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In-Person and Telehealth Ambulatory Contacts and Costs in a Large US Insured Cohort Before and During the COVID-19 Pandemic

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

Question  How did ambulatory care patterns change after the initial COVID-19 surge in the US and what role did telehealth play?

Findings  In this cohort study of 36 568 010 US individuals, ambulatory contacts decreased by 18% between the 2019 and 2020 March to June periods, and telehealth use increased from 0.3% of contacts in 2019 to 23.6% of all contacts in 2020. Increased disease burden, COVID-19 prevalence, and greater social resources were associated with higher telehealth use.

Meaning  These findings suggest that the dramatic shift in the adoption of virtual care has many implications for health services provision both during and after the pandemic.

Abstract

Importance  This study assesses the role of telehealth in the delivery of care at the start of the COVID-19 pandemic.

Objectives  To document patterns and costs of ambulatory care in the US before and during the initial stage of the pandemic and to assess how patient, practitioner, community, and COVID-19–related factors are associated with telehealth adoption.

Design, Setting, and Participants  This is a cohort study of working-age persons continuously enrolled in private health plans from March 2019 through June 2020. The comparison periods were March to June in 2019 and 2020. Claims data files were provided by Blue Health Intelligence, an independent licensee of the Blue Cross and Blue Shield Association. Data analysis was performed from June to October 2020.

Main Outcomes and Measures  Ambulatory encounters (in-person and telehealth) and allowed charges, stratified by characteristics derived from enrollment files, practitioner claims, and community characteristics linked to the enrollee’s zip code.

Results  A total of 36 568 010 individuals (mean [SD] age, 35.71 [18.77] years; 18 466 557 female individuals [50.5%]) were included in the analysis. In-person contacts decreased by 37% (from 1.63 to 1.02 contacts per enrollee) from 2019 to 2020. During 2020, telehealth visits (0.32 visit per person) accounted for 23.6% of all interactions compared with 0.3% of contacts in 2019. When these virtual contacts were added, the overall COVID-19 era patient and practitioner visit rate was 18% lower than that in 2019 (1.34 vs 1.64 visits per person). Behavioral health encounters were far more likely than medical contacts to take place virtually (46.1% vs 22.1%). COVID-19 prevalence in an area was associated with higher use of telehealth; patients from areas within the top quintile of COVID-19 prevalence during the week of their encounter were 1.34 times more likely to have a telehealth visit compared with those in the lowest quintile (the reference category). Persons living in areas with limited social resources were less likely to use telehealth (most vs least socially advantaged neighborhoods, 27.4% vs 19.9% usage rates). Per enrollee medical care costs decreased by 15% between 2019 and 2020 (from $358.32 to $306.04 per person per month). During 2020, those with 1 or more COVID-19–related service (1 470 721 members) had more than 3 times the medical costs ($1701 vs $544 per member per month) than those without COVID-19–related services. Persons with 1 or more telehealth visits in 2020 had considerably higher costs than persons having only in-person ambulatory contacts ($2214.10 vs $1337.78 for the COVID-19–related subgroup and $735.87 vs $456.41 for the non–COVID-19 subgroup).

Conclusions and Relevance  This study of a large cohort of patients enrolled in US health plans documented patterns of care at the onset of COVID-19. The findings are relevant to policy makers, payers, and practitioners as they manage the use of telehealth during the pandemic and afterward.

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Article Information

Accepted for Publication: January 29, 2021.

Published: March 23, 2021. doi:10.1001/jamanetworkopen.2021.2618

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Weiner JP et al. JAMA Network Open.

Corresponding Author: Jonathan P. Weiner, DrPH, Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Rm 605, Baltimore, Maryland 21205 (jweiner1@jhu.edu).

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

Concept and design: Weiner, Bandeian, Hatef, Liu.

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

Drafting of the manuscript: Weiner, Hatef, Lans, Liu.

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

Statistical analysis: Weiner, Bandeian, Lans, Lemke.

Administrative, technical, or material support: Weiner, Hatef, Liu.

Supervision: Weiner.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was internally funded through the Center for Population Health Information Technology at Johns Hopkins Bloomberg School of Public Health and Blue Health Intelligence.

Role of the Funder/Sponsor: The funders 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.

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.

Additional Contributions: We are grateful to Blue Health Intelligence and the health plans who contributed to this database for making these data available. Lauren Tansky, BA (Johns Hopkins Center for Population Health Information Technology), provided technical support in the preparation of manuscript tables and was not compensated beyond her normal salary.

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