Evidence map›Paper›PMID 38669075›Full record

ArticleJMIR public health and surveillance2024

Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022.

Jiyeong Kim, Zhuo Ran Cai, Michael L Chen, Sonia Onyeka, Justin M Ko, Eleni Linos

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
12.5field-weighted citation impact, top 1% 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

23 citing papers in PubMed, 23 citations in OpenAlex.

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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 at 1 institution in 1 country.

Jiyeong KimStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-2869-5751
Zhuo Ran CaiStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-5611-2293
Michael L ChenStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-0168-1122
Sonia OnyekaStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0009-0006-5757-1180
Justin M KoStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0003-4232-5906
Eleni LinosStanford Center for Digital Health, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-5856-6301
Stanford Health Care · US

Funding

Patient Oriented Research in Vulnerable Populations with Skin DiseaseK24AR075060 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2019 to 2026
$1.6M
Novel digital tools for home-based monitoring of skin diseaseR01AR082109 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2023 to 2026
$629k
NIAMS NIH HHS K24 AR075060NIAMS NIH HHS R01 AR082109
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence.

objectiveWe aim to comprehensively assess telehealth use and its associated factors in the United States.

methodsThis cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model.

resultsAmong a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth.

conclusionsTo our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

Indexed as

COVID-19TelemedicineAdolescentAdultAgedCross-Sectional StudiesDemographyFemaleHealth Care SurveysHumansMaleMiddle AgedUnited StatesYoung Adultclinical practiceCOVID-19digital healthe-healthe-medicinehealthcare deliverypandemicpopulation-based studysociodemographic factortelehealthtelemedicineutilization

Identifiers

PMID38669075
PMCPMC11087857
OpenAlexW4392479212

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.