ArticleApplied clinical informatics2021
Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities.
Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
66 citing papers in PubMed, 2 syntheses or guidelines pooled it, 108 citations in OpenAlex.
- Satisfaction with telemedicine use during COVID-19 pandemic in the UK: a systematic review.The Libyan journal of medicine · 2024Pooled it
- Telehealth Use and Health Equity for Mental Health and Substance Use Disorder During the COVID-19 Pandemic: A Systematic Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2024Pooled it
- Patterns of Telemedicine Use and the Digital Divide Among Adults in Poland's Postpandemic Era: Nationwide Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- Assessing patient and caregiver satisfaction with outpatient palliative care telemedicine service at a tertiary care hospital in Karachi, Pakistan.Pakistan journal of medical sciences · 2026Article
- Dynamics of healthcare inequalities in type 2 diabetes mellitus across the COVID-19 pandemic: a real-world population-based study.BMC health services research · 2026Observational
- China's new quality productive forces in healthcare: spatial disparities, dynamic evolution, and convergence.BMC health services research · 2026Article
- Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.Journal of medical Internet research · 2026Observational
- Telehealth services utilization among middle-aged and older informal caregivers: evidence from national-level data in the United States.Frontiers in public health · 2026Article
- Exploring medical students' attitudes and perceptions toward artificial intelligence in medicine in Shandong Province, China.BMC medical education · 2025Article
- Design and implementation of mHealth applications for older people with cancer: A scoping review.Asia-Pacific journal of oncology nursing · 2025Review
- How limited english proficiency impacts patient engagement with telemedicine: a systematic review.NPJ digital medicine · 2025Article
- Demographic and socioeconomic factors influencing the adoption of telehealth services for substance use treatment.BMC public health · 2025Article
- Determinants of feasibility, acceptability and reach of mobile phone delivery of an Adolescent Transition Package (ATP) supporting the transition of youth living with HIV to adult HIV care in Kenya during the COVID-19 pandemic.BMC health services research · 2025Article
- Which Patients With Cancer Access Their Clinical Notes? A Disparities Analysis.JCO clinical cancer informatics · 2025Article
- Social vulnerability, lower broadband internet access, and rurality associated with lower telemedicine use in U.S. Counties.JAMIA open · 2025Article
- Sociodemographic variation in use of and preferences for digital technologies among patients in primary care: Results from the OurCare national survey.Canadian family physician Medecin de famille canadien · 2025Article
- Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study.JMIR formative research · 2025Article
- Public health emergency accelerated research response-the Clinical and Translational Science Institute of Southeast Wisconsin COVID-19 research initiative.Frontiers in public health · 2025Article
- Telehealth Adoption Among Saudi Older Adults: A Qualitative Analysis of Utilization and Barriers.Healthcare (Basel, Switzerland) · 2024Article
- Patterns of healthcare utilization according to health equity determinants during the first year of the pandemic at Johns Hopkins Medicine.JAMIA open · 2024Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe telemedicine industry has been experiencing fast growth in recent years. The outbreak of coronavirus disease 2019 (COVID-19) further accelerated the deployment and utilization of telemedicine services. An analysis of the socioeconomic characteristics of telemedicine users to understand potential socioeconomic gaps and disparities is critical for improving the adoption of telemedicine services among patients.
objectivesThis study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area.
methodsElectronic health record review of patients using telemedicine services compared with those not using telemedicine services within an academic-community health system: patient demographics (e.g., age, gender, race, and ethnicity), insurance status, and socioeconomic determinants obtained through block-level census data in Milwaukee area. The telemedicine users were compared with all other patients using regression analysis. The telemedicine adoption rates were calculated across regional ZIP codes to analyze the geographic patterns of telemedicine adoption.
resultsA total of 104,139 patients used telemedicine services during the study period. Patients who used video visits were younger (median age 48.12), more likely to be White (odds ratio [OR] 1.34; 95% confidence interval [CI], 1.31-1.37), and have private insurance (OR 1.43; CI, 1.41-1.46); patients who used telephone visits were older (median age 57.58), more likely to be Black (OR 1.31; CI 1.28-1.35), and have public insurance (OR 1.30; CI 1.27-1.32). In general, Latino and Asian populations were less likely to use telemedicine; women used more telemedicine services in general than men. In the multiple regression analysis of social determinant factors across 126 ZIP codes, college education (coefficient 1.41,
conclusionAdoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type. The study reveals the potential inequities and disparities in telemedicine adoption.
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Registered trials
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.