COVID-19 transforms health care through telemedicine: evidence from the field

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

This study provides data on the feasibility and impact of video-enabled telemedicine use among patients and providers and its impact on urgent and non-urgent health care delivery from one large health system (NYU Langone Health) at the epicenter of the COVID-19 outbreak in the United States. Between March 2nd and April 14th 2020, telemedicine visits increased from 369.1 daily to 866.8 daily (135% increase) in urgent care after the system-wide expansion of virtual health visits in response to COVID-19, and from 94.7 daily to 4209.3 (4345% increase) in non-urgent care post expansion. Of all virtual visits post expansion, 56.2% and 17.6% urgent and non-urgent visits, respectively, were COVID-19-related. Telemedicine usage was highest by patients aged 20-44, particularly for urgent care. The COVID-19 pandemic has driven rapid expansion of telemedicine use for urgent care and non-urgent care visits beyond baseline periods. This reflects an important change in telemedicine that other institutions facing the COVID-19 pandemic should anticipate.

Related collections

Author and article information

Journal

Journal ID (nlm-ta): J Am Med Inform Assoc

Journal ID (iso-abbrev): J Am Med Inform Assoc

Journal ID (publisher-id): jamia

Title: Journal of the American Medical Informatics Association : JAMIA

Publisher: Oxford University Press

ISSN (Print): 1067-5027

ISSN (Electronic): 1527-974X

Publication date (Electronic): 23 April 2020

Publication date PMC-release: 23 April 2020

Electronic Location Identifier: ocaa072

Affiliations

[o1 ] NYU Grossman School of Medicine , Department of Population Health, New York, NY, USA

[o2 ] NYU Langone Health, Medical Center Information Technology , New York, NY, USA

[o3 ] NYU Tandon School of Engineering , Department of Computer Science & Engineering, Brooklyn, NY, USA

[o4 ] NYU School of Global Public Health , Department of Biostatistics, New York, NY, USA

[o5 ] NYU Tandon School of Engineering , Department of Technology Management & Innovation, Brooklyn, NY, USA

Author notes

Corresponding Author information: Devin Mann, MD, MS, NYU Grossman School of Medicine, NYU Langone Health, 227 E 30th St., 6th Floor, New York, NY, 10016. Devin.Mann@ 123456nyulangone.org , 212-263-9026

Article

Publisher ID: ocaa072

DOI: 10.1093/jamia/ocaa072

PMC ID: 7188161

PubMed ID: 32324855

SO-VID: 8508c2bc-2591-4319-b6f0-55281520b35d

Copyright © © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com

License:

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.