Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19
| Autor: | Devin M. Mann, Oded Nov, Katharine Lawrence, Paul A. Testa, Ji Chen, Yuan Zhao, Rumi Chunara |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male medicine.medical_specialty Telemedicine AcademicSubjects/SCI01060 020205 medical informatics Ethnic group MEDLINE Health Informatics 02 engineering and technology Research and Applications Cohort Studies 03 medical and health sciences Racism 0302 clinical medicine Health care Odds Ratio 0202 electrical engineering electronic engineering information engineering medicine Electronic Health Records Humans 030212 general & internal medicine Healthcare Disparities 10. No inequality AcademicSubjects/MED00580 business.industry Risk of infection COVID-19 Middle Aged Quality Improvement Digital health Triage 3. Good health Family medicine Regression Analysis Female New York City AcademicSubjects/SCI01530 business Delivery of Health Care Cohort study |
| Zdroj: | Journal of the American Medical Informatics Association Journal of the American Medical Informatics Association : JAMIA |
| ISSN: | 1527-974X |
| DOI: | 10.1093/jamia/ocaa217 |
| Popis: | Objective Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage, and treatment. Racial and ethnic disparities in healthcare have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19. Materials and Methods Electronic health record data of patients at New York University Langone Health between March 19th and April 30, 2020 were used to conduct descriptive and multilevel regression analyses with respect to visit type (telemedicine or in-person), suspected COVID diagnosis, and COVID test results. Results Controlling for individual and community-level attributes, Black patients had 0.6 times the adjusted odds (95% CI: 0.58–0.63) of accessing care through telemedicine compared to white patients, though they are increasingly accessing telemedicine for urgent care, driven by a younger and female population. COVID diagnoses were significantly more likely for Black versus white telemedicine patients. Discussion There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of a zip code were also significantly related to telemedicine use. Conclusion Telemedicine access disparities reflect those in in-person healthcare access. Roots of disparate use are complex and reflect individual, community, and structural factors, including their intersection—many of which are due to systemic racism. Evidence regarding disparities that manifest through telemedicine can be used to inform tool design and systemic efforts to promote digital health equity. |
| Databáze: | OpenAIRE |
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