Evidence map›Paper›PMID 31304346›Full record

ReviewNPJ digital medicine2018

Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials.

Benjamin Noah, Michelle S Keller, Sasan Mosadeghi, Libby Stein, Sunny Johl, Sean Delshad, Vartan C Tashjian, Daniel Lew, James T Kwan, Alma Jusufagic and 1 more

Erratum issuedOpen access · hybridAbstract readReview
In one paragraph

Review in NPJ digital medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 140 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
140citing papers in PubMed, 7 pooled it
42.3field-weighted citation impact, top 1% of its field
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

140 citing papers in PubMed, 7 syntheses or guidelines pooled it, 276 citations in OpenAlex.

  1. Pooled it
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  6. Remote symptom monitoring integrated into electronic health records: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020
    Pooled it
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  15. Observational
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80 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Benjamin Noah1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Michelle S Keller1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Sasan Mosadeghi4Department of Medicine, University of Arizona, College of Medicine Tucson, Tucson, AZ USA.
Libby Stein1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Sunny Johl1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Sean Delshad1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Vartan C Tashjian1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Daniel Lew1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
James T Kwan1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Alma Jusufagic1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Brennan M R Spiegel1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Cedars-Sinai Medical Center · USUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite growing interest in remote patient monitoring, limited evidence exists to substantiate claims of its ability to improve outcomes. Our aim was to evaluate randomized controlled trials (RCTs) that assess the effects of using wearable biosensors (e.g. activity trackers) for remote patient monitoring on clinical outcomes. We expanded upon prior reviews by assessing effectiveness across indications and presenting quantitative summary data. We searched for articles from January 2000 to October 2016 in PubMed, reviewed 4,348 titles, selected 777 for abstract review, and 64 for full text review. A total of 27 RCTs from 13 different countries focused on a range of clinical outcomes and were retained for final analysis; of these, we identified 16 high-quality studies. We estimated a difference-in-differences random effects meta-analysis on select outcomes. We weighted the studies by sample size and used 95% confidence intervals (CI) around point estimates. Difference-in-difference point estimation revealed no statistically significant impact of remote patient monitoring on any of six reported clinical outcomes, including body mass index (-0.73; 95% CI: -1.84, 0.38), weight (-1.29; -3.06, 0.48), waist circumference (-2.41; -5.16, 0.34), body fat percentage (0.11; -1.56, 1.34), systolic blood pressure (-2.62; -5.31, 0.06), and diastolic blood pressure (-0.99; -2.73, 0.74). Studies were highly heterogeneous in their design, device type, and outcomes. Interventions based on health behavior models and personalized coaching were most successful. We found substantial gaps in the evidence base that should be considered before implementation of remote patient monitoring in the clinical setting.

Indexed as

Disease preventionHealth servicesWeight management

Identifiers

PMID31304346
PMCPMC6550143
OpenAlexW2771061271

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.