Evidence map›Paper›PMID 31512582›Full record

ArticleJMIR mHealth and uHealth2019

Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions.

Catherine Dinh-Le, Rachel Chuang, Sara Chokshi, Devin Mann

Open access · goldAbstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
168citing papers in PubMed, 9 pooled it
56.3field-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

168 citing papers in PubMed, 9 syntheses or guidelines pooled it, 394 citations in OpenAlex.

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  5. Effect of mobile application types on stroke rehabilitation: a systematic review.Journal of neuroengineering and rehabilitation · 2023
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  8. A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities.International journal of environmental research and public health · 2022
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  9. Remote symptom monitoring integrated into electronic health records: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020
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108 more citing papers are in PubMed but not listed here.

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

4 authors at 2 institutions in 1 country.

Catherine Dinh-Le *Department of Population Health, New York University School of Medicine, New York, NY, United States.ORCID 0000-0001-7885-6536
Rachel Chuang *Accenture, New York, NY, United States.ORCID 0000-0002-9564-3660
Sara Chokshi *Department of Population Health, New York University School of Medicine, New York, NY, United States.ORCID 0000-0002-3952-6654
Devin Mann *Department of Population Health, New York University School of Medicine, New York, NY, United States.ORCID 0000-0002-2099-0852
New York University · USAccenture (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR capabilities, offerings, and innovations to better capture patient data. A novel capability offered by health systems encompasses the integration between EHRs and wearable health technology. Although wearables have the potential to transform patient care, issues such as concerns with patient privacy, system interoperability, and patient data overload pose a challenge to the adoption of wearables by providers.

objectiveThis study aimed to review the landscape of wearable health technology and data integration to provider EHRs, specifically Epic, because of its prevalence among health systems. The objectives of the study were to (1) identify the current innovations and new directions in the field across start-ups, health systems, and insurance companies and (2) understand the associated challenges to inform future wearable health technology projects at other health organizations.

methodsWe used a scoping process to survey existing efforts through Epic's Web-based hub and discussion forum, UserWeb, and on the general Web, PubMed, and Google Scholar. We contacted Epic, because of their position as the largest commercial EHR system, for information on published client work in the integration of patient-collected data. Results from our searches had to meet criteria such as publication date and matching relevant search terms.

resultsNumerous health institutions have started to integrate device data into patient portals. We identified the following 10 start-up organizations that have developed, or are in the process of developing, technology to enhance wearable health technology and enable EHR integration for health systems: Overlap, Royal Philips, Vivify Health, Validic, Doximity Dialer, Xealth, Redox, Conversa, Human API, and Glooko. We reported sample start-up partnerships with a total of 16 health systems in addressing challenges of the meaningful use of device data and streamlining provider workflows. We also found 4 insurance companies that encourage the growth and uptake of wearables through health tracking and incentive programs: Oscar Health, United Healthcare, Humana, and John Hancock.

conclusionsThe future design and development of digital technology in this space will rely on continued analysis of best practices, pain points, and potential solutions to mitigate existing challenges. Although this study does not provide a full comprehensive catalog of all wearable health technology initiatives, it is representative of trends and implications for the integration of patient data into the EHR. Our work serves as an initial foundation to provide resources on implementation and workflows around wearable health technology for organizations across the health care industry.

Indexed as

Biomedical TechnologyData CollectionElectronic Health RecordsHumansWearable Electronic Devicesdata collectionelectronic health recordsmobile healthpatient monitoringwearable electronic devices

Identifiers

PMID31512582
PMCPMC6746089
OpenAlexW2964331637

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.