Cited by 161ICT Impact and PoliciesTelemedicine and Telehealth ImplementationHealth disparities and outcomes

Disparities in digital access among American rural and urban households and implications for telemedicine‐based services

Open access
Curtis, Megan E., Clingan, Sarah E., Guo, Huiying, Zhu, Yuhui, Mooney, Larissa J., Hser, Yih‐Ing·2022·The Journal of Rural Health

Abstract

Purpose: To examine characteristics associated with disparities in digital access (i.e., access to high‐speed Internet via a computer or smartphone) in American rural and urban households given that digital access has a direct impact on access to telemedicine‐based services. Methods: Using the 2019 American Community Survey, we analyzed the proportions of geographic area, race/ethnicity, and socioeconomic status according to device and high‐speed Internet access. Maximum likelihood logit estimators estimated how these factors influenced device and high‐speed Internet access. Findings: Of 105,312,959 households, 32.29% were without a desktop or laptop computer with high‐speed Internet (WDW), 21.51% were without a smartphone with a data plan for wireless Internet (WSW), and 14.02% were without any digital access (WDA). Nonmetropolitan households were significantly more likely to be WDA than metropolitan households (odds ratio [OR] = 1.87; 95% confidence interval [CI]: 1.83‐1.91). Relative to non‐Hispanic Whites, non‐Hispanic Blacks (OR = 1.60; 95% CI: 1.56‐1.64), American Indian or Alaska natives (OR = 2.00; 95% CI: 1.82‐2.19), or Hispanics (OR = 1.70; 95% CI: 1.66‐1.74) were significantly more likely to be WDA. When compared to households with private health insurance coverage, households WDA were significantly more likely to have no insurance (OR = 2.44; 95% CI: 2.36‐2.53) or public insurance coverage (OR = 3.78; 95% CI: 3.70‐3.86). Households with any digital access reported higher income and more family members living at home. Using the same predictors, similar findings were reported for households WDW or WSW. Conclusions: Significant disparities in digital access exist among nonmetropolitan households, racial/ethnic minority households, and lower‐income households. The lack of digital access has implications for the accessibility of health care services via telemedicine and thus could exacerbate health disparities.

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  • Barriers such as geographic isolation, socioeconomic disadvantage, limited broadband access, and systemic inequities in access to palliative and psychosocial care can contribute to unmet needs for information, skills training, and emotional support.

    “Barriers such as geographic isolation, socioeconomic disadvantage, limited broadband access, and systemic inequities in access to palliative and psychosocial care can contribute to unmet needs for information, skills training, and emotional support.6,7,8,9,10”

    From Palliative Care Coaching for Family Caregivers of Patients With Advanced Cancer (2026) · cites this paper as [8]

    The Discussion and Conclusion (page not provided) link rural residence, low income, and limited digital access to reduced access to telemedicine-based health care. They do not address inequities in palliative or psychosocial care, or unmet needs for information, skills training, and emotional support. (LLM, conf=0.86)

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  • African American and rural caregivers have historically had limited access to formal resources and supportive services.

    “In addition, African American and rural caregivers have historically had limited access to formal resources and supportive services.”

    From Palliative Care Coaching for Family Caregivers of Patients With Advanced Cancer (2026) · cites this paper as [8]

    The Discussion (page unavailable) reports that non-metropolitan and non-Hispanic Black households had less digital access needed for telemedicine. This supports a narrower point about a barrier to health services, but the paper does not study caregivers or establish historical limits on their access to formal resources and supportive services. (LLM, conf=0.83)

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Research works printed but not linked: 7

  1. [1]Bashshur R, Doarn CR, Frenk JM, Kvedar JC, Woolliscroft JO. Telemedicine and the COVID-19 Pandemic, lessons for the future. Telemed J E Health. 2020. 571– 573. 10.1089/tmj.2020.29040.rbexternalicon 32275485 · DOI
  2. [6]Lorence DP, Park H, Fox S. Racial disparities in health information access: Resilience of the digital divide. J Med Syst. 2006; 30(4): 241– 249. doi: 10.1007/s10916-005-9003-y 16978003 · DOI
  3. [7]Mitchell UA, Chebli PG, Ruggiero L, Muramatsu N. The digital divide in health-related technology use: The significance of race/ethnicity. Gerontologist. 2019; 59(1): 6– 14. doi: 10.1093/geront/gny138 30452660 · DOI
  4. [8]Greenberg AJ, Haney D, Blake KD, Moser RP, Hesse BW. Differences in access to and use of electronic personal health information between rural and urban. J Rural Health. 2018; 34(Suppl 1): s30– s38. doi: 10.1111/jrh.12228 28075508 PMC5505819 · DOI
  5. [10]Ruggles S, Flood S, Goeken R, IPUMS USA: Version 10.0 [ dataset]. IPUMS; 2020. doi: 10.18128/D010.V10.0 · DOI
  6. [12]Centers for Medicare and Medicaid Services. Medicare and Medicaid programs; policy and regulatory revisions in response to the COVID-19 public health emergency. Federal Regist. 2020; 85(66): 19230– 19292.
  7. [14]Federal Communications Commission. Establishing the digital opportunity data collection; modernizing the FCC form 477 data program. FedRegist. 2021; 86: 18124– 18163.

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Authors
Curtis, M. E., Clingan, S. E., Guo, H., Zhu, Y., Mooney, L. J., & Hser, Y.
Affiliations
University of California, Los Angeles (US)
Corresponding author
Hser, Yih‐Ing
Venue
The Journal of Rural Health
Publisher
Wiley
Published
2021-08-06
Volume
38
Issue
3
Pages
512-518
ISSN
  • 0890-765X (ISSN-L)
  • 1748-0361
OpenAlex
W3193251485
Cited by
161
References
1
Citations by year
2026: 43 · 2025: 41 · 2024: 31 · 2023: 25 · 2022: 18 · 2021: 3
FWCI
8.64
Type
journal article
Language
en
Open access
Locations
  • The Journal of Rural Health (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
National Institute on Drug Abuse (UG1DA049435)
Topics
  • Physical Sciences › Engineering › Media Technology › ICT Impact and Policies
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Social Sciences › Health › Health disparities and outcomes
Keywords
digital divide, digital access, telemedicine, urban-rural differences, high-speed internet, smartphone access, racial and ethnic disparities, socioeconomic status, health insurance coverage, health disparities
MeSH terms
Ethnicity, Health Services Accessibility, Hispanic or Latino, Humans, Minority Groups, United States, Telemedicine, White People, Healthcare Disparities

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