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The impact of COVID-19 on racial and ethnic disparities in cardiac procedural care

Open AccessPublished:January 09, 2023DOI:https://doi.org/10.1053/j.jvca.2023.01.006

      Abstract

      Objective

      : The primary objective of this study was to evaluate whether the COVID-19 pandemic altered the racial and ethnic composition of patient receiving for cardiac procedural care.

      Design

      : This was a retrospective observational study.

      Setting

      : This study was conducted at a single tertiary university hospital.

      Participants

      : 1,704 adult patients undergoing transcatheter aortic valve replacement (TAVR) (n=413), coronary artery bypass grafting (CABG) (n=506), or atrial fibrillation (AF) ablation (n=785) from March 2019 through March 2022 were included in this study.

      Interventions

      : No interventions were performed as this was a retrospective observational study.

      Measurements and Main Results

      : Patients were grouped based on the date of their procedure: pre-COVID (03/2019 to 02/2020), COVID Year 1 (03/2020 to 02/2021), and COVID Year 2 (03/2021 to 03/2022). Population-adjusted procedural incidence rates during each period were examined and stratified based on race and ethnicity. The procedural incidence rate was higher for Whites vs. Blacks and non-Hispanics vs. Hispanics for every procedure and every time period. For TAVR, the difference in procedural rates between Whites vs. Blacks decreased between the pre-COVID and COVID Year 1 (12.05 to 6.34 per 1,000,000 persons). For CABG, the difference in procedural rates between Whites vs. Blacks and non-Hispanics vs. Hispanics did not change significantly. For AF ablations, the difference in procedural rates between Whites vs. Blacks increased over time (13.06 to 21.55 to 29.64 per 1,000,000 persons in the pre-COVID, COVID Year 1, and COVID Year 2, respectively).

      Conclusion

      : Racial and ethnic disparities in access to cardiac procedural care were present throughout all study time periods at our institution. Our findings reinforce the continuing need for initiatives to reduce racial and ethnic disparities in healthcare. Further studies are needed to fully elucidate the effects of the COVID-19 pandemic on healthcare access and delivery.

      Keywords

      Background

      Racial and ethnic disparities in healthcare access and delivery in the United States have been extensively reported across various fields (1–4). Compared to White patients, Black patients are less likely to receive medical procedures and diagnostic tests, and have a lower life expectancy and worse health outcomes (5,6). At the federal, state and local level, several institutions including US Department of Health and Human Services Office of Minority Health, the National Institute on Minority Health and Health Disparities, the CDC and others have implemented several strategies to address health disparities and promote health equity since the 1990s (1). Some of these interventions include diabetes prevention programs in American Indian and Alaska Native communities, the National Hypertension Control Initiative, implementation of cultural competency training for healthcare providers and pipeline programs to increase underrepresented minority healthcare providers.
      Data with regards to racial and ethnic disparities in access to cardiovascular procedures have also been previously published (7–9). Minority Americans compared to White Americans have worse outcomes and increased mortality for cardiac related care (10,11). Contemporary data with regards to racial and ethnic disparities in cardiac procedural care are limited, especially in the setting of the recent coronavirus disease 2019 (COVID-19) pandemic.
      The COVID-19 pandemic has also disproportionately affected people of color and minority Americans in terms of prevalence, mortality, and outcomes (12,13). The age-adjusted COVID-19 death rate for Latino/Hispanic residents in Los Angeles County was more than 2.5x the rate for White residents, 452 compared to 176 per 100,000. Furthermore, nationwide surgical case cancellations due to the lack of hospital resources and capacity have exacerbated issues related to access to healthcare (14). The primary objective of this study was to determine whether or not the COVID-19 pandemic has led to worsening racial and ethnic disparities in access to cardiac procedural care at a single center within Los Angeles County.

      Methods

      After obtaining Institutional Review Board approval, all adult patients undergoing transcatheter aortic valve replacement (TAVR), coronary artery bypass grafting (CABG), or atrial fibrillation (AF) ablation from March 2019 through March 2022 at our tertiary care university hospital were included in this retrospective observational study. Patients undergoing combined surgical procedures such as CABG along with valve surgery or CABG along with solid organ transplantation were also included in the study.
      Data elements such as patient age, sex, ethnicity, race, insurance provider, pre-procedural admission status, zip code, procedure type, and procedure year were collected from the electronic medical record and institutional databases. The patient's zip code was used to identify Los Angeles County residents. Additionally, zip code data was converted to zip code tabulation areas (ZCTA) which were then used to collect socioeonomic status information, including median income, percent of families living in poverty, and percent unemployment, from the American Community Survey database available through the US Census Bureau. Patients were separated into three groups based on the date of their procedure: pre-COVID indicating March 2019 to February 2020, COVID Year 1 indicating March 2020 to February 2021, and COVID Year 2 indicating March 2021 to March 2022. The procedural incidence rates were adjusted to the Los Angeles County population based on data from the 2020 United States Census Bureau (15). For each study period, these population-adjusted incidence rates were examined and stratified based on race and ethnicity.

