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Sociodemographic Disparities in Outpatient Cardiology Telemedicine During the COVID-19 Pandemic

2021; Lippincott Williams & Wilkins; Volume: 14; Issue: 8 Linguagem: Inglês

10.1161/circoutcomes.121.007813

1941-7705

Xiaowen Wang, Michael K. Hidrue, Marcela G. del Carmen, Rory B. Weiner, Jason H. Wasfy,

Healthcare Systems and Technology

HomeCirculation: Cardiovascular Quality and OutcomesVol. 14, No. 8Sociodemographic Disparities in Outpatient Cardiology Telemedicine During the COVID-19 Pandemic Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBSociodemographic Disparities in Outpatient Cardiology Telemedicine During the COVID-19 Pandemic Xiaowen Wang, Michael K. Hidrue, Marcela G. del Carmen, Rory B. Weiner and Jason H. Wasfy Xiaowen WangXiaowen Wang https://orcid.org/0000-0002-5374-7832 Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School (X.W.), Massachusetts General Hospital, Harvard Medical School, Boston. , Michael K. HidrueMichael K. Hidrue Massachusetts General Physicians Organization, Boston (M.K.H., M.G.d.C., J.H.W.). , Marcela G. del CarmenMarcela G. del Carmen Division of Gynecologic Oncology (M.G.d.C.), Massachusetts General Hospital, Harvard Medical School, Boston. Massachusetts General Physicians Organization, Boston (M.K.H., M.G.d.C., J.H.W.). , Rory B. WeinerRory B. Weiner Cardiology Division (R.B.W., J.H.W.), Massachusetts General Hospital, Harvard Medical School, Boston. and Jason H. WasfyJason H. Wasfy Correspondence to: Jason H. Wasfy, MD, MPhil, Massachusetts General Physicians Organization, Headquarters, Bulfinch 2, Boston, MA 02114. Email E-mail Address: [email protected] https://orcid.org/0000-0002-0871-5970 Cardiology Division (R.B.W., J.H.W.), Massachusetts General Hospital, Harvard Medical School, Boston. Massachusetts General Physicians Organization, Boston (M.K.H., M.G.d.C., J.H.W.). Originally published23 Jul 2021https://doi.org/10.1161/CIRCOUTCOMES.121.007813Circulation: Cardiovascular Quality and Outcomes. 2021;14:e007813Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: July 23, 2021: Ahead of Print Severe acute respiratory syndrome coronavirus 2 infected millions of people, causing profound stress to health care systems. To enhance the resilience of health care delivery and to limit disease spread, health care systems implemented video and telephone visits in lieu of in-person outpatient visits. We sought to understand the differences in utilization of video visits in outpatient cardiac care across different racial and socioeconomic groups.In this single-center retrospective study, we identified patients with outpatient cardiology encounters (in-person, video, or telephone) between March 23, 2020, and July 3, 2020, at Massachusetts General Hospital. This date range was selected as virtual visits (video and telephone) were highly encouraged during this time period, with >70% visits conducted as virtual visits. Patient characteristics included age, sex, race, language, income level, insurance type, education, and visit week. We estimated household income by assigning the median household income for the patient's zip code from the US census. Using patient-visit level data, we specified a generalized estimation equation to assess the independent association of sociodemographic variables on the likelihood of video visit. This project was approved by the Mass General Brigham Institutional Review Board. To minimize the possibility of unintentionally sharing information that can be used to reidentify private information, the analytical codes used for this study are available from the corresponding author upon reasonable request.A total of 10 113 patients (11 394 visits) were included in our analysis (Table). After adjustment, older patients were less likely to have had video visits (odds ratio [OR], 0.57 [0.51–0.64], for patients 61 to 75; OR, 0.29 [0.25–0.33], for patients >75, reference ≤60). Non-English speaking patients were less likely to have had video visits (OR, 0.59 [0.46–0.76], reference: English speaking). Compared with patients with commercial insurance, Medicaid and Medicare patients were less likely to have video visits (OR, 0.75 [0.59–0.95] and OR, 0.56 [0.51–0.64], respectively). Compared with those with a college degree, those with high school or lower education were