Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials
Authors: Libby Stein
Brennan M R Spiegel
James T Kwan
Michelle S Keller
Sean Delshad
Vartan C Tashjian
Benjamin Noah
Sasan Mosadeghi
Daniel Lew
Alma Jusufagic
Sunny Johl
Journal: npj Digital Medicine (2018)
Discipline: CLINICAL MEDICINE
Keywords: Disease prevention; Health services; Weight management.
Affiliations: 1Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, CA USA., Cedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, CA USA., 3Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA USA., 4Department of Medicine, University of Arizona, College of Medicine Tucson, Tucson, AZ USA., 5Cedars-Sinai Medical Center, Los Angeles, CA USA., American Journal of Gastroenterology, Bethesda, USA.

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. 

Retracted: No

PubPeer comments:
 Correction to: npj Digital Medicine 1:2; https: doi.org 10.1038 s41746-017-0002-4, published online 15 January 2018 The original version of this Review Article contained calculation errors within the abstract: u201cBody mass index (u22120.96; 95% CI: u22122.30, 0.37)u201d has been corrected to u201cBody mass index (u22120.73; 95% CI: u22121.84, 0.38)u201d, u201cBMI I2 statistic 92% (95% Confidence Interval: [82%, 96%]u201d was corrected to u201cBMI I2 statistic 92% (95% Confidence Interval: [83%, 96%]u201d, u201cbody fat percentage (0.19; u22121.2,1.57)u201d has been corrected to u201cbody fat percentage (u22120.11; u22121.56, 1.34)u201d, I2 statistic 85% (95% [56%, 95%])u201d was corrected to u201cbody fat u201cI2 statistic 86% (95% [59%, 95%])u201d, and u201cdiastolic blood pressure (u22120.74; u22122.34, 0.86)u201d has been corrected to u201cdiastolic blood pressure (u22120.99; u22122.73, 0.74)u201d, u201cdiastolic blood pressure I2 statistic 28% (95% [0%, 73%])u201d has been changed to u201cdiastolic blood pressure I2 statistic 44% (95% [0%, 81%])u201d. These corrections have been repeated in the results section and Figs. 2, 5 and 7. Via: https: www.nature.com articles s41746-018-0027-3 ,