An Evidence-Based Roadmap for the Provision of More Equitable Telemedicine.


Journal

Applied clinical informatics
ISSN: 1869-0327
Titre abrégé: Appl Clin Inform
Pays: Germany
ID NLM: 101537732

Informations de publication

Date de publication:
05 2022
Historique:
entrez: 8 6 2022
pubmed: 9 6 2022
medline: 11 6 2022
Statut: ppublish

Résumé

During the coronavirus disease 2019 pandemic, as a safety-net organization with a substantial percentage of patients of color and with limited English proficiency (LEP), we were wary of furthering health disparities in our community. We analyzed gaps in telemedicine (telephone and video) delivery in our communities, quantified the effects of our tests of change, and began the process of accumulating evidence to create a road map for other organizations. We leveraged Lean problem-solving strategies to identify modifiable gaps across multiple domains that could inhibit equity in telemedicine. We implemented tests of change across domains of community engagement, technology, education, and access. We observed the proportion of telemedicine encounters across races and languages between April and November, 2020. Regression analyses tested the impact of race and language on telemedicine controlling for age, gender, insurance, and time. Several rounds of changes and enhancements were associated with changes in telemedicine use of +5.5% ( Our roadmap to improve equitable delivery of telemedicine was associated with a significant improvement in telemedicine use among certain minority populations. Most populations of color used telephone more often than video. This preference changed over time and with equity-focused changes in telemedicine delivery.

Identifiants

pubmed: 35675839
doi: 10.1055/s-0042-1749597
pmc: PMC9179235
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

612-620

Informations de copyright

Thieme. All rights reserved.

Déclaration de conflit d'intérêts

None declared.

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Auteurs

Ryan Jelinek (R)

Department of Medicine, Hennepin Healthcare, and University of Minnesota, Minneapolis, Minnesota, United States.

Deepti Pandita (D)

Department of Medicine, Hennepin Healthcare, and University of Minnesota, Minneapolis, Minnesota, United States.

Mark Linzer (M)

Department of Medicine, Hennepin Healthcare, and University of Minnesota, Minneapolis, Minnesota, United States.

Jeremy Bikah Bi Nguema Engoang (JBBN)

Analytics Center of Excellence, Hennepin Healthcare, Minneapolis, Minnesota, United States.

Holly Rodin (H)

Analytics Center of Excellence, Hennepin Healthcare, Minneapolis, Minnesota, United States.

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Classifications MeSH