      Statistical analysis

      The primary objective was to evaluate whether or not the COVID-19 pandemic has led to worsening racial and ethnic disparities in access to TAVR, CABG, or AF ablation for patients at our institution. All summary data are presented as median and interquartile ranges or as number and percentages. The procedural incidence rates are reported as adjusted to the county population as cases per 1,000,000 persons. Statistical analysis with one-way ANOVA, Kruskal-Wallis or chi-square tests were used to compare the groups. All data were analyzed using STATA statistical software version 14.0 (StataCorp, LLC, College Station, Texas, USA), and p<0.05 was considered statistically significant.

      Results

      A total of 1,341 patients were identified in the database search. Only 11 patients were excluded (3 undergoing TAVR, 1 undergoing CABG, and 7 undergoing AF ablation) because of incomplete demographic data, such as unknown address, insurance provider or admission status. Of the remaining 1,330 patients included in the study, there were 283 patients undergoing TAVR, 455 patients undergoing CABG, and 592 undergoing AF ablation. There were no significant differences in age, sex, race, insurance provider, and pre-procedural admission status between the pre-COVID, COVID Year 1, and COVID Year 2 groups for each procedure (Table 1). There was, however, a significant difference in the distribution of Latino/Hispanic patients vs. non-Latino/Hispanic patients during COVID Year 1 for CABG procedures (Table 1b).
      Table 1aDemographics for AF Ablation
      Pre-COVID (n=160)COVID Year 1 (n=177)COVID Year 2 (n=255)p
      Age (years)63 (12.3)64 (10.7)66 (11.5)0.111
      Sex (female)58 (36.25)48 (27.11)93 (36.47)0.092
      Ethnicity0.17
      Hispanic/Latino7 (4.37)11 (6.21)27 (10.58)
      Not Hispanic/Latino137 (85.62)147 (83.05)206 (80.78)
      Not reported/not answered16 (10.0)19 (10.73)22 (8.62)
      Race0.371
      American Indian/Alaska Native2 (1.25)1 (0.56)1 (0.39)
      Asian12 (7.5)11 (6.21)14 (5.49)
      Black/African American7 (4.37)3 (1.69)4 (1.56)
      Native Hawaiian/Pacific Islander0 (0.0)0 (0.0)1 (0.39)
      Not reported/not answered10 (6.25)18 (10.16)30 (11.76)
      Other11 (6.87)6 (3.39)18 (7.05)
      White118 (73.75)138 (77.96)187 (73.33)
      Insurance provider0.61
      Commercial75 (46.87)81 (45.76)95 (37.25)
      Medi-Cal2 (1.25)1 (0.56)4 (1.56)
      Medicare63 (39.37)72 (40.67)115 (45.09)
      Other2 (1.25)3 (1.69)3 (1.17)
      Managed Care18 (11.25)20 (11.29)38 (14.90)
      Pre-procedure admission status0.539
      Same day admit157 (98.12)176 (99.43)252 (98.82)
      Inpatient0 (0.0)0 (0.0)0 (0.0)
      ED admit3 (1.87)1 (0.56)3 (1.17)
      Socioeconomic factors (ZCTA-based)
      Median income (USD)102867 (35027)106026 (37327)101496 (33084)0.411
      Families in poverty (%)5 (3.4)5 (3.9)6 (4.1)0.422
      Unemployed (%)5 (1.8)5 (1.5)5 (1.6)0.176
      Outcomes
      Hospital length of stay (hours)31 (30.0)21 (9.9)21 (18.4)<0.005
      ICU length of stay (hours)1 (12.1)0 (4.1)0 (9.1)0.245
      Table 1bDemographics for CABG
      Pre-COVID (n=167)COVID Year 1 (n=130)COVID Year 2 (n=158)p
      Age (years)65 (9.4)64 (10.5)65 (11.6)0.88
      Sex (female)32 (19.16)28 (21.53)21 (13.29)0.161
      Ethnicity0.025
      Hispanic/Latino27 (16.16)35 (26.92)29 (18.35)
      Not Hispanic/Latino132 (79.04)86 (66.15)111 (70.25)
      Not reported/not answered8 (4.79)9 (6.92)18 (11.39)
      Race0.062
      American Indian/Alaska Native3 (1.796)0 (0.0)0 (0.0)
      Asian19 (11.37)20 (15.38)19 (12.02)
      Black/African American11 (6.58)5 (3.84)7 (4.43)
      Native Hawaiian/Pacific Islander1 (0.59)2 (1.53)1 (0.63)
      Not reported/not answered6 (3.59)8 (6.15)19 (12.02)
      Other27 (16.168)30 (23.07)32 (20.25)
      White100 (59.88)65 (50.0)80 (50.63)
      Insurance provider0.492
      Commercial44 (26.34)47 (36.15)42 (26.58)
      Medi-Cal16 (9.58)11 (8.46)18 (11.39)
      Medicare81 (48.50)59 (45.38)76 (48.10)
      Other6 (3.59)2 (1.53)2 (1.26)
      Managed Care20 (11.97)11 (8.46)20 (12.65)
      Pre-procedure admission status0.447
      Same day admit72 (43.11)65 (50.0)81 (51.26)
      Inpatient37 (22.15)31 (23.84)33 (20.88)
      ED admit58 (34.73)34 (26.15)44 (27.84)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)88047 (32622)86038 (32948)92318 (36657)0.274
      Families in poverty (%)8 (5.9)8 (5.7)7 (5.6)0.67
      Unemployed (%)6 (1.8)6 (1.9)6 (1.7)0.523
