Evidence map›Paper›PMID 38728070›Full record

ArticleJournal of medical Internet research2024

Prevalence and Disparities in Telehealth Use Among US Adults Following the COVID-19 Pandemic: National Cross-Sectional Survey.

Erin M Spaulding, Michael Fang, Yvonne Commodore-Mensah, Cheryl R Himmelfarb, Seth S Martin, Josef Coresh

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

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  9. Telehealth service use in people with cancer compared to people without cancer: analysis of Patient Experience Surveys in Australia.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

6 authors.

Erin M SpauldingJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID 0000-0001-8390-2277
Michael FangWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-2849-1780
Yvonne Commodore-MensahJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID 0000-0002-5054-3025
Cheryl R HimmelfarbJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID 0000-0003-1918-4316
Seth S MartinDigital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.ORCID 0000-0002-7021-7622
Josef CoreshWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-4598-0669

Funding

ARIC Neurocognitive Study (ARIC-NCS) Renewal 2023-2028U01HL096812 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI JOSEF CORESH, THOMAS H MOSLEY · 2010 to 2026
$65.7M
Sex Hormones in Pulmonary Arterial HypertensionP01HL108800 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI NEWMAN, JOHN HUGHES · 2012 to 2021
$22.0M
Leveraging the 24-hour movement paradigm to preserve cognitive function and prevent Alzheimer's disease: The Multi-Ethnic Study of Atherosclerosis (MESA) 24H-ACT StudyR01AG071032 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DIAZ, KEITH M, GABRIEL, KELLEY PETTEE · 2021 to 2024
$7.3M
Disparities in the management and prognosis of type 1 diabetesK01DK138273 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Michael Fang · 2024 to 2026
$470k
NHLBI NIH HHS P01 HL108800NHLBI NIH HHS U01 HL096812NIA NIH HHS R01 AG071032NIDDK NIH HHS K01 DK138273
6 · The paper itself

Abstract

backgroundTelemedicine expanded during the COVID-19 pandemic, though use differed by age, sex, race or ethnicity, educational attainment, income, and location. It is unclear if high telehealth use or inequities persisted late into the pandemic.

objectiveThis study aims to evaluate the prevalence of, inequities in, and primary reasons for telehealth visits a year after telemedicine expansion.

methodsWe used cross-sectional data from the 2022 Health Information National Trends Survey (HINTS 6), the first cycle with data on telemedicine. In total, 4830 English- and Spanish-speaking US adults (aged ≥18 years) were included in this study. The primary outcomes were telehealth visit attendance in the 12 months before March 7, 2022, to November 8, 2022, and the primary reason for the most recent telehealth visit. We evaluated sociodemographic and clinical predictors of telehealth visit attendance and the primary reason for the most recent telehealth visit through Poisson regression. Analyses were weighted according to HINTS 6 standards.

resultsWe included 4830 participants (mean age 48.3, SD 17.5 years; 50.28% women; 65.21% White). Among US adults, 38.78% reported having a telehealth visit in the previous year. Telehealth visit attendance rates were similar across age, race or ethnicity, income, and urban versus rural location. However, individuals with a telehealth visit were less likely to live in the Midwest (adjusted prevalence ratio [aPR] 0.65, 95% CI 0.54-0.77), and more likely to be women (aPR 1.21, 95% CI 1.06-1.38), college graduates or postgraduates (aPR 1.24, 95% CI 1.05-1.46), covered by health insurance (aPR 1.56, 95% CI 1.08-2.26), and married or cohabitating (aPR 1.17, 95% CI 1.03-1.32), adjusting for sociodemographic characteristics, frequency of health care visits, and comorbidities. Among participants with a telehealth visit in the past year, the primary reasons for their most recent visit were minor or acute illness (32.15%), chronic disease management (21%), mental health or substance abuse (16.94%), and an annual exam (16.22%). Older adults were more likely to report that the primary reason for their most recent telehealth visit was for chronic disease management (aPR 2.08, 95% CI 1.33-3.23), but less likely to report that it was for a mental health or substance abuse issue (aPR 0.19, 95% CI 0.10-0.35), adjusting for sociodemographic characteristics and frequency of health care visits.

conclusionsAmong US adults, telehealth visit attendance was high more than a year after telemedicine expansion and did not differ by age, race or ethnicity, income, or urban versus rural location. Telehealth could continue to be leveraged following COVID-19 to improve access to care and health equity.

Indexed as

COVID-19Healthcare DisparitiesTelemedicineAdolescentAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedPandemicsPrevalenceSARS-CoV-2United StatesYoung AdultCOVID-19delivery of health carehealth care disparitiestelehealthtelemedicine

Identifiers

PMID38728070
PMCPMC11127137

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LicenceCC BY
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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.