Evidence map›Paper›PMID 42228910›Full record

ArticleJMIR human factors2026

Telehealth Use Among Older Adults Receiving Home- and Community-Based Services: Cross-Sectional Analysis Using the National Core Indicators-Aging and Disabilities Survey.

Dana P Urbanski, Romil R Parikh, Benjamin W Langworthy, Jack M Wolf, Chanee D Fabius, Janette Dill, Eric Jutkowitz, Tetyana P Shippee

Abstract read
In one paragraph

Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Dana P UrbanskiCollege of Arts and Sciences, Indiana University Bloomington, 2631 E Discovery Pkwy, Bloomington, IN, 47408, United States, 1 440-523-0350.ORCID 0000-0003-2781-9860
Romil R ParikhDivision of Health Policy & Management, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0001-6087-0583
Benjamin W LangworthyDivision of Biostatistics & Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0001-6735-3853
Jack M WolfDivision of Biostatistics & Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0002-8919-8740
Chanee D FabiusDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0003-1217-8415
Janette DillDivision of Health Policy & Management, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0002-4044-3127
Eric JutkowitzDepartment of Health Services, Policy & Practice, School of Public Health, Brown University, Providence, RI, United States.ORCID 0000-0002-1735-8434
Tetyana P ShippeeDivision of Health Policy & Management, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0003-1804-2527

Funding

Person-Reported and Health Care Utilization Outcomes of Home and Community Based Care Recipients With and Without Alzheimer's Disease and its Related DementiasRF1AG069771 · NIA · UNIVERSITY OF MINNESOTA · PI JUTKOWITZ, ERIC, SHIPPEE, TETYANA P. · 2020 to 2023
$2.4M
Microsimulation Modeling to Compare the Effectiveness and Cost-Effectiveness of Nondrug Interventions to Manage Clinical Symptoms in Racially/Ethnically Diverse Persons with DementiaR01AG060871 · NIA · BROWN UNIVERSITY · PI JUTKOWITZ, ERIC · 2019 to 2022
$1.7M
Person-Reported and Health Care Utilization Outcomes of Home and Community Based Care Recipients With and Without Alzheimer's Disease and its Related DementiasR01AG069771 · NIA · UNIVERSITY OF MINNESOTA · PI JUTKOWITZ, ERIC, SHIPPEE, TETYANA P. · 2024 to 2024
$514k
NIA NIH HHS R01 AG060871NIA NIH HHS R01 AG069771NIA NIH HHS RF1 AG069771
6 · The paper itself

Abstract

Background: Telehealth was essential for maintaining care continuity during the COVID-19 pandemic, leading to its rapid adoption across the United States. Telehealth has been heralded as a strategy for improving health care access and reducing health disparities, especially for community-dwelling older adults who face significant barriers to in-person care. However, data on telehealth use among socially and financially vulnerable older adults are limited, and little is known about characteristics associated with telehealth use in this population. Objective: Guided by the Systems Engineering Initiative for Patient Safety (SEIPS) 3.0 framework, this study examined factors associated with postpandemic telehealth use among older adults living at home and receiving publicly funded home- and community-based services (HCBS), considering HCBS receipt as an indicator of social and financial vulnerability. Methods: This cross-sectional study included older adults aged 65 years or older living at home with available telehealth use data who participated in the 2021-2022 survey wave of the National Core Indicators-Aging and Disabilities Adult Consumer Survey. We used complete-case multivariable logistic regression, adjusting for sociodemographic and health-related factors with state-level random intercepts, to examine associations between telehealth use and covariates of interest (age, sex, race/ethnicity, zip code, rural-urban commuting area code, internet access, self-perceived overall health, medical transportation access, living alone, number of known non-Alzheimer disease and related dementias [ADRD] diagnoses, known ADRD diagnosis, and HCBS program/payer type). Based on the regression results, we estimated bivariate associations between internet access and key sociodemographic variables (age, sex, race/ethnicity, and zip code rural-urban commuting area) using the Pearson chi-square test. Findings were organized and interpreted through the SEIPS 3.0 framework. Results: Of the 3680 participants, 1467 (40%) were telehealth users and 2213 (60%) were nonusers. Significantly lower odds of telehealth were observed for older adults in older age groups, males, Black individuals, those living in nonmetropolitan areas, and recipients of Older Americans Act services (odds ratios [OR] between 0.66 and 0.80). Individuals with more than one known non-ADRD diagnosis (OR 1.49, 95% CI 1.02-2.17) and those with an ADRD diagnosis (OR 1.33, 95% CI 1.07-1.66) had higher odds of telehealth use. Internet access was strongly associated with telehealth use (OR 2.51, 95% CI 2.15-2.92). Follow-up bivariate analyses between internet access and sociodemographic characteristics revealed that those of younger age, females, and White individuals had higher levels of internet access. Conclusions: Differences in telehealth use among older HCBS recipients are associated with multiple individual, technological, and organizational factors. Interpreted through the SEIPS 3.0 framework, these findings underscore the importance of viewing telehealth use as the outcome of multiple features of the health care system. Future research should clarify the mechanisms driving variation in telehealth use to identify and address barriers to telehealth adoption among vulnerable older adults.

Indexed as

Community Health ServicesCOVID-19Home Care ServicesTelemedicineAgedAged, 80 and overAging in PlaceCross-Sectional StudiesDigital HealthFemaleHealth Services AccessibilityHumansMaleUnited Statesaging in placehome- and community-based servicesinternet accessolder adultstelehealth

Identifiers

PMID42228910
PMCPMC13229466

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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.