      Outcomes
      Hospital length of stay (hours)359 (329.7)420 (1105.5)310 (233.7)0.348
      ICU length of stay (hours)217 (320.7)587 (4841.6)117 (90.2)0.283
      When Latino/Hispanic patients were compared to non-Latino/Hispanic patients according to time period and procedure, several additional differences were notable (Table 2). Within COVID year 2, Latino/Hispanic patients undergoing AF ablation and CABG were statistically younger than their non-Latino/Hispanic counterparts (Table 2a and 2b). For AF ablation and TAVR in COVID year 1 and year 2 as well as CABG in all years, Latino/Hispanic patients resided in zip codes with a lower median incomes and higher percentage of families in poverty. The distribution of the median incomes throughout all three time periods remained consistent within each ethnic group (Figure 1). Additionally in the pre-COVID time period for AF ablation and COVID year 2 for TAVR, the distribution of insurance providers was different between ethnic groups.
      Figure 1
      Figure 1ZCTA-median income data for pre-COVID, COVID year 1 and COVID year 2 in Latino/Hispanic versus non-Latino/Hispanic Patients in (a) AF ablation, (b) CABG, and (c) TAVR. The median income was divided into deciles (10 bins) and charted as a smooth histogram as a frequency of the total population for each ethnic group and time period.
      Similar to Latino/Hispanic patients, Black/African American patients were statistically younger than their non-Hispanic White peers when undergoing CABG (Table 3). For all procedures, the addresses of Black/African American patients were in zip codes with lower median income, higher percent of families in poverty and increased percentage of unemployment. The smoothed histogram of the median income deciles revealed the non-Hispanic White patients tended to have a right skewed distribution with a higher median income mode compared to Black/African Americans (Figure 2). There were no differences in the total hospital and ICU length of stay between these two racial groups.
      Figure 2
      Figure 2ZCTA-median income data for pre-COVID, COVID year 1 and COVID year 2 in Black/African American versus non-Hispanic White Patients in (a) AF ablation, (b) CABG, and (c) TAVR. The median income was divided into deciles (10 bins) and charted as a smooth histogram as a frequency of the total population for each ethnic group and time period.
      The population-adjusted procedural incidence rate was higher for White patients compared to Black patients and for non-Hispanic patients compared to Hispanic patients at every time point in the study period (Table 4). For AF ablation, the difference in procedural incidence rates between non-Hispanic White patients and Black/African American patients increased from 3.63 to 4.72 to 6.51 per 100,000 persons in the pre-COVID, COVID Year 1, and COVID Year 2 groups, respectively. A similar trend was seen when comparing non-Latino/Hispanic patients to Latino/Hispanic patients, as the difference in procedural incidence rates increased from 2.57 to 2.7 to 3.54 per 100,000 persons in the pre-COVID, COVID Year 1, and COVID Year 2 groups, respectively. The largest differences in population-adjusted procedural incidence rates between White patients and Black patients and between non-Hispanic patients and Hispanic patients were seen with AF ablation rates in all three study time periods (Table 4).
      For TAVR, the difference in procedural incidence rates between White patients and Black patients decreased from 2.22 per 100,000 persons in the pre-COVID group to 1.37 per 100,00 persons in COVID year 1 prior to returning to a similar difference in COVID year 2 (2.06 per 100,000). The procedural incidence rates between non-Latino/Hispanic patients to Latino/Hispanic patients undergoing TAVR remained relatively stable throughout all three time periods, 1.33 to 1.43 to 1.33 per 100,000 persons.
      For CABG, the difference in procedural incidence rates between White patients and Black patients decreased between pre-COVID and COVID year 1 prior to returning to pre-COVID rates in COVID year 2, 2.22 to 1.52 to 2.06 per 100,000 persons, respectively. From pre-COVID to COVID year 1, the difference in procedural incidence rates for Hispanic/Latino versus non-Hispanic/Latino decreased, 2.03 to 0.97 per 100,000 persons. Between COVID year 1 and year 2, the difference increased, 0.97 to 1.6 per 100,000 persons, though it did not return to the pre-COVID rate.

