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Quantifying digital health inequality across a national healthcare system

Overview of attention for article published in BMJ Health & Care Informatics Online, November 2023
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Title
Quantifying digital health inequality across a national healthcare system
Published in
BMJ Health & Care Informatics Online, November 2023
DOI 10.1136/bmjhci-2023-100809
Pubmed ID
Authors

Joe Zhang, Jack Gallifant, Robin L Pierce, Aoife Fordham, James Teo, Leo Celi, Hutan Ashrafian

Abstract

Digital health inequality, observed as differential utilisation of digital tools between population groups, has not previously been quantified in the National Health Service (NHS). Deployment of universal digital health interventions, including a national smartphone app and online primary care services, allows measurement of digital inequality across a nation. We aimed to measure population factors associated with digital utilisation across 6356 primary care providers serving the population of England. We used multivariable regression to test association of population and provider characteristics (including patient demographics, socioeconomic deprivation, disease burden, prescribing burden, geography and healthcare provider resource) with activation of two independent digital services during 2021/2022. We find a significant adjusted association between increased population deprivation and reduced digital utilisation across both interventions. Multivariable regression coefficients for most deprived quintiles correspond to 4.27 million patients across England where deprivation is associated with non-activation of the NHS App. Results are concerning for technologically driven widening of healthcare inequalities. Targeted incentive to digital is necessary to prevent digital disparity from becoming health outcomes disparity.

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Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 44%
Unspecified 1 11%
Other 1 11%
Student > Doctoral Student 1 11%
Unknown 2 22%
Readers by discipline Count As %
Medicine and Dentistry 3 33%
Computer Science 3 33%
Unspecified 1 11%
Social Sciences 1 11%
Agricultural and Biological Sciences 1 11%
Other 0 0%