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Cited by 33Mobile Health and mHealth ApplicationsElectronic Health Records SystemsTechnology Use by Older Adults

Sharing patient-generated data with healthcare providers: findings from a 2019 national survey

Open access
Turner, Kea, Jo, Ara, Wei, Grace, Tabriz, Amir Alishahi, Clary, Alecia, Jim, Heather S L·2021·Journal of the American Medical Informatics Association
DOI 10.1093/jamia/ocaa272PMC PMC7883987
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Abstract

Objective: Our study estimates the prevalence and predictors of wearable device adoption and data sharing with healthcare providers in a nationally representative sample. Materials and Methods: Data were obtained from the 2019 Health Information National Trend Survey. We conducted multivariable logistic regression to examine predictors of device adoption and data sharing. Results: The sample contained 4159 individuals, 29.9% of whom had adopted a wearable device in 2019. Among adopters, 46.3% had shared data with their provider. Individuals with diabetes (odds ratio [OR], 2.39; 95% CI, 1.66–3.45; P < .0001), hypertension (OR, 2.80; 95% CI, 2.12–3.70; P < .0001), and multiple chronic conditions (OR, 1.55; 95% CI, 1.03–2.32; P < .0001) had significantly higher odds of wearable device adoption. Individuals with a usual source of care (OR, 2.44; 95% CI, 1.95–3.04; P < .0001), diabetes (OR, 1.66; 95% CI, 1.32–2.08; P < .0001), and hypertension (OR, 1.78; 95% CI, 1.44–2.20; P < .0001) had significantly higher odds of sharing data with providers. Discussion: A third of individuals adopted a wearable medical device and nearly 50% of individuals who owned a device shared data with a provider in 2019. Patients with certain conditions, such as diabetes and hypertension, were more likely to adopt devices and share data with providers. Social determinants of health, such as income and usual source of care, negatively affected wearable device adoption and data sharing, similarly to other consumer health technologies. Conclusions: Wearable device adoption and data sharing with providers may be more common than prior studies have reported; however, digital disparities were noted. Studies are needed that test implementation strategies to expand wearable device use and data sharing into care delivery.

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Authors
Turner, K., Jo, A., Wei, G., Tabriz, A. A., Clary, A., & Jim, H. S. L.
Affiliations
  • Moffitt Cancer Center (US)
  • University of Florida Health (US)
  • University of South Florida (US)
  • University of North Carolina at Chapel Hill (US)
  • Center for Healthcare Transformation, Avalere Health, Washington DC, USA
Corresponding author
Turner, Kea
ORCID
Venue
Journal of the American Medical Informatics Association
Publisher
Oxford University Press (OUP)
Published
2020-11-12
Volume
28
Issue
2
Pages
371-376
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
DOI
10.1093/jamia/ocaa272
PMC
PMC7883987
OpenAlex
W3102581449
Cited by
33
References
35
Citations by year
2026: 6 · 2025: 8 · 2024: 9 · 2023: 4 · 2022: 5 · 2021: 1
FWCI
2.61
Type
journal article
Language
en
Open access
Licence
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
Locations
  • Journal of the American Medical Informatics Association (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Social Sciences › Demography › Technology Use by Older Adults
Keywords
wearable medical devices, patient-generated health data, diabetes mellitus, hypertension, chronic disease, usual source of care, social determinants of health, digital health disparities, consumer health technology
MeSH terms
Patient Generated Health Data, Wearable Electronic Devices, Age Factors, Female, Health Personnel, Humans, Male, Middle Aged, Multivariate Analysis, Logistic Models, Health Care Surveys, Information Dissemination

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