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Outcomes of In-Person and Telehealth Ambulatory Encounters During COVID-19 Within a Large Commercially Insured Cohort

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  What is the association of telehealth vs in-person encounters with outcomes of care during the COVID-19 pandemic in the US?

Findings  In this cohort study of 40.7 million US commercially insured adults with acute clinical conditions, those with an initial telehealth encounter, compared with an in-person encounter, had higher odds for any follow-up encounter, an emergency department encounter, and in-patient admissions. For people with chronic conditions, the odds were lower for those with an initial telehealth encounter.

Meaning  The contrasting patterns of follow-up care among members receiving telehealth for acute and chronic conditions have implications for health services during and after the COVID-19 pandemic.

Abstract

Importance  Since the start of the COVID-19 pandemic, few studies have assessed the association of telehealth with outcomes of care, including patterns of health care use after the initial encounter.

Objective  To assess the association of telehealth and in-person visits with outcomes of care during the COVID-19 pandemic.

Design, Setting, and Participants  This cohort study assessed continuously enrolled members in private health plans of the Blue Cross and Blue Shield Association from July 1, 2019, to December 31, 2020.

Main Outcomes and Measures  Main outcomes were ambulatory encounters per enrollee stratified by characteristics derived from enrollment files, practitioner claims, and community characteristics linked to the enrollee’s zip code. Outcomes of care were assessed 14 days after the initial encounters and included follow-up encounters of any kind, emergency department encounters, and hospitalizations after initial telehealth or in-person encounters.

Results  In this cohort study of 40 739 915 individuals (mean [SD] age, 35.37 [18.77] years; 20 480 768 [50.3%] female), ambulatory encounters decreased by 1.0% and the number of in-person encounters per enrollee decreased by 17.0% from 2019 to 2020; however, as a proportion of all ambulatory encounters, telehealth encounters increased substantially from 0.6% (n = 236 220) to 14.1% (n = 5 743 718). For members with an initial telehealth encounter for a new acute condition, the adjusted odds ratio was 1.44 (95% CI, 1.42-1.46) for all follow-ups combined and 1.11 (95% CI, 1.06-1.16) for an emergency department encounter. For members with an initial telehealth encounter for a new chronic condition, the adjusted odds ratios were 0.94 (95% CI, 0.92-0.95) for all follow-ups combined and 0.94 (95% CI, 0.90-0.99) for in-patient admissions.

Conclusions and Relevance  In this cohort study of 40.7 million commercially insured adults, telehealth accounted for a large share of ambulatory encounters at the peak of the pandemic and remained prevalent after infection rates subsided. Telehealth encounters for chronic conditions had similar rates of follow-up to in-person encounters for these conditions, whereas telehealth encounters for acute conditions seemed to be more likely than in-person encounters to require follow-up. These findings suggest a direction for future work and are relevant to policy makers, payers, and practitioners as they manage the use of telehealth during the COVID-19 pandemic and afterward.

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Article Information

Accepted for Publication: March 7, 2022.

Published: April 26, 2022. doi:10.1001/jamanetworkopen.2022.8954

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Hatef E et al. JAMA Network Open.

Corresponding Author: Elham Hatef, MD, MPH, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, 624 N Broadway, Room 502, Baltimore, MD 21218 (ehatef1@jhu.edu).

Author Contributions: Mr Lans had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Hatef, Bandeian, Lasser, Goldsack, Weiner.

Acquisition, analysis, or interpretation of data: Hatef, Lans, Bandeian, Lasser, Weiner.

Drafting of the manuscript: Hatef, Lans, Lasser.

Critical revision of the manuscript for important intellectual content: Hatef, Bandeian, Goldsack, Weiner.

Statistical analysis: Lans, Bandeian.

Obtained funding: Weiner.

Administrative, technical, or material support: Lasser, Goldsack, Weiner.

Supervision: Hatef, Weiner.

Conflict of Interest Disclosures: Drs Hatef, Lasser, and Weiner had a contract with the American Telehealth Association during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was funded by the Center for Population Health Information Technology at Johns Hopkins Bloomberg School of Public Health (Drs Hatef, Lasser, and Weiner) and Blue Health Intelligence and partially funded by the American Telemedicine Association (Drs Hatef, Lasser, and Weiner).

Role of the Funder/Sponsor: The Center for Population Health Information Technology at Johns Hopkins Bloomberg School of Public Health and Blue Health Intelligence had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The American Telemedicine Association reviewed and commented on the conduct of the study, but did not play any other role in the study design; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content of this article is the responsibility of the authors and does not necessarily represent the positions of the Johns Hopkins University or Blue Health Intelligence or the Blue Cross and Blue Shield Association or the American Telemedicine Association.

Additional Contributions: Lauren Tansky, BS, Center for Population Health Information Technology, provided technical support in the preparation of tables. She was compensated for her work. We are grateful to Blue Health Intelligence and the health plans who contributed to this database for making these data available.

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