Evidence map›Paper›PMID 26788432›Full record

ArticlePeerJ2016

A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

Cinnamon S Bloss, Nathan E Wineinger, Melissa Peters, Debra L Boeldt, Lauren Ariniello, Ju Young Kim, Judith Sheard, Ravi Komatireddy, Paddy Barrett, Eric J Topol

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 4 pooled it
34.6field-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

46 citing papers in PubMed, 4 syntheses or guidelines pooled it, 96 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Remote Patient Monitoring via Non-Invasive Digital Technologies: A Systematic Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2017
    Pooled it
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Article
  10. Review
  11. Article
  12. Article
  13. Evaluation of the Effectiveness of the Mobile Application on Adherence of Patients With Arterial Hypertension.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2022
    Article
  14. Current and Potential Applications of Wearables in Sports Cardiology.Current treatment options in cardiovascular medicine · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. The Doctor Will Call You Now! Telemedicine in the Midst of a Pandemic.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2020
    Article
  19. Contribution of telemedicine and information technology to hypertension control.Hypertension research : official journal of the Japanese Society of Hypertension · 2020
    Review
  20. Article
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

10 authors at 3 institutions in 2 countries.

Cinnamon S Bloss *Scripps Translational Science Institute, La Jolla, California, United States.
Nathan E Wineinger *Scripps Translational Science Institute, La Jolla, California, United States.
Melissa PetersScripps Translational Science Institute, La Jolla, California, United States.
Debra L BoeldtScripps Translational Science Institute, La Jolla, California, United States.
Lauren ArinielloScripps Translational Science Institute, La Jolla, California, United States.
Ju Young KimDepartment of Family Medicine, Seoul National University Bundang Hospital, Seoul, South Korea.
Judith SheardScripps Translational Science Institute, La Jolla, California, United States.
Ravi KomatireddyScripps Translational Science Institute, La Jolla, California, United States.
Paddy BarrettScripps Translational Science Institute, La Jolla, California, United States.
Eric J TopolScripps Translational Science Institute, La Jolla, California, United States.
Scripps Research Institute · USScripps Health · USSeoul National University Bundang Hospital · KR

Funding

Scripps Translational Science InstituteUL1TR001114 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2013 to 2017
$24.0M
NCATS NIH HHS UL1 TR001114
6 · The paper itself

Abstract

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers-some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program-making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.

Indexed as

ArrhythmiaDiabetesDigital medicineHealth insurance claimsHealth monitoringHypertensionMobile health

Identifiers

PMID26788432
PMCPMC4715435
OpenAlexW2949426068

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.