Racial Disparities in Telemedicine Uptake during the COVID-19 Pandemic among Patients with Hematologic Malignancies in the United States

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Natalia Neparidze, MD Krystal W. Lau, PhD Xiaoliang Wang, PhD Scott Huntington, MD, MPH Omer Jamy, MD Gregory S. Calip, PharmD, MPH, PhD Harsh Shah, DO Deborah M. Stephens, DO Rebecca Miksad, MD, MPH Ravi B. Parikh, MD, MPP Samuel Takvorian, MD, MSHP Gaurav Goyal, MD Erlene Seymour, MD

Abstract

Background: The COVID-19 pandemic impacted healthcare visit trends, transitioning care to utilize telemedicine. We aimed to investigate if the uptake in telemedicine during pandemic was equitable across racial groups for patients with hematologic malignancies.


Methods: Using the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database we analyzed patients with diagnosis of acute myelogenous leukemia (AML), diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), mantle cell lymphoma (MCL), chronic lymphocytic leukemia (CLL) or multiple myeloma (MM). Patients were categorized into treatment types within lines of therapy: outpatient (oral therapy and outpatient infusions combined with oral therapy) vs. inpatient treatments (chemotherapy, cellular therapy). Monthly visit rates were calculated as the number of visits (telemedicine or in-person [in-clinic treatment administration, vitals, and/or labs]) per active patient per 30-day standardized month. We used time-series forecasting methods on pre-pandemic monthly visit rate data (March 2016 - February 2020) to estimate projected counterfactual monthly visit rates between March 2020 - February 2021.Telemedicine uptake was descriptively analyzed over time (t).


Results: We included 18,924 active patients (2,394 Black and 16,530 White) and 884,504 visits (117,673 Black and 766,831 White). 4,053 AML, 3,468 diffuse large B cell lymphoma, 1,943 follicular lymphoma, 2,151 mantle cell lymphoma, 5,926 chronic lymphocytic leukemia and 7,752 myeloma patients. Black patients had no significant reductions in in-person visit rates throughout the pandemic period compared to the projected rates. Conversely, White patients experienced an 18% (95% PI 9.9% - 25%) lower rate of in-person visits for outpatient therapy during the early pandemic (March - May 2020) (actual monthly visit rate 1.61; projected visit rate 2.0 [95% CI 1.8-2.2]). Telemedicine uptake was significantly higher for White patients compared with Black patients for all diseases and treatment categories between March 2020-February 2021 (t = 9.5, p < 0.01), AML inpatient (t = 2.4, p = 0.04), MM outpatient (Figure 3C) (t = 6.0, p < 0.01) and MM inpatient treatment categories (Figure 3D) (t = 2.3, p = 0.04). 


Conclusions: White patients had significantly higher telemedicine uptake compared with Black patients for all treatment categories. These findings challenge healthcare systems to direct efforts toward reducing the gap in healthcare access.

Article Details

How to Cite
NEPARIDZE, Natalia et al. Racial Disparities in Telemedicine Uptake during the COVID-19 Pandemic among Patients with Hematologic Malignancies in the United States. Medical Research Archives, [S.l.], v. 12, n. 2, feb. 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/5164>. Date accessed: 28 apr. 2024. doi: https://doi.org/10.18103/mra.v12i2.5164.
Section
Research Articles

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. Jan 2019;69(1):7-34. doi:10.3322/caac.21551
2. Patt DA, Wilfong L, Toth S, et al. Telemedicine in Community Cancer Care: How Technology Helps Patients With Cancer Navigate a Pandemic. JCO Oncol Pract. Jan 2021;17(1):e11-e15. doi:10.1200/OP.20.00815
3. Mitchell UA, Chebli PG, Ruggiero L, Muramatsu N. The Digital Divide in Health-Related Technology Use: The Significance of Race/Ethnicity. Gerontologist. Jan 9 2019;59(1):6-14. doi:10.1093/geront/gny138
4. Jella TK, Cwalina TB, Sachdev RR, Otteson T, Fowler N. Sociodemographic disparities in the use of health information technology by a national sample of head and neck cancer patients. Am J Otolaryngol. Mar-Apr 2022;43(2):103308. doi:10.1016/j.amjoto.2021.103308
5. Kim HS, Kim HJ, Juon HS. Racial/Ethnic Disparities in Patient-Provider Communication and the Role of E-Health Use. J Health Commun. Mar 4 2021;26(3):194-203. doi:10.1080/10810730.2021.1919248
6. Cantor J, Schuler MS, Matthews S. Availability of Mental Telehealth Services in the US. JAMA Health Forum. 2024 Feb 2;5(2):e235142.
7. Iasiello JA, Rajan A, Zervos E. Racial Differences in Patient-Reported Access to Telehealth: An Important and Unmeasured Social Determinant of Health.JCO Oncol Pract. 2023 Dec;19(12):1215-1223.
8. Thomas E, Kennedy A, Walsh W. Telehealth through the pandemic at a safety net hospital: observations and next steps for cancer care delivery. Front Public Health. 2023 Jun 2;11:1186350.
9. Masias Gil, Marcelin JR, Zuniga-Blanco B, et al. COVID-19 Pandemic: Disparate Health Impact on the Hispanic/Latinx Population in the United States. J Infect. Dis. 2020; 222(10):1592-1595.
10. Price-Haywood EG, Burton J, Fort D, Seoane L. Hospitalization and Mortality among Black Patients and White Patients with Covid-19. N Engl J Med. Jun 25 2020;382(26):2534-2543. doi:10.1056/NEJMsa2011686
11. Vijenthira A, Gong IY, Fox TA, et al. Outcomes of patients with hematologic malignancies and COVID-19: a systematic review and meta-analysis of 3377 patients. Blood. Dec 17 2020;136(25):2881-2892. doi:10.1182/blood.2020008824
12. Chunara R, Zhao Y, Chen J, et al. Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19. J Am Med Inform Assoc. Jan 15 2021;28(1):33-41. doi:10.1093/jamia/ocaa217
13. Neeman E, Lyon L, Sun H, et al. Future of Teleoncology: Trends and Disparities in Telehealth and Secure Message Utilization in the COVID-19 Era. JCO Clin Cancer Inform. Mar 2022;6:e2100160. doi:10.1200/CCI.21.00160
14. Alkureishi MA, Choo ZY, Rahman A, et al. Digitally Disconnected: Qualitative Study of Patient Perspectives on the Digital Divide and Potential Solutions. JMIR Hum Factors. Dec 15 2021;8(4):e33364. doi:10.2196/33364
15. Jacobs M, Ellis C. Telemedicine disparities during COVID-19: Provider offering and individual technology availability. J Am Geriatr Soc. Sep 2021;69(9):2432-2434. doi:10.1111/jgs.17280