      Discussion

      In this study, we report data on discrepancies in procedural incidence rates between Non-Hispanic White and Black/African American patients and between non-Latino/Hispanic and Latino/Hispanic patients and how these differences changed over time at our institution. The COVID-19 pandemic was associated with an increase in disparities between White patients and Black patients and between non-Hispanic patients and Hispanic patients with AF undergoing catheter ablations. Surprisingly, the disparities between non-Hispanic White and Black/African American patients and between non-Latino Hispanic patients and Latino/Hispanic patients undergoing CABG and TAVR decreased with the onset of the COVID-19 pandemic prior to returning to near pre-pandemic rates. The disparities between non-Hispanic patients and Hispanic patients undergoing TAVR did not change significantly over time.
      Racial and ethnic disparities in access to healthcare have previously been reported in various fields. One broad-ranging study published by the American Public Health Association reported that White patients were more likely to receive higher-cost care and have access to higher-technology health services compared to Black patients, and that the disparity could not be explained by differences in the disease prevalence, patients’ clinical characteristics, or financial barriers (5). Racial and ethnic disparities in use of surgical procedures have been well described across a variety of surgical subspecialties (2–5). Despite numerous national and local initiatives to reduce racial differences in access to health care, Jha et al. found no meaningful change in disparities between White and Black Medicare enrollees (1). While healthcare-focused interventions are important, they are insufficient to fully address health disparities if social determinants of health, such as economic stability and opportunity, access to quality education, safe and affordable housing, food security and community support/engagement access, are not also addressed.
      The discrepancy in procedural and surgical rates is also evident in cardiovascular care. With regards to coronary artery disease, previous studies have published data showing lower rates of myocardial revascularization by percutaneous interventions or CABG in Black patients compared to White patients (7–9,16,17). There have also been previous reports of discrepancies in the use of catheter ablation in patients with AF (18–20), and more recently in access to TAVR procedures in patients with aortic stenosis (21–23). The disparities are not limited to just access to cardiac procedures and surgeries, but also include worse outcomes and increased mortality for minorities who undergo such procedures (5,6). In our present study, we similarly found that the procedural incidence rates were higher for White patients and non-Latino/Hispanic patients undergoing CABG, AF ablation, and TAVR at every time point throughout our study period. This is consistent with data that has been previously reported in the literature.
      The COVID-19 pandemic has also disproportionately affected minority Americans more so than White Americans. Minorities are more likely to be of lower socioeconomic status, suffer from chronic medical conditions that are poorly controlled, have lower healthcare literacy and access to healthcare, and experience living and working conditions that predispose them to worse outcomes (24). Though the most pervasive disparities have been reported among Black and Hispanic patients, there are data to suggest that these disparities exist for other minorities such as American Indian/Alaskan Native and Native Hawaiian/Pacific Islander populations as well (12). Other studies have reported a higher incidence of COVID-19 and COVID-19-related hospitalizations and deaths in racial and ethnic minority groups compared to White Americans (13,25,26).
      Nevertheless, there is a paucity of data analyzing the effects of the COVID-19 pandemic on access to cardiac procedural care. We initially hypothesized that the disparities in cardiac procedure rates would be exacerbated by the pandemic considering the previously published data. Interestingly, we found that discrepancies in procedural rates for Black patients and Hispanic patients requiring CABG and TAVR decreased at the onset of the pandemic. As COVID disproportionately affected minority populations, an unintended consequence of this disparity may have been that more minority patients interacted with the healthcare system during COVID and more underlying cardiac conditions were diagnosed and intervened upon. This increased minority patient-healthcare interaction may have led to better access at a higher-level center for cardiac procedural care that was more urgent or emergent such as severe aortic stenosis and acute coronary syndromes. In our study, we also found that discrepancies in the procedural rates for Black and Hispanic patients undergoing AF ablation increased significantly during the pandemic, which we posit may be a disappointing trend towards worsening disparities in access to more elective, non-urgent procedures for minorities. Given the observational nature of this study and the multitude of potential confounding factors, we cannot definitively conclude that the COVID-19 pandemic is responsible for these trends. However, our data does confirm that disparities in access to cardiac procedural care are still prevalent at our institution.
