rohan Khera

Abstract read
In one paragraph

Article in Circulation. Cardiovascular quality and outcomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Aline F PedrosoSection of Cardiovascular Medicine, Department of Internal Medicine (A.F.P., Z.L., J.S.R., R.K.), Yale School of Medicine, New Haven, CT.ORCID 0000-0002-1876-8304
Zhenqiu LinSection of Cardiovascular Medicine, Department of Internal Medicine (A.F.P., Z.L., J.S.R., R.K.), Yale School of Medicine, New Haven, CT.
Joseph S RossSection of Cardiovascular Medicine, Department of Internal Medicine (A.F.P., Z.L., J.S.R., R.K.), Yale School of Medicine, New Haven, CT.ORCID 0000-0002-9218-3320
Rohan KheraSection of Cardiovascular Medicine, Department of Internal Medicine (A.F.P., Z.L., J.S.R., R.K.), Yale School of Medicine, New Haven, CT.ORCID 0000-0001-9467-6199

Funding

Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS StudyR01AG089981 · NIA · YALE UNIVERSITY · PI Rohan Khera · 2024 to 2026
$2.4M
Translating Personalized Inference from Randomized Clinical Trials to Real-World Cardiovascular CareR01HL167858 · NHLBI · YALE UNIVERSITY · PI Rohan Khera · 2024 to 2026
$2.3M
Evaluating and Improving Utilization of Evidence-Based Medical Therapy in Patients with Heart Failure using Automated Tools in the Electronic Health RecordK23HL153775 · NHLBI · YALE UNIVERSITY · PI KHERA, ROHAN · 2021 to 2025
$918k
AHRQ HHS R01 HS022882NHLBI NIH HHS K23 HL153775NHLBI NIH HHS R01 HL167858NIA NIH HHS R01 AG089981
6 · The paper itself

Abstract

backgroundDigital remote patient monitoring (RPM), such as home-based blood pressure, heart rate, or weight monitoring, enables longitudinal care outside traditional health care settings, especially in the vulnerable period after hospitalizations, with broad coverage of the service by payers. We sought to evaluate patterns of RPM service availability at US hospitals and the characteristics of hospitals and the counties they serve that are associated with the availability of these services.

methodsWe used national data from the American Hospital Association Annual Survey from 2018 to 2022 to ascertain US hospitals offering RPM services for postdischarge or chronic care. We linked hospitals with their census-based county-level data to define the characteristics of the counties they serve, including sociodemographic features such as age distribution, racial/ethnic composition, median household income, education level, and disability status. We used multivariable logistic regression to assess associations between hospital- and county-level characteristics and RPM availability, adjusting for hospital size, region, teaching status, and ownership.

resultsThe study included 5644 hospitals. Over 5 years of study, there was a 40.3% increase in the number of hospitals offering RPM services, rising from 1364 (33.0%) hospitals in 2018 to 1797 (46.3%) in 2022. In 2022, hospitals with >300 beds had 3.7-fold odds of offering RPM compared with those with <100 beds (adjusted odds ratio, 3.71 [95% CI, 2.90-4.74]). Nonteaching hospitals had lower odds of RPM availability than teaching hospitals (adjusted odds ratio, 0.29 [95% CI, 0.19-0.44]), and rural hospitals had lower odds than urban hospitals (adjusted odds ratio, 0.49 [95% CI, 0.32-0.77]).

conclusionsIn this national study of US hospitals, there has been a large increase in the availability of RPM services but with large variation among hospitals, with lower availability in hospitals serving low-income and rural counties.

Indexed as

Health Services AccessibilityHospitalsTelemedicineTelemetryHealthcare DisparitiesHealth Care SurveysHumansRemote Patient MonitoringTime FactorsUnited StatesAmerican Hospital Associationdigital healthhealth devicespatient monitoring

Identifiers

PMID40827414
PMCPMC12367071

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.