Evidence map›Paper›PMID 36103553›Full record

ArticleJMIR formative research2022

Evidence for Telemedicine's Ongoing Transformation of Health Care Delivery Since the Onset of COVID-19: Retrospective Observational Study.

Soumik Mandal, Batia M Wiesenfeld, Devin Mann, Katharine Lawrence, Rumi Chunara, Paul Testa, Oded Nov

Abstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Soumik Mandal *Department of Population Health, New York University Grossman School of Medicine, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0003-3602-703X
Batia M WiesenfeldNew York University Leonard N Stern School of Business, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-6854-1976
Devin MannDepartment of Population Health, New York University Grossman School of Medicine, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-2099-0852
Katharine LawrenceDepartment of Population Health, New York University Grossman School of Medicine, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0001-5640-2138
Rumi ChunaraComputer Science & Engineering, New York University Tandon School of Engineering, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-5346-7259
Paul TestaMedical Center Information Technology, New York University Langone Health, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-1512-9638
Oded NovDepartment of Population Health, New York University Grossman School of Medicine, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0001-6410-2995

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe surge of telemedicine use during the early stages of the COVID-19 pandemic has been well documented. However, scarce evidence considers the use of telemedicine in the subsequent period.

objectiveThis study aims to evaluate use patterns of video-based telemedicine visits for ambulatory care and urgent care provision over the course of recurring pandemic waves in 1 large health system in New York City (NYC) and what this means for health care delivery.

methodsRetrospective electronic health record (EHR) data of patients from January 1, 2020, to February 28, 2022, were used to longitudinally track and analyze telemedicine and in-person visit volumes across ambulatory care specialties and urgent care, as well as compare them to a prepandemic baseline (June-November 2019). Diagnosis codes to differentiate suspected COVID-19 visits from non-COVID-19 visits, as well as evaluating COVID-19-based telemedicine use over time, were compared to the total number of COVID-19-positive cases in the same geographic region (city level). The time series data were segmented based on change-point analysis, and variances in visit trends were compared between the segments.

resultsThe emergence of COVID-19 prompted an early increase in the number of telemedicine visits across the urgent care and ambulatory care settings. This use continued throughout the pandemic at a much higher level than the prepandemic baseline for both COVID-19 and non-COVID-19 suspected visits, despite the fluctuation in COVID-19 cases throughout the pandemic and the resumption of in-person clinical services. The use of telemedicine-based urgent care services for COVID-19 suspected visits showed more variance in response to each pandemic wave, but telemedicine visits for ambulatory care have remained relatively steady after the initial crisis period. During the Omicron wave, the use of all visit types, including in-person activities, decreased. Patients between 25 and 34 years of age were the largest users of telemedicine-based urgent care. Patient satisfaction with telemedicine-based urgent care remained high despite the rapid scaling of services to meet increased demand.

conclusionsThe trend of the increased use of telemedicine as a means of health care delivery relative to the pre-COVID-19 baseline has been maintained throughout the later pandemic periods despite fluctuating COVID-19 cases and the resumption of in-person care delivery. Overall satisfaction with telemedicine-based care is also high. The trends in telemedicine use suggest that telemedicine-based health care delivery has become a mainstream and sustained supplement to in-person-based ambulatory care, particularly for younger patients, for both urgent and nonurgent care needs. These findings have implications for the health care delivery system, including practice leaders, insurers, and policymakers. Further investigation is needed to evaluate telemedicine adoption by key demographics, identify ongoing barriers to adoption, and explore the impacts of sustained use of telemedicine on health care outcomes and experience.

Indexed as

COVID-19digital healthhealth care deliverytelemedicineurgent care

Identifiers

PMID36103553
PMCPMC9578517

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.