Health data poverty: an assailable barrier to equitable digital health care
Open accessAbstract
Data-driven digital health technologies have the power to transform health care. If these tools could be sustainably delivered at scale, they might have the potential to provide everyone, everywhere, with equitable access to expert-level care, narrowing the global health and wellbeing gap. Conversely, it is highly possible that these transformative technologies could exacerbate existing health-care inequalities instead. In this Viewpoint, we describe the problem of health data poverty: the inability for individuals, groups, or populations to benefit from a discovery or innovation due to a scarcity of data that are adequately representative. We assert that health data poverty is a threat to global health that could prevent the benefits of data-driven digital health technologies from being more widely realised and might even lead to them causing harm. We argue that the time to act is now to avoid creating a digital health divide that exacerbates existing health-care inequalities and to ensure that no one is left behind in the digital era.
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- Authors
- Ibrahim, H., Liu, X., Zariffa, N., Morris, A. D., & Denniston, A. K.
- Affiliations
- University Hospitals Birmingham NHS Foundation Trust (GB)
- Health Data Research UK (GB)
- Corresponding author
- Denniston, Alastair K
- Venue
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 3
- Issue
- 4
- Pages
- e260-e265
- ISSN
- 2589-7500 (ISSN-L)
- OpenAlex
- W3135721250
- Cited by
- 326
- References
- 34
- Citations by year
- 2026: 59 · 2025: 71 · 2024: 64 · 2023: 72 · 2022: 47 · 2021: 13
- FWCI
- 14.24
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Digital Health (publishedVersion, cc-by)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (publishedVersion, cc-by)
- Funders
- National Institute for Health and Care Research
- Department of Health and Social Care
- Medical Research Council (MC_PC_13040, MR/M501633/1)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- data scarcity, health care inequality, digital divide, global health inequities
- MeSH terms
- Digital Technology, Diffusion of Innovation, Humans, Biomedical Technology, Healthcare Disparities, Datasets as Topic
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