less likely to make video visits (OR, 0.63 [0.56–0.71]) while those with graduate/postgraduate degree were more likely to make video visits (OR, 1.22 [1.07–1.39]). Compared with those with a median income of >$110 000, those with estimated income of $70 000 or less and those with estimated income of $71 000 to 90 000 were less likely to have video visits (OR, 0.57 [0.50–0.65] and OR, 0.87 [0.78–0.98], respectively). Finally, at the beginning of our study period, there were no differences in the likelihood of video visit by race. However, as the weeks went by, the odds of making a video visit increased roughly by13% per week for non-Black patients while the odds of making video visit for Black patients did not change over time (Table).Table. Sociodemographic Characteristics of Patients and Both Unadjusted and Independent Association With Video TelemedicineCovariaten (%)* (N=11 394 patient-visit)Unadjusted association†Adjusted association‡Proportion video (%)P valueOR95% CISex0.064 Female6578 (57.7)36.7Reference Male4816 (42.3)35.01.091.00–1.19Language<0.001 English10 829 (95.0)36.7Reference Non-English565 (5.0)20.50.590.46–0.76Payor<0.001 Commercial5201 (45.7)48.2Reference Medicaid431 (3.8)34.10.750.59–0.95 Medicare5762 (50.5)25.00.560.51–0.64Age group 75 y3637 (31.9)20.70.290.25–0.33Income group $ 110 0002444 (21.4)40.7Reference $ 91 000–$ 110 0002132 (18.7)38.70.880.77–1.01 $ 71 000–$ 90 0004101 (36.0)38.10.870.78–0.98 $ 70 000 or less2717 (23.9)26.20.570.50–0.65Education<0.001 College graduate4466 (39.2)41.0Reference Grad school or more1533 (13.5)44.21.221.07–1.39 High school or less2856 (25.1)25.80.630.56–0.71 Declined/unavailable2539 (22.3)33.40.810.73–0.91Race<0.001 White10 043 (88.1)36.4Reference Asian348 (3.1)41.41.080.60–1.95 Black378 (3.3)25.41.360.77–2.40 Others/declined§625 (5.5)32.30.910.57–1.45Race × week∥ White × week1.131.11–1.14 Asian × week1.131.06–1.20 Black × week1.030.97–1.09 Others × week1.121.08–1.18OR indicates odds ratio.* Proportion of total sample by sociodemographic characteristic.† Univariate comparisons based on χ2 tests.‡ OR estimates based on multivariable logistic regression adjusting for sex, age, race, neighborhood median income, education level, language at home (English vs others), and payor group.§ Including patients self-identified as Hispanic, Latino, or Dominican race.∥ Week is a continuous variable with value of zero for the first week of the study period. The interaction terms represent the change in the odds ratio of making a video visit as the pandemic period increases by one week.Our study identified significant disparities in video telemedicine between different racial and socioeconomic groups. Patients who were Black, poorer, non-English speaking, or with lower education had lower utilization of video visits, which confirms and extends prior work to a larger dataset and longer time period.1 Although our data source and study design limit our ability to make causal inferences, our results highlight the potential role of structural bias since our predictor variables are social constructs and social variables.2 Several studies have highlighted lack of digital access in older adults especially those with lower income, an issue further compounded by existence of other disabilities.3,4 Work schedules, broadband access, or access to computing devices may all have been mechanisms of structural bias, although we cannot directly measure these mechanisms or others from this study design. Improving access and usability for video platforms (eg, non-English software or access to broadband) could address these structural barriers and improve equity.3,4 Conversely, payment policies that reduce access for telephone visits could worsen disparities further.Our study has several limitations. First, it is a single-center study and the extent to which these results apply to other clinical areas is unknown. However, large administrative data sets do not typically include granular data, highlighting the importance of single-center analysis for this analytic aim. Second, we did not assess whether a decrease in accessing cardiac care overall may have contributed to observed disparity. The small number (<1%) of virtual visits prepandemic also limited our ability to compare to historical trends. Third, our study did not examine clinical outcomes related to these