Evidence mapPaperPMID 41313208Full record

ArticleJournal of medical Internet research2025

Telehealth Usage Disparities in Israel in Light of the COVID-19 Pandemic: Retrospective Cohort Study of Intersectional Sociodemographic Patterns and Health Equity Implications.

Motti Haimi, Efrat Shadmi, Tzipi Hornik-Lurie, Daniel Sperling

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In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

4 authors.

Motti HaimiHealth Systems Management Department, Max Stern Academic College of Emek Yezreel, D. N Emek Yezreel, Emek Yezreel, 1930600, Israel, 972 46423504, 972 72334523.ORCID http://orcid.org/0000-0001-8751-9793
Efrat ShadmiDepartment of Nursing, University of Haifa, Haifa, Israel.ORCID http://orcid.org/0000-0001-9752-5724
Tzipi Hornik-LurieClalit Health Services, Tel Aviv, Israel.ORCID http://orcid.org/0000-0002-2122-5116
Daniel SperlingDepartment of Nursing, University of Haifa, Haifa, Israel.ORCID http://orcid.org/0000-0002-4371-7736

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Telehealth has become a transformative health care delivery approach post the COVID-19 pandemic. Although telehealth improves health care access and reduces disparities, mounting evidence suggests usage patterns may exacerbate pre-existing health care inequities. Understanding these patterns across diverse populations is crucial for equitable digital health implementation. Objective: This study aimed to examine telehealth usage patterns across sociodemographic groups in Israel's universal health system to identify equity issues. We investigated variations across intersecting demographic characteristics during pre-, mid-, and post-COVID-19 periods and assessed evolving after-hours usage patterns. Methods: We conducted a retrospective cohort analysis using health and administrative data from the electronic database of Clalit Health Services' Sharon-Shomron District in Israel. The study population comprised 499,607 adult members (≥25 years; mean age 50.6, SD 16.5 years) with continuous enrollment from March 2019 to February 2022. We analyzed telehealth usage across 3 periods that are pre-COVID-19 (March 2019-February 2020), COVID-19 (March 2020-February 2021), and post-COVID-19 (March 2021-February 2022). Telehealth services included telephone consultations, video consultations, and TYTO (Tytocare) remote diagnostic device usage. Primary outcomes were telehealth usage rates and after-hours usage patterns. We used descriptive statistics, temporal trend analysis, and multivariable logistic regression with bootstrapping. Results: Telehealth usage among unique members more than doubled from 4.06% (20,264/499,607) pre-COVID-19 to 9.38% (46,868/499,607) post-COVID-19. Significant intersectional disparities emerged across multiple dimensions. In the post-COVID-19 period, young adults (25-35 years) used telehealth at 3.1 times the rate of older adults (≥70 years; 18,333/102,533, 17.9% vs 4129/72,280, 5.7%). Women consistently showed higher usage than men (26,702/258,471, 10.3% vs 20,166/241,136, 8.4% post-COVID-19). Profound socioeconomic disparities persisted, with high socioeconomic status members using telehealth at nearly 4 times the rate of low socioeconomic status members (19,064/172,011, 11.1% vs 1328/56,154, 2.4% post-COVID-19). Cultural differences were striking: religious Jewish sector members demonstrated nearly 10-fold higher usage than Arab and Bedouin members (904/7630, 11.8% vs 1125/76,895, 1.5% post-COVID-19). A U-shaped relationship with peripherality (geographic distance from major urban centers and service availability) persisted after adjusting for socioeconomic status. In geographic analyses, this pattern remained across locations. After-hours telehealth usage declined from 65% (324,744/499,607) of all telehealth visits pre-COVID-19 to 49% (244,807/499,607) post-COVID-19, indicating telehealth's evolution from an after-hours alternative to an integrated health care component. Multivariable analysis confirmed these disparities remained significant after adjusting for demographic and health factors. Conclusions: Telehealth expansion benefits remain unevenly distributed across populations in Israel's universal health care system. Significant disparities along age, socioeconomic, cultural, and geographic lines suggest that digital health innovations may widen existing health care inequities without interventions. Intersectional disparities require multidimensional approaches to overlapping barriers. Health care systems must intentionally address equity considerations to ensure digital health and telehealth integration reduces, not worsens, existing health care disparities in routine care delivery.

Indexed as

COVID-19Healthcare DisparitiesHealth EquityTelemedicineAdultAgedFemaleHumansIsraelMaleMiddle AgedPandemicsRetrospective StudiesSARS-CoV-2Sociodemographic Factorsafter-hoursdigital healthequityintersectionalitytelehealth

Identifiers

PMID41313208
PMCPMC12661909

What Socratic holds

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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 Socratic graph.