Evidence map›Paper›PMID 39586091›Full record

ArticleJournal of medical Internet research2024

Impact of Telehealth on Health Disparities Associated With Travel Time to Hospital for Patients With Recurrent Admissions: 4-Year Panel Data Analysis.

Youyou Tao, Ace Vo, Dezhi Wu, Junyuan Lin, Kala Seal, Abhay Mishra, Arindam Brahma

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

7 authors.

Youyou TaoLoyola Marymount University, Los Angeles, CA, United States.ORCID 0000-0001-8572-4830
Ace VoLoyola Marymount University, Los Angeles, CA, United States.ORCID 0000-0001-9363-2688
Dezhi WuUniversity of South Carolina, Columbia, SC, United States.ORCID 0000-0002-3554-1136
Junyuan LinLoyola Marymount University, Los Angeles, CA, United States.ORCID 0000-0003-1730-1646
Kala SealLoyola Marymount University, Los Angeles, CA, United States.ORCID 0000-0002-3933-3676
Abhay MishraIowa State University, Ames, IA, United States.ORCID 0000-0002-2448-0139
Arindam BrahmaLoyola Marymount University, Los Angeles, CA, United States.ORCID 0000-0001-7653-3709

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeographic, demographic, and socioeconomic differences in health outcomes persist despite the global focus on these issues by health organizations. Barriers to accessing care contribute significantly to these health disparities. Among these barriers, those related to travel time-the time required for patients to travel from their residences to health facilities-remain understudied compared with others.

objectiveThis study aimed to explore the impact of telehealth in addressing health disparities associated with travel time to hospitals for patients with recurrent hospital admissions. It specifically examined the role of telehealth in reducing in-hospital length of stay (LOS) for patients living farther from the hospital.

methodsWe sourced the data from 4 datasets, and our final effective sample consisted of 1,600,699 admissions from 536,182 patients from 63 hospitals in New York and Florida in the United States from 2012 to 2015. We applied fixed-effect models to examine the direct effects and the interaction between telehealth and patients' travel time to hospitals on LOS. We further conducted a series of robustness checks to validate our main models and performed post hoc analyses to explore the different effects of telehealth across various patient groups.

resultsOur summary statistics show that, on average, 22.08% (353,396/1,600,699) of patients were admitted to a hospital with telehealth adopted, with an average LOS of 5.57 (SD 5.06) days and an average travel time of about 16.89 (SD 13.32) minutes. We found that telehealth adoption is associated with a reduced LOS (P<.001) and this effect is especially pronounced as the patients' drive time to the hospital increases. Specifically, the coefficient for drive time is -0.0079 (P<.001), indicating that for every additional minute of driving time, there is a decrease of 0.0079 days (approximately 11 minutes) in the expected LOS. We also found that telehealth adoption has a larger impact on patients frequently needing health services, patients living in high internet coverage areas, and patients who have high virtualization potential diseases.

conclusionsOur findings suggest that telehealth adoption can mitigate certain health disparities for patients living farther from hospitals. This study provides key insights for health care practitioners and policy makers on telehealth's role in addressing distance-related disparities and planning health care resources. It also has practical implications for hospitals in resource-limited countries that are in the early stages of implementing telehealth.

Indexed as

Length of StayTelemedicineTravelAdolescentAdultAgedFemaleFloridaHealthcare DisparitiesHealth Services AccessibilityHospitalizationHumansMaleMiddle AgedNew YorkTime Factorshealth care accesshealth disparitieslength of stayrecurrent admissionstelehealthtravel timevirtual carevirtualization potential

Identifiers

PMID39586091
PMCPMC11629038

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LicenceCC BY
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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.