COVID-19 transforms health care through telemedicine: Evidence from the field
Open accessAbstract
This study provides data on the feasibility and impact of video-enabled telemedicine use among patients and providers and its impact on urgent and nonurgent healthcare delivery from one large health system (NYU Langone Health) at the epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States. Between March 2nd and April 14th 2020, telemedicine visits increased from 102.4 daily to 801.6 daily. (683% increase) in urgent care after the system-wide expansion of virtual urgent care staff in response to COVID-19. Of all virtual visits post expansion, 56.2% and 17.6% urgent and nonurgent visits, respectively, were COVID-19–related. Telemedicine usage was highest by patients 20 to 44 years of age, particularly for urgent care. The COVID-19 pandemic has driven rapid expansion of telemedicine use for urgent care and nonurgent care visits beyond baseline periods. This reflects an important change in telemedicine that other institutions facing the COVID-19 pandemic should anticipate.
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NYU Langone Virtual Urgent Care visits grew 683% and non-urgent video doctor visits grew 4,345% over six weeks in March and the first half of April 2020.
“daily averages for Virtual Urgent Care visits at New York University’s Langone Health, which was well-situated to expand telecare, grew by 683% and non-urgent video doctor visits grew by 4,345% in response to COVID-19 over six weeks during March and the first half of April 2020.”
From REVISITING HEALTH INFORMATION TECHNOLOGY ETHICAL, LEGAL, and SOCIAL ISSUES and EVALUATION: TELEHEALTH/TELEMEDICINE and COVID-19 (2020) · cites this paper as [7]
At NYU Langone during early COVID-19, in-person visits declined 80% while emergency medicine providers increased from 40 to 289.
“In-person visits declined 80% while forty emergency medicine providers were increased to 289 “surge” providers from multiple specialties.”
From REVISITING HEALTH INFORMATION TECHNOLOGY ETHICAL, LEGAL, and SOCIAL ISSUES and EVALUATION: TELEHEALTH/TELEMEDICINE and COVID-19 (2020) · cites this paper as [7]
Young adult patients from 20 to 44 years of age were represented as the most frequent telecare service consumers.
“Globally, studies have shown that during the COVID-19 pandemic, females used telecare facilities two times more than males and suggested that young adult patients were represented as the most frequent telecare service consumers, from 20 to 44 years of age [53,54,55,56,57].”
From Telehealth and COVID-19 Pandemic: An Overview of the Telehealth Use, Advantages, Challenges, and Opportunities during COVID-19 Pandemic (2022) · cites this paper as [55]
In Australia, a national study suggests that the COVID-19 pandemic considerably encouraged and promoted the use of telehealth, and without that progress, telehealth use would have remained infrequent.
“In Australia, a national study suggests that the COVID-19 pandemic considerably encouraged and promoted the use of telehealth and thanks to this window of opportunity, a lot of progress was made in the domain that, without that progress, telehealth use would have remained infrequent [50,51,52,53,54,55,56,57,58].”
From Telehealth and COVID-19 Pandemic: An Overview of the Telehealth Use, Advantages, Challenges, and Opportunities during COVID-19 Pandemic (2022) · cites this paper as [55]
Globally, during the COVID-19 pandemic, females used telecare facilities two times more than males.
“Globally, studies have shown that during the COVID-19 pandemic, females used telecare facilities two times more than males and suggested that young adult patients were represented as the most frequent telecare service consumers, from 20 to 44 years of age [53,54,55,56,57].”
From Telehealth and COVID-19 Pandemic: An Overview of the Telehealth Use, Advantages, Challenges, and Opportunities during COVID-19 Pandemic (2022) · cites this paper as [55]
Consultations through telemedicine underwent an increase of 683% during the COVID-19 pandemic in New York City.
“Consultations through telemedicine underwent an increase of 683% during the COVID-19 pandemic in New York City [9].”
From Global Interest in Telehealth During COVID-19 Pandemic: An Analysis of Google Trends™ (2020) · cites this paper as [9]
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- Authors
- Mann, D. M., Chen, J., Chunara, R., Testa, P. A., & Nov, O.
- Affiliations
- NYU Langone Health (US)
- New York University (US)
- Corresponding author
- Mann, Devin M
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-05-29
- Volume
- 27
- Issue
- 7
- Pages
- 1132-1135
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC7188161
- OpenAlex
- W3019006697
- Cited by
- 1,361
- References
- 7
- Citations by year
- 2026: 55 · 2025: 87 · 2024: 164 · 2023: 220 · 2022: 301 · 2021: 368 · 2020: 161 · 2019: 1 · 2018: 1
- FWCI
- 196.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (#1928614)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Physical Sciences › Computer Science › Information Systems › Healthcare during COVID-19 Pandemic
- Keywords
- telemedicine, COVID-19 pandemic, urgent care, virtual visits, health system response, patient demographics
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Aged, Aged, 80 and over, Ambulatory Care, Humans, Middle Aged, New York City, Pneumonia, Viral, Telemedicine, Age Distribution, Coronavirus Infections, Young Adult, Pandemics
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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