Evidence map›Paper›PMID 39583033›Full record

ArticleNeurology. Clinical practice2025

Disparities in Utilization of Outpatient Telemedicine for Neurologic Care.

Marisa Patryce McGinley, Tucker Harvey, Daniel Ontaneda, Allison L Weathers, Bryan R Cobb, Anisha Patel

Abstract read
In one paragraph

Article in Neurology. Clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Marisa Patryce McGinleyCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0000-0002-7463-6787
Tucker HarveyCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0000-0001-6992-8753
Daniel OntanedaCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0000-0002-2838-9148
Allison L WeathersCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0009-0006-9041-5999
Bryan R CobbCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0000-0001-7147-8720
Anisha PatelCleveland Clinic (MPM, DO, ALW); Department of Quantitative Health Sciences (TH), Cleveland Clinic, OH; and Genentech Inc., (BRC, AP), South San Francisco, CA.ORCID https://orcid.org/0000-0003-1902-905X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: To characterize outpatient telemedicine utilization for neurologic conditions and identify potential disparities. Methods: All outpatient visits conducted by neurology clinicians at an academic medical health care system for patients aged 18 years or older from January 2019 to July 2022 were included. All telemedicine visits were synchronous audio-visual. Patients completing in-person visits alone were compared with patients completing telemedicine visits. Utilization of telemedicine was compared across 3 time frames: prepandemic (before March 2020), early-pandemic (March-June 2020), and late-pandemic (July 2020-July 2022). Generalized linear mixed-effects models were used to evaluate whether the odds of a visit being telemedicine vs in-person differed based on the time frame and to predict likelihood of telemedicine vs in-person visit in late pandemic time frame. Results: In total, 242,273 patients (mean age 55.9 years, 58.2% female, 81.9% White, 12.5% Black, 3.4% Hispanic, 39.2% Medicare) completed 752,174 visits during the study time frame. There was a significant difference in telemedicine utilization between the time frames, with the highest utilization being in the early pandemic ( Discussion: Disparities in telemedicine persist with lower use in individuals who were older, Black, Hispanic, non-English preferred language, and lower socioeconomic status. These disparities improved initially but were accentuated later in the pandemic. The equal utilization of telemedicine by rural and urban patients in this study suggests the potential of telemedicine to improve access disparities for rural patients. The implementation of equitable health care delivery will require a better understanding of barriers, preferences, and legislation needed to support equitable telemedicine access.

Identifiers

PMID39583033
PMCPMC11581764

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.