      The causes of disparities in healthcare access and delivery are multifactorial, and as such, strategies to reduce these disparities must be multifaceted. One approach has been a push to improve the diversification and cultural competency of the healthcare workforce, as there is evidence to suggest this may help address racial and ethnic disparities (27,28). In the last five years, there has been an exponential increase in publications and discussions regarding the effective implementation of diversity, equity and inclusion programs in all aspects of medicine, nursing, and science (29–35). While some progress has been made, there is ample evidence that racial and ethnic disparities still remain prevalent (34,36,37). Our institution participates in several diversity, equity and inclusion programs to introduce underrepresented minority students at all training levels to medicine and engages with the community to promote education and build support networks to ensure we can be a trusted resource for at-risk populations. As COVID has shown, the populace needs to know the healthcare remains a ‘helping’ profession who can be trusted to care for individuals in moments of vulnerability.
      Despite efforts within the healthcare system, perhaps the largest contributing causes to these disparities are related to social determinants of health that are external to healthcare systems (27). Unsurprisingly in our study, Black/African American and Latino/Hispanic patients were more likely to reside within areas with indicators of lower socioeconomic status such as lower median income and higher percentage of families living in poverty or dealing with unemployment. Therefore, interventions focused on the health care sector are most likely to be insufficient to address these population-level health disparities. Thornton et al. reviewed the evidence and presented recommendations for a multipronged approach to reducing health disparities, including interventions surrounding early childhood education, parental support programs, urban planning and community development, housing quality and neighborhood safety, income enhancements and supplements, and specific employment interventions (38). There are of course financial and logistical challenges to the implementation of these strategies that need to be addressed in order to make any progress in reducing healthcare disparities. Governmental advocacy at the local, state and federal level is important to inform lawmakers and policy makers of the extent of the problem as well as to them there is political will to address these problems with novel, evidence-based solutions that are multidisciplinary in nature. Local and national non-governmental organizations and most medical societies are involved in these activities and can serve as a good resource for those who want further information.
      This study has a few inherent limitations that should be acknowledged. The data collected and analyzed in this study are dependent on the accuracy and completeness of records stored in our institutional databases and the reliability of our automated electronic data extraction tools. Because this was a retrospective analysis, we were unable to verify the accuracy of each patients’ reported race and ethnicity, and it is possible that patients who declined to report their race or ethnicity or reported “Other” may be misclassified. It is also possible that other clinical practice changes during the COVID-19 pandemic may have occurred over the study period resulting in unknown confounders that may influence the outcomes of this study. Particularly during the first year of the pandemic, resource allocation was constantly shifted in order to manage the increased hospitalizations due to COVID and its associated sequelae. We chose to study AF ablation, CABG, and TAVR as they are associated with cardiovascular pathophysiology that requires prompt intervention. Though we did see a decline in these cases in the first year of the pandemic, our institution made every effort to limit cancellations for urgent cardiac procedures and perform these procedures within a narrow frame of time after the initial cancellation to ensure timely patient care. Lastly, we report data from a single tertiary care academic institution with a diverse patient population, and the results may not be generalizable to other clinical settings or institutions.

