Evidence map›Paper›PMID 35425872›Full record

ArticleJB & JS open access

Disparities in Telemedicine Utilization During COVID-19 Pandemic: Analysis of Demographic Data from a Large Academic Orthopaedic Practice.

Richard A Ruberto, Eric A Schweppe, Rifat Ahmed, Hasani W Swindell, Christopher A Cordero, Nathan S Lanham, Charles M Jobin

Abstract read
In one paragraph

Article in JB & JS open access. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

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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.

Richard A RubertoDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Eric A SchweppeDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Rifat AhmedDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Hasani W SwindellDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Christopher A CorderoDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Nathan S LanhamDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.
Charles M JobinDepartment of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The coronavirus-19 (COVID-19) pandemic has prompted a shift in health-care provision toward implementation of telemedicine. This study investigated demographic information on orthopaedic telemedicine utilization at a single academic orthopaedic institution in an effort to identify factors associated with telemedicine usage. Methods: Demographic and appointment data were collected from the electronic medical record during equivalent time periods prior to the onset of the COVID pandemic (pre-COVID) and during the COVID pandemic (peri-COVID). Multivariate analyses were performed to identify demographic and socioeconomic correlates of telemedicine utilization. Results: There was a significant increase in telemedicine visits between the eras of study, with significant differences in telemedicine usage in association with age, sex, marital status, English as the primary language, and insurance type (p < 0.001). Multivariate analyses found American Indian/Alaska Native (adjusted odds ratio [aOR] = 0.487, p = 0.004), Black/African American (aOR = 0.622, p < 0.001), Native Hawaiian/other Pacific Islander (aOR = 0.676, p = 0.003), and Asian (aOR = 0.731, p < 0.001) race to be significantly associated with decreased telemedicine usage. Additionally, male sex (aOR = 0.878, p < 0.001) and a non-commercial insurance plan (p < 0.001) were significantly associated with decreased telemedicine usage. Conclusions: Non-White race, non-commercial insurance plans, and male sex were associated with decreased telemedicine utilization. Further investigation is needed to characterize and better identify underlying factors contributing to disparities in telemedicine access and utilization.

Identifiers

PMID35425872
PMCPMC9000049

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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.