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Language-Specific Challenges and Solutions for Equitable Telemedicine Implementation in the Primary Care Safety Net During COVID-19

  • Original Research: Qualitative Research
  • Published:
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Abstract

Purpose

Telemedicine care dramatically expanded during the COVID-19 pandemic. We characterized facilitators and barriers to telemedicine implementation among safety-net primary care clinics serving patients with limited English proficiency (LEP).

Methods

We collected data on telemedicine volume and patient demographics among safety-net clinics participating in a telemedicine learning collaborative. Data on various metrics were reported to the collaborative from February 2019 through August 2021. We conducted semi-structured interviews with clinical and quality leaders, purposively sampling clinics serving high proportions of patients with LEP. We analyzed interviews with a mixed inductive-deductive approach applying the Consolidated Framework for Implementation Research.

Results

By September 2020, the 23 sites served 121,589 unique patients with in-person and 120,338 with telephone visits; 47% of these patients had LEP. Of 10,897 unique patients served by video visits, 38% had LEP. As a proportion of total visits, telemedicine (telephone and video) visits increased from 0–17% in October 2019–March 2020 to 10–98% in March–August 2020. We conducted 14 interviews at 11 sites. Themes included (1) existing telemedicine platforms and interpreter services were not optimized to support patients with LEP; (2) clinics invested significant labor iterating workflows; (3) sites with technological infrastructure and language-concordant staff were best suited to serve patients; (4) patients speaking less-represented languages or experiencing intersecting literacy barriers were underserved with telemedicine. Interviewees recommended innovations in telemedicine platforms and community-based access.

Conclusions

Safety-net sites relied on existing resources to accommodate patients with LEP, but struggled providing access for the most marginalized. Proactive, data-driven strategies to address patient and community barriers as well as optimize clinical workflows with high-quality, certified medical interpreters are needed to ensure equitable access.

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Acknowledgements

The authors would like to thank all participants in the Connected Care Accelerator, and all the interviewees, Erica Shin, BA, Elaine Khoong, MD, MAS, Sofi Bergkvist, MS, MBA, and Jeanette Wong, BS.

Funding

This work was supported by The Commonwealth Fund, a national, private foundation based in New York City that supports independent research on healthcare issues and makes grants to improve healthcare practice and policy (Grant No. 20202842). The views presented here are those of the author and not necessarily those of The Commonwealth Fund, its directors, officers, or staff. The Connected Care Accelerator was supported by the California Health Care Foundation (Grant No. G-31003). Dr. Sharma was supported by K08 HS028477-01 (Agency for Healthcare Research and Quality) and KL2 TR001870 (National Center for Advancing Translational Sciences of the National Institutes of Health). Dr. Sarkar was supported by K24 CA212294 (National Cancer Institute).This paper’s contents are solely the responsibility of the authors and do not necessarily represent the official views of AHRQ nor the NIH.

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Author notes

  1. Urmimala Sarkar and Courtney R. Lyles are joint senior authors

Authors and Affiliations

  1. Center for Excellence in Primary Care, Department of Family and Community Medicine, University of California San Francisco, San Francisco, CA, USA

    Anjana E. Sharma MD, MAS

  2. Center for Vulnerable Populations, Department of Medicine, University of California San Francisco, San Francisco, CA, USA

    Anjana E. Sharma MD, MAS, Sarah Lisker BA, Jessica D. Fields BA, Urmimala Sarkar MD, MPH & Courtney R. Lyles PhD

  3. University of California School of Medicine, San Francisco, 1001 Potrero Ave., San Francisco, CA, 94143, USA

    Anjana E. Sharma MD, MAS

  4. Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, USA

    Sarah Lisker BA, Jessica D. Fields BA, Urmimala Sarkar MD, MPH & Courtney R. Lyles PhD

  5. Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA

    Jessica D. Fields BA & Courtney R. Lyles PhD

  6. Center for Care Innovations, Oakland, CA, USA

    Veenu Aulakh MSPH & Kathleen Figoni MS-HCA

  7. Center for Community Health and Evaluation, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

    Maggie E. Jones MPH & Natasha B. Arora MS

  8. UC Davis Center for Healthcare Policy and Research, UC Davis School of Medicine, Sacramento, CA, USA

    Courtney R. Lyles PhD

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Correspondence to Anjana E. Sharma MD, MAS.

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Conflict of Interest:

Dr Sarkar received contract funding from InquisitHealth, AppliedVR, and SomnologyMD; is supported by a gift from The Doctors Company Foundation; serves as a scientific/expert advisor for nonprofit organizations HealthTech 4 Medicaid and HopeLab (no compensation); is a member of the American Medical Association’s Equity and Innovation Advisory Group (for which she receives honoraria); and previously served as a clinical advisor for Omada Health and as an advisory board member for Doximity (for which she received honoraria). Dr. Lyles received contract funding from InquisitHealth, AppliedVR, and SomnologyMD. She is currently a Visiting Researcher at Google.

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Sharma, A.E., Lisker, S., Fields, J.D. et al. Language-Specific Challenges and Solutions for Equitable Telemedicine Implementation in the Primary Care Safety Net During COVID-19. J GEN INTERN MED 38, 3123–3133 (2023). https://doi.org/10.1007/s11606-023-08304-2

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