      Conclusion

      In conclusion, racial and ethnic disparities in access to cardiac procedural care were present throughout all study time periods at our institution. The COVID-19 pandemic was associated with an increase in disparities for patients undergoing AF ablation, a decrease in disparities for patients undergoing TAVR, and no change in disparities for patients undergoing CABG. The findings of our study reinforce the continuing need for initiatives to reduce racial and ethnic disparities in medicine and to achieve equal access to health care.(Table 1c, 2a, 2b 2c, 3a, 3b, 3c)
      Table 1cDemographics for TAVR
      Pre-COVID (n=85)COVID Year 1 (n=87)COVID Year 2 (n=111)p
      Age (years)80 (7.9)77 (10.4)78 (8.2)0.102
      Sex (female)38 (44.706)38 (43.678)46 (41.441)0.893
      Ethnicity0.404
      Hispanic/Latino6 (7.05)9 (10.34)17 (15.31)
      Not Hispanic/Latino74 (87.05)72 (82.75)85 (76.57)
      Not reported/not answered5 (5.88)6 (6.89)9 (8.10)
      Race0.28
      American Indian/Alaska Native0 (0.0)0 (0.0)0 (0.0)
      Asian6 (7.05)6 (6.89)4 (3.60)
      Black/African American1 (1.17)6 (6.89)7 (6.30)
      Native Hawaiian/Pacific Islander0 (0.0)0 (0.0)0 (0.0)
      Not reported/not answered6 (7.05)5 (5.74)13 (11.71)
      Other11 (12.94)12 (13.79)8 (7.20)
      White61 (71.76)58 (66.66)79 (71.17)
      Insurance provider0.098
      Commercial5 (5.88)2 (2.29)6 (5.40)
      Medi-Cal0 (0.0)4 (4.59)2 (1.80)
      Medicare63 (74.11)62 (71.26)92 (82.88)
      Other1 (1.17)0 (0.0)1 (0.90)
      Managed Care16 (18.82)19 (21.83)10 (9.01)
      Pre-procedure admission status0.229
      Same day admit60 (70.58)63 (72.41)91 (81.98)
      Inpatient11 (12.94)13 (14.94)7 (6.30)
      ED admit14 (16.47)11 (12.64)13 (11.71)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)97405 (35651)96320 (35537)100204 (37199)0.736
      Families in poverty (%)6 (4.6)7 (5.6)6 (5.8)0.205
      Unemployed (%)5 (1.8)5 (1.6)5 (1.9)0.684
      Outcomes
      Hospital length of stay (hours)123 (125.6)146 (182.8)125 (285.5)0.722
      ICU length of stay (hours)21 (65.8)57 (215.7)27 (106.7)0.192
      Data is present as mean (SD) or count (%) where appropriate.
      Table 2aAF Ablation in Latino/Hispanic vs Non-Latino/Hispanic Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Latino or Hispanic (n=7)Non-Latino or Hispanic (n=137)pLatino or Hispanic (n=11)Non-Latino or Hispanic (n=147)pLatino or Hispanic (n=27)Non-Latino or Hispanic (n=206)p
      Age (years)54.86 (19.18)64.05 (12.32)0.06360.64 (13.48)64.35 (10.85)0.28359.26 (15.9)67.19 (10.55)<0.005
      Sex (female)4 (57.14)48 (35.03)0.4334 (36.36)41 (27.89)0.79910 (37.03)79 (38.35)1
      Insurance provider0.0410.8110.174
      Commercial4 (57.14)66 (48.17)7 (63.63)66 (44.89)10 (37.03)73 (35.43)
      Medi-Cal1 (14.28)1 (0.73)0 (0.0)1 (0.68)1 (3.70)3 (1.45)
      Medicare2 (28.57)54 (39.41)3 (27.27)58 (39.45)8 (29.63)100 (48.54)
      Other0 (0.0)2 (1.46)0 (0.0)3 (2.04)1 (3.70)2 (0.97)
      Managed Care0 (0.0)14 (10.21)1 (9.09)19 (12.92)7 (25.92)28 (13.59)
      Pre-procedure admission status
      Same day admit7 (100.0)134 (97.81)111 (100.0)146 (99.32)127 (100.0)203 (98.54)1
      Inpatient0 (0.0)0 (0.0)10 (0.0)0 (0.0)10 (0.0)0 (0.0)1
      ED admit0 (0.0)3 (2.19)10 (0.0)1 (0.68)10 (0.0)3 (1.456)1
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)82741 (26085)101720 (34979)0.1684635 (23169)108841 (38388)0.04178832 (24683)102564 (32590)<0.005
      Families in poverty (%)8.2 (4.03)5.68 (3.44)0.0638.25 (6.08)5.37 (3.28)0.019.09 (5.03)5.88 (3.87)<0.005
      Unemployed (%)5.9 (1.12)5.97 (1.89)0.9196.09 (1.22)5.39 (1.46)0.1256.09 (1.35)5.63 (1.63)0.155
      Outcomes
      Hospital length of stay (hours)28.57 (3.6)32.23 (32.33)0.76620.18 (6.1)21.19 (10.41)0.75220.26 (7.17)22.46 (20.14)0.575
