Evidence map›Paper›PMID 36540144›Full record

ArticleNeurology. Clinical practice2022

Telemedicine Utilization Among Patients With Multiple Sclerosis in the US Veterans Health Administration, 2010-2020.

Hoda S Abdel Magid, Shan Jin, William J Culpepper, Lorene M Nelson, Mitchell Wallin

Open access · greenAbstract read
In one paragraph

Article in Neurology. Clinical practice, 2022. 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
0.8field-weighted citation impact, top 27% of its field
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, 4 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 1 country.

Hoda S Abdel MagidVA Palo Alto Healthcare System (HSAM), US Department of Veterans Affairs, Palo Alto, CA; Department of Epidemiology and Population Health (HSAM, LMN), Stanford University School of Medicine, CA; Center for Population Health Sciences (HSAM, LMN), Stanford University School of Medicine, CA; Health Economics Research Center (HSAM), Veterans Affairs Palo Alto Health Care System, CA; VA Multiple Sclerosis Center of Excellence-East (SJ, WJC, MW), Baltimore, MD; University of Maryland School of Medicine (WJC, MW), Neurology Department, Baltimore, MD; and Epidemiology Program (WJC), Health Outcomes of Military Exposures, Veteran Health Administration, Washington, DC.
Shan JinVA Palo Alto Healthcare System (HSAM), US Department of Veterans Affairs, Palo Alto, CA; Department of Epidemiology and Population Health (HSAM, LMN), Stanford University School of Medicine, CA; Center for Population Health Sciences (HSAM, LMN), Stanford University School of Medicine, CA; Health Economics Research Center (HSAM), Veterans Affairs Palo Alto Health Care System, CA; VA Multiple Sclerosis Center of Excellence-East (SJ, WJC, MW), Baltimore, MD; University of Maryland School of Medicine (WJC, MW), Neurology Department, Baltimore, MD; and Epidemiology Program (WJC), Health Outcomes of Military Exposures, Veteran Health Administration, Washington, DC.
William J CulpepperVA Palo Alto Healthcare System (HSAM), US Department of Veterans Affairs, Palo Alto, CA; Department of Epidemiology and Population Health (HSAM, LMN), Stanford University School of Medicine, CA; Center for Population Health Sciences (HSAM, LMN), Stanford University School of Medicine, CA; Health Economics Research Center (HSAM), Veterans Affairs Palo Alto Health Care System, CA; VA Multiple Sclerosis Center of Excellence-East (SJ, WJC, MW), Baltimore, MD; University of Maryland School of Medicine (WJC, MW), Neurology Department, Baltimore, MD; and Epidemiology Program (WJC), Health Outcomes of Military Exposures, Veteran Health Administration, Washington, DC.
Lorene M NelsonVA Palo Alto Healthcare System (HSAM), US Department of Veterans Affairs, Palo Alto, CA; Department of Epidemiology and Population Health (HSAM, LMN), Stanford University School of Medicine, CA; Center for Population Health Sciences (HSAM, LMN), Stanford University School of Medicine, CA; Health Economics Research Center (HSAM), Veterans Affairs Palo Alto Health Care System, CA; VA Multiple Sclerosis Center of Excellence-East (SJ, WJC, MW), Baltimore, MD; University of Maryland School of Medicine (WJC, MW), Neurology Department, Baltimore, MD; and Epidemiology Program (WJC), Health Outcomes of Military Exposures, Veteran Health Administration, Washington, DC.
Mitchell WallinVA Palo Alto Healthcare System (HSAM), US Department of Veterans Affairs, Palo Alto, CA; Department of Epidemiology and Population Health (HSAM, LMN), Stanford University School of Medicine, CA; Center for Population Health Sciences (HSAM, LMN), Stanford University School of Medicine, CA; Health Economics Research Center (HSAM), Veterans Affairs Palo Alto Health Care System, CA; VA Multiple Sclerosis Center of Excellence-East (SJ, WJC, MW), Baltimore, MD; University of Maryland School of Medicine (WJC, MW), Neurology Department, Baltimore, MD; and Epidemiology Program (WJC), Health Outcomes of Military Exposures, Veteran Health Administration, Washington, DC.
United States Department of Veterans Affairs · USMultiple Sclerosis Center of Atlanta · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Telemedicine may help to bridge the specialty care access gap for patients with MS (PwMS) restricted by distance or disability. The objective of this study is to assess the frequency and longitudinal patterns of telemedicine utilization among PwMS and controls. Methods: We conducted a population-based nested case-control study within the Veterans Health Administration (VHA) from January 1, 2010, to December 31, 2020. MS cases and controls were individually matched on sex, age, and Veterans Affair (VA) service region (Veterans Integrated Service Network). MS case and control participants sample sizes by year included 2010: 19,387/86,379; 2016: 19,752/88,535; and 2020: 16,451/78,315. Telemedicine encounter codes were used to identify telemedicine utilization among MS cases and controls in the VHA for 2010, 2016, and 2020. Telemedicine encounters were categorized according to mode (video, phone, and supplementary remote) and type of care provided. Results: Patients in the VHA have had increasing utilization of telemedicine over the past decade. Among PwMS, mean telemedicine encounters increased steadily from 2010 to 2020 (5.6-10.5 encounters/patient, respectively). Across all years, MS cases were significantly more likely than controls to use telemedicine. The odds ratios (ORs) (95% confidence interval [CI]) of any telemedicine utilization comparing MS cases with controls in 2010, 2016, and 2020, respectively, were 1.5 (CI: 1.3-1.5), 1.9 (CI: 1.8-2.0), and 1.7 (CI: 1.6-1.8). Compared with non-Hispanic White veterans, non-Hispanic Black veterans were more likely to use telemedicine (adjusted OR = 1.5; [CI: 1.40-1.60]). The most common and least common modes of telemedicine among cases and controls were telephone and supplementary remote, respectively. Comparing 2010 with 2020, the largest increases in telemedicine utilization exhibited among MS cases were among primary care, specialty care, specialty neurology care, and other types of health care. States with the highest increases in telemedicine utilization were AL, CA, CO, FL, GA, KS, IL, NY, and SC. PwMS tended to live in counties with more adverse social determinants of health compared with controls. Discussion: PwMS were significantly more likely to use telemedicine than their matched controls. There were significant increases in telemedicine utilization between 2010 and 2020. The VHA has a robust telemedicine system of care that has grown to supplement in person care more so than other US health care systems. Future work is needed to assess the determinants of telemedicine utilization.

Identifiers

PMID36540144
PMCPMC9757110
OpenAlexW4304807944

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.