Literature DB >> 27920321

Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain.

Karandeep Singh1, Kaitlin Drouin2, Lisa P Newmark3, JaeHo Lee4, Arild Faxvaag5, Ronen Rozenblum6, Erika A Pabo7, Adam Landman8, Elissa Klinger9, David W Bates10.   

Abstract

With rising smartphone ownership, mobile health applications (mHealth apps) have the potential to support high-need, high-cost populations in managing their health. While the number of available mHealth apps has grown substantially, no clear strategy has emerged on how providers should evaluate and recommend such apps to patients. Key stakeholders, including medical professional societies, insurers, and policy makers, have largely avoided formally recommending apps, which forces patients to obtain recommendations from other sources. To help stakeholders overcome barriers to reviewing and recommending apps, we evaluated 137 patient-facing mHealth apps-those intended for use by patients to manage their health-that were highly rated by consumers and recommended by experts and that targeted high-need, high-cost populations. We found that there is a wide variety of apps in the marketplace but that few apps address the needs of the patients who could benefit the most. We also found that consumers' ratings were poor indications of apps' clinical utility or usability and that most apps did not respond appropriately when a user entered potentially dangerous health information. Going forward, data privacy and security will continue to be major concerns in the dissemination of mHealth apps. Project HOPE—The People-to-People Health Foundation, Inc.

Entities:  

Keywords:  Chronic Care; Consumer Issues; High-need; Mobile health; Patient engagement; high-cost populations

Mesh:

Year:  2016        PMID: 27920321     DOI: 10.1377/hlthaff.2016.0578

Source DB:  PubMed          Journal:  Health Aff (Millwood)        ISSN: 0278-2715            Impact factor:   6.301


  61 in total

1.  A Clinically Integrated mHealth App and Practice Model for Collecting Patient-Reported Outcomes between Visits for Asthma Patients: Implementation and Feasibility.

Authors:  Robert S Rudin; Christopher H Fanta; Nabeel Qureshi; Erin Duffy; Maria O Edelen; Anuj K Dalal; David W Bates
Journal:  Appl Clin Inform       Date:  2019-10-16       Impact factor: 2.342

2.  Advancing science and practice using immersive virtual reality: what behavioral medicine has to offer.

Authors:  Susan Persky; Megan A Lewis
Journal:  Transl Behav Med       Date:  2019-11-25       Impact factor: 3.046

3.  Mobile apps for mood tracking: an analysis of features and user reviews.

Authors:  Clara Caldeira; Yu Chen; Lesley Chan; Vivian Pham; Yunan Chen; Kai Zheng
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

4.  Trends in user ratings and reviews of a popular yet inaccurate blood pressure-measuring smartphone app.

Authors:  Timothy B Plante; Anna C O'Kelly; Zane T Macfarlane; Bruno Urrea; Lawrence J Appel; Edgar R Miller Iii; Roger S Blumenthal; Seth S Martin
Journal:  J Am Med Inform Assoc       Date:  2018-08-01       Impact factor: 4.497

5.  Patients' and Nephrologists' Evaluation of Patient-Facing Smartphone Apps for CKD.

Authors:  Karandeep Singh; Clarissa J Diamantidis; Shreyas Ramani; Nrupen A Bhavsar; Peter Mara; Julia Warner; Jorge Rodriguez; Tianshi Wang; Julie Wright-Nunes
Journal:  Clin J Am Soc Nephrol       Date:  2019-03-21       Impact factor: 8.237

6.  Cognitive-Behavioral Therapy in the Digital Age: Presidential Address.

Authors:  Sabine Wilhelm; Hilary Weingarden; Ilana Ladis; Valerie Braddick; Jin Shin; Nicholas C Jacobson
Journal:  Behav Ther       Date:  2019-08-08

7.  Assessing the Public Health Impact of the mHealth App Business.

Authors:  Nicholas Freudenberg
Journal:  Am J Public Health       Date:  2017-11       Impact factor: 9.308

8.  The Spanish Availability and Readability of Diabetes Apps.

Authors:  Jorge A Rodriguez; Karandeep Singh
Journal:  J Diabetes Sci Technol       Date:  2018-01-02

9.  Development and Feasibility of Self-Management Application in Left-Ventricular Assist Devices.

Authors:  Jesus M Casida; James E Aikens; Heidi Craddock; Matthew W Aldrich; Francis D Pagani
Journal:  ASAIO J       Date:  2018 Mar/Apr       Impact factor: 2.872

10.  Core Components for a Clinically Integrated mHealth App for Asthma Symptom Monitoring.

Authors:  Robert S Rudin; Christopher H Fanta; Zachary Predmore; Kevin Kron; Maria O Edelen; Adam B Landman; Eyal Zimlichman; David W Bates
Journal:  Appl Clin Inform       Date:  2017-12-14       Impact factor: 2.342

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