      ICU length of stay (hours)0.0 (0.0)2.25 (13.01)0.650.0 (0.0)0.49 (4.49)0.720.0 (0.0)0.81 (10.15)0.679
      Table 2bCABG in Latino/Hispanic vs Non-Latino/Hispanic Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Latino or Hispanic (n=27)Non-Latino or Hispanic (n=132)pLatino or Hispanic (n=35Non-Latino or Hispanic (n=86)pLatino or Hispanic (n=29)Non-Latino or Hispanic (n=111)p
      Age (years)64.15 (9.49)65.54 (9.53)0.49162.71 (12.22)65.59 (9.79)0.17658.76 (13.49)66.71 (10.61)<0.005
      Sex (female)7 (25.92)22 (16.66)0.38912 (34.28)16 (18.60)0.1066 (20.69)14 (12.613)0.419
      Insurance provider0.20.0250.236
      Commercial5 (18.51)37 (28.03)7 (20.0)37 (43.02)6 (20.69)30 (27.02)
      Medi-Cal6 (22.22)10 (7.576)7 (20.0)4 (4.65)6 (20.69)12 (10.81)
      Medicare13 (48.14)64 (48.48)16 (45.71)38 (44.18)15 (51.72)52 (46.84)
      Other1 (3.70)5 (3.78)1 (2.85)1 (1.16)1 (3.44)1 (0.90)
      Managed Care2 (7.40)16 (12.12)4 (11.42)6 (6.97)1 (3.44)16 (14.41)
      Pre-procedure admission status0.8160.7210.073
      Same day admit12 (44.444)56 (42.42)18 (51.42)39 (45.34)9 (31.03)58 (52.25)
      Inpatient7 (25.92)29 (21.97)7 (20.0)23 (26.74)10 (34.48)20 (18.01)
      ED admit8 (29.63)47 (35.60)10 (28.57)24 (27.90)10 (34.48)33 (29.73)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)70948 (20581)91615 (33868)<0.00571079 (21390)88846 (32101)<0.00573061 (23558)93175 (36990)0.006
      Families in poverty (%)11.02 (6.17)7.83 (5.86)0.01211.14 (6.44)7.8 (5.21)<0.00510.28 (5.21)7.8 (5.72)0.036
      Unemployed (%)6.57 (1.9)5.91 (1.77)0.0867.03 (1.91)6.03 (1.8)0.0076.32 (1.73)6.03 (1.71)0.418
      Outcomes
      Hospital length of stay (hours)442.3 (406.24)348.32 (320.4)0.188662.09 (2049.01)345.55 (373.79)0.169369.86 (307.53)309.12 (222.36)0.231
      ICU length of stay (hours)243.44 (318.5)212.32 (331.1)0.6551694.02 (9314.77)188.43 (422.15)0.135125.8 (83.48)121.14 (96.66)0.813
      Table 2cTAVR in Latino/Hispanic vs Non-Latino/Hispanic Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Latino or Hispanic (n=6)Non-Latino or Hispanic (n=74)pLatino or Hispanic (n=9)Non-Latino or Hispanic (n=72)pLatino or Hispanic (n=17)Non-Latino or Hispanic bn(n=85)p
      Age (years)84.83 (5.31)79.84 (7.9)0.13372.56 (9.3)78.35 (10.09)0.10676.29 (7.42)79.38 (8.44)0.164
      Sex (female)3 (50.0)32 (43.24)12 (22.22)33 (45.83)0.3229 (52.94)34 (40.0)0.473
      Insurance provider0.2250.6690.029
      Commercial0 (0.0)5 (6.75)0 (0.0)2 (2.77)0 (0.0)6 (7.05)
      Medi-Cal0 (0.0)0 (0.0)1 (11.11)3 (4.16)0 (0.0)2 (2.35)
      Medicare3 (50.0)56 (75.67)7 (77.77)51 (70.83)12 (70.58)71 (83.52)
      Other0 (0.0)1 (1.35)0 (0.0)0 (0.0)1 (5.88)0 (0.0)
      Managed Care3 (50.0)12 (16.21)1 (11.11)16 (22.22)4 (23.52)6 (7.05)
      Pre-procedure admission status0.5030.0340.478
      Same day admit5 (83.33)50 (67.56)5 (55.55)52 (72.22)14 (82.35)68 (80.0)
      Inpatient1 (16.66)10 (13.51)4 (44.44)9 (12.5)2 (11.76)5 (5.88)
      ED admit0 (0.0)14 (18.91)0 (0.0)11 (15.27)1 (5.88)12 (14.11)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)67273.0 (29740.45)98236.39 (35469.38)0.04168733.56 (20183.8)97353.89 (34778.94)0.01886004.82 (27623.69)103873.36 (38868.92)0.074
      Families in poverty (%)14.23 (9.87)5.74 (3.45)<0.00510.9 (7.7)7.44 (5.34)0.0858.82 (9.53)5.88 (4.54)0.053
      Unemployed (%)6.35 (1.31)5.89 (1.82)0.5466.8 (1.57)5.67 (1.61)0.0516.08 (2.21)5.91 (1.89)0.745
      Outcomes
      Hospital length of stay (hours)107.5 (81.61)120.81 (114.94)0.782192.67 (152.77)148.67 (191.76)0.5194.47 (102.85)139.16 (321.95)0.574
      ICU length of stay (hours)2.97 (7.27)15.86 (26.73)0.24546.21 (82.1)63.91 (235.12)0.82416.04 (39.44)32.0 (120.44)0.591
      Table 3aAF Ablation in Non-Hispanic White and Black/African American Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Non-Hispanic White (n=110)Black/Afr.

