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Cited by 46Mobile Health and mHealth ApplicationsHealth Literacy and Information AccessibilityPublic Health Policies and Education

Population health-based approaches to utilizing digital technology: a strategy for equity

Open access
Graham, Garth N., Ostrowski, MaryLynn, Sabina, Alyse B.·2016·Journal of Public Health Policy
DOI 10.1057/s41271-016-0012-5
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Abstract

Health care disparities and high chronic disease rates burden many communities and disproportionally impact racial/ethnic populations in the United States. These disparities vary geographically, increase health care expenses, and result in shortened lifespans. Digital technologies may be one tool for addressing health disparities and improving population health by increasing individuals' access to health information-especially as most low-income U.S. residents gain access to smartphones. The Aetna Foundation partners with organizations to use digital technologies, including mobile applications, data collection, and related platforms, for learning and sharing. Projects range from the broad-childhood education, lifestyle modification, health IT training, and nutrition education, to the specific-local healthy foods, stroke rehabilitation, and collection of city-level data. We describe our approaches to grantmaking and discuss lessons learned and their implications. When combined with sound policy strategies, emerging, scalable, digital technologies will likely become powerful allies for improving health and reducing health disparities.

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Crossref · 10.1057/s41271-016-0012-5

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  • Many people in remote or low-income settings are not well supported by conventional health care.

    “Many people in remote or low-income settings are not well supported by conventional health care.121”

    From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [121]

    The Abstract (page not specified in our copy) says access to care depends on where a person lives and describes disparities in the use of health services. The section on Camden describes residents relying on inefficient emergency-department care rather than preventive care. These passages support the point for underserved, low-income communities, but do not specifically establish it for remote settings. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • The reach of AI-based DHTs, coupled with the relative reduction in cost and increased capability of mobile communications, has led to its greater penetration into traditionally difficult-to-reach communities compared with robust conventional health care.

    “The reach of AI-based DHTs, coupled with the relative reduction in cost and increased capability of mobile communications, has led to its greater penetration into traditionally difficult-to-reach communities compared with robust conventional health care.121”

    From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [121]

    The “Digital Technology -Mobile Personal Engagement” section reports widespread smartphone ownership among low-income and underserved U.S. populations, and the Conclusion describes mobile technology’s potential to reach them. The paper does not establish that AI-based digital health tools have penetrated these communities more than conventional health care, or attribute such penetration to falling mobile-communication costs and increasing capabilities. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Authors
Graham, G. N., Ostrowski, M., & Sabina, A. B.
Affiliations
Aetna (United States) (US)
Corresponding author
Graham, Garth N.
ORCID
Venue
Journal of Public Health Policy
Publisher
Springer Science and Business Media LLC
Published
2016-11
Volume
37
Issue
S2
Pages
154-166
ISSN
  • 0197-5897 (ISSN-L)
  • 1745-655X
DOI
10.1057/s41271-016-0012-5
OpenAlex
W2557541991
Cited by
46
References
16
Citations by year
2025: 9 · 2024: 6 · 2023: 11 · 2022: 4 · 2021: 6 · 2020: 2 · 2019: 6 · 2018: 2
FWCI
4.98
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Public Health Policy (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • U.S. Department of Health and Human Services
  • Aetna Foundation
  • University of Connecticut
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Health Sciences › Health Professions › General Health Professions › Public Health Policies and Education
Keywords
health disparities, digital health technologies, population health, health equity, racial and ethnic minorities, mobile health apps, smartphone access, low-income populations, grantmaking, health information access, nutrition education, healthy food, stroke rehabilitation, childhood education, lifestyle modification
MeSH terms
Health Equity, Diffusion of Innovation, Health Policy, Humans, Medical Informatics, United States, Biomedical Technology, Cell Phone, Health Status Disparities

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