disparities. It is conceivable that video visits allow better communication, better assessment of patient's clinical status, and more patient satisfaction, all of which could influence clinical outcomes.In conclusion, during the early surge, large disparities exist in the utilization of video technology in outpatient cardiology. Such differences may lead to further disparities outcomes in disadvantaged groups and worsening inequity. Urgent measures are needed to improve equity in telemedicine platforms.Nonstandard Abbreviations and AcronymsORodds ratioSources of FundingThis work was funded with a grant from the American Heart Association (18 CDA 34110215) awarded to Dr Wasfy and the Massachusetts General Physicians Organization.Disclosures Dr Wasfy declares serving as a co-chair of the American College of Cardiology Roundtable on Telemedicine (without compensation). The other authors report no conflicts.FootnotesThis manuscript was sent to Dennis T. Ko, MD, Senior Guest Editor, for review by expert referees, editorial decision, and final disposition.For Sources of Funding and Disclosures, see page 913.Correspondence to: Jason H. Wasfy, MD, MPhil, Massachusetts General Physicians Organization, Headquarters, Bulfinch 2, Boston, MA 02114. Email jwasfy@mgh.harvard.eduReferences1. Eberly LA, Khatana SAM, Nathan AS, Snider C, Julien HM, Deleener ME, Adusumalli S. Telemedicine outpatient cardiovascular care during the COVID-19 pandemic: bridging or opening the digital divide?Circulation. 2020; 142:510–512. doi: 10.1161/CIRCULATIONAHA.120.048185LinkGoogle Scholar2. Breathett K, Spatz ES, Kramer DB, Essien UR, Wadhera RK, Peterson PN, Ho PM, Nallamothu BK. The groundwater of racial and ethnic disparities research.Circ Cardiovasc Qual Outcomes. 2021; 14:e007868. doi: 10.1161/CIRCOUTCOMES.121.007868LinkGoogle Scholar3. Lam K, Lu AD, Shi Y, Covinsky KE. Assessing telemedicine unreadiness among older adults in the United States during the COVID-19 pandemic.JAMA Intern Med. 2020; 180:1389–1391. doi: 10.1001/jamainternmed.2020.2671CrossrefMedlineGoogle Scholar4. Roberts ET, Mehrotra A. Assessment of disparities in digital access among medicare beneficiaries and implications for telemedicine.JAMA Intern Med. 2020; 180:1386–1389. doi: 10.1001/jamainternmed.2020.2666CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Osmanlliu E, Kalwani N, Parameswaran V, Qureshi L, Dash R, Scheinker D and Rodriguez F (2023) Sociodemographic disparities in the use of cardiovascular ambulatory care and telemedicine during the COVID-19 pandemic, American Heart Journal, 10.1016/j.ahj.2023.06.011, 263, (169-176), Online publication date: 1-Sep-2023. Boulos P, Freeman S, Henry T, Mahmud E and Messenger J (2023) Interaction of COVID-19 With Common Cardiovascular Disorders, Circulation Research, 132:10, (1259-1271), Online publication date: 12-May-2023. Mackwood M, Nagpal A, Yuen J and Cancino R (2022) Virtual Access to Subspecialty Care, Primary Care: Clinics in Office Practice, 10.1016/j.pop.2022.05.001, 49:4, (557-573), Online publication date: 1-Dec-2022. Ogunniyi M, Mahmoud Z, Commodore-Mensah Y, Fleg J, Fatade Y, Quesada O, Aggarwal N, Mattina D, Moraes De Oliveira G, Lindley K, Ovbiagele B, Roswell R, Douglass P, Itchhaporia D and Hayes S (2022) Eliminating Disparities in Cardiovascular Disease for Black Women, Journal of the American College of Cardiology, 10.1016/j.jacc.2022.08.769, 80:18, (1762-1771), Online publication date: 1-Nov-2022. Kalwani N, Osmanlliu E, Parameswaran V, Qureshi L, Dash R, Heidenreich P, Scheinker D and Rodriguez F (2022) Changes in telemedicine use and ambulatory visit volumes at a multispecialty cardiovascular center during the COVID-19 pandemic, Journal of Telemedicine and Telecare, 10.1177/1357633X211073428, (1357633X2110734) Superina S, Malik A, Moayedi Y, McGillion M and Ross H (2022) Digital Health: The Promise and Peril, Canadian Journal of Cardiology, 10.1016/j.cjca.2021.09.033, 38:2, (145-148), Online publication date: 1-Feb-2022. August 2021Vol 14, Issue 8 Advertisement Article InformationMetrics © 2021 American Heart Association, Inc.https://doi.org/10.1161/CIRCOUTCOMES.121.007813PMID: 34293931 Originally publishedJuly 23, 2021 Keywordscardiologycoronavirushealthhealth policyquality improvementPDF download Advertisement SubjectsEthics and PolicyHealth EquityQuality and Outcomes