Evidence map›Paper›PMID 40570326›Full record

ArticleJournal of medical Internet research2025

The State of Remote Patient Monitoring for Chronic Disease Management in the United States.

Margaret M Paul, Nandita Khera, Praneetha R Elugunti, Kevin C Ruff, Musab S Hommos, Leslie F Thomas, Vivek Nagaraja, Ashley L Garrett, Mari Pantoja-Smith, Nathan L Delafield and 5 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Margaret M PaulMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0003-3281-6234
Nandita KheraMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0002-0577-3155
Praneetha R EluguntiMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0003-3956-9328
Kevin C RuffMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0002-6278-5363
Musab S HommosMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0003-2697-4463
Leslie F ThomasMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0009-0002-2413-1374
Vivek NagarajaMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0002-4930-3200
Ashley L GarrettMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0009-0001-4587-9288
Mari Pantoja-SmithMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0009-0004-4955-6066
Nathan L DelafieldMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0009-0005-9695-710X
Blanca C Lizaola-MayoMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0003-0130-0091
Molly M KresinMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0002-0842-3695
Mahesh SeetharamMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0001-9201-6840
Sandhya R NagarakantiMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0000-0001-7587-7569
Manreet KaurMayo Clinic in Arizona, Phoenix, AZ, United States.ORCID https://orcid.org/0009-0004-8264-6848

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remote patient monitoring (RPM) increased exponentially during the COVID-19 pandemic. RPM programs commonly incorporate tools to capture and transmit health-relevant data from the home to the clinical space to augment the clinical decision-making process of health care providers. Given the potential to improve patient health outcomes, health care systems around the world are actively engaged in fashioning, implementing, and exploring the outcomes of various RPM program models. However, new challenges to health care systems include increasing RPM program enrollment, optimizing condition-specific RPM programs to best address the needs of specific patient groups, integrating new RPM-derived data streams into existing IT infrastructure, overcoming limited availability of desired remote monitoring technologies, and quantifying the health outcomes produced by RPM use. Herein, we identify stakeholders for RPM in the United States, summarize the landscape of RPM tools available for chronic disease management, discuss the current regulatory environment, delve into the benefits and challenges of integrating these tools into clinical practice, summarize aspects of coverage and reimbursement, and examine the knowledge and policy gaps regarding sustained use of RPM in clinical practice, along with associated opportunities.

Indexed as

TelemedicineChronic DiseaseCOVID-19Disease ManagementHumansMonitoring, PhysiologicPandemicsRemote Patient MonitoringSARS-CoV-2United Stateschronic diseasechronic disease managementhealth information systemsreimbursement mechanismsremote patient monitoringtelemedicine

Identifiers

PMID40570326
PMCPMC12246758

What OpenQuestion holds

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Registered trials

None linked

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.