      American

      (n=7)
      pNon-Hispanic White (n=126)Black/Afr.

      American

      (n=3)
      pNon-Hispanic White (n=173)Black/Afr.

      American

      (n=4)
      p
      Age (years)64.76 (11.14)68.57 (11.63)0.58164.49 (10.76)63.0 (14.73)0.58167.66 (10.28)57.75 (10.31)0.581
      Sex (female)41 (37.27)2 (28.57)0.95337 (29.36)1 (33.3)168 (39.30)1 (25.0)0.951
      Insurance provider0.3670.861<0.005
      Commercial56 (50.90)2 (28.57)57 (45.23)1 (33.33)64 (36.99)1 (25.0)
      Medi-Cal1 (0.90)0 (0.0)1 (0.79)0 (0.0)1 (0.57)1 (25.0)
      Medicare44 (40.0)3 (42.85)50 (39.68)1 (33.33)83 (47.97)1 (25.0)
      Other1 (0.90)0 (0.0)3 (2.38)0 (0.0)1 (0.57)0 (0.0)
      Managed Care8 (7.27)2 (28.57)15 (11.90)1 (33.33)24 (13.87)1 (25.0)
      Pre-procedure admission status111
      Same day admit108 (98.18)7 (100.0)125 (99.20)3 (100.0)170 (98.26)4 (100.0)
      Inpatient0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)
      ED admit2 (1.81)0 (0.0)1 (0.79)0 (0.0)3 (1.73)0 (0.0)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)105192 (35544)77871 (15909)0.005108987 (36450)84636 (28757)0.005104752 (33560)80059 (19672)0.005
      Families in poverty (%)5.29 (3.31)7.0 (3.47)0.0215.19 (3.08)7.83 (4.59)0.0215.73 (3.73)8.5 (3.49)0.021
      Unemployed (%)5.93 (1.84)6.53 (1.79)0.0755.38 (1.48)5.4 (2.42)0.0755.61 (1.66)7.05 (1.4)0.075
      Outcomes
      Hospital length of stay (hours)32.79 (34.1)26.0 (9.38)0.73721.06 (10.64)22.33 (9.81)0.73721.4 (16.88)16.0 (5.72)0.737
      ICU length of stay (hours)2.8 (14.48)0.0 (0.0)0.6650.4 (4.47)0.0 (0.0)0.6650.13 (1.76)0.0 (0.0)0.665
      Table 3bCABG in Non-Hispanic White and Black/African American Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Non-Hispanic White (n=86)Black/Afr.

      American

      (n=11)
      pNon-Hispanic White (n=52)Black/Afr.

      American

      (n=5)
      pNon-Hispanic White (n=71)Black/Afr.

      American

      (n=7)
      p
      Age (years)67.14 (9.03)61.27 (12.17)0.00367.08 (7.82)62.6 (14.83)0.00366.38 (9.84)58.43 (11.15)0.003
      Sex (female)14 (16.27)1 (9.091)0.8599 (17.30)2 (40.0)0.52611 (15.49)0 (0.0)0.579
      Insurance provider0.1210.0480.996
      Commercial24 (27.90)4 (36.36)23 (44.23)0 (0.0)21 (29.57)2 (28.57)
      Medi-Cal2 (2.32)2 (18.18)1 (1.92)1 (20.0)8 (11.26)1 (14.28)
      Medicare45 (52.32)4 (36.36)25 (48.07)3 (60.0)31 (43.66)3 (42.85)
      Other4 (4.65)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)
      Managed Care11 (12.79)1 (9.09)3 (5.76)1 (20.0)11 (15.49)1 (14.28)
      Pre-procedure admission status0.8850.1520.994
      Same day admit38 (44.18)4 (36.36)25 (48.07)1 (20.0)42 (59.15)4 (57.14)
      Inpatient21 (24.41)3 (27.27)11 (21.15)3 (60.0)10 (14.08)1 (14.28)
      ED admit27 (31.39)4 (36.36)16 (30.76)1 (20.0)19 (26.76)2 (28.57)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)99316 (33917.72)76893 (32659.55)<0.00596741 (34341.0)57120 (5354.97)<0.00599547 (38651.74)69212 (20583.61)<0.005
      Families in poverty (%)6.31 (3.89)11.03 (6.39)<0.0056.51 (4.59)15.96 (4.36)<0.0056.88 (5.18)10.89 (6.86)<0.005
      Unemployed (%)5.92 (1.82)6.76 (1.74)<0.0055.78 (1.58)9.1 (0.53)<0.0055.91 (1.75)6.19 (1.69)<0.005
      Outcomes
      Hospital length of stay (hours)364.78 (333.79)267.82 (120.95)0.536343.73 (412.72)328.6 (83.39)0.536293.32 (245.7)304.71 (183.32)0.536
      ICU length of stay (hours)233.07 (368.95)109.41 (47.39)0.54223.89 (538.03)180.7 (109.09)0.54114.48 (99.35)170.76 (163.81)0.54
      Table 3cTAVR in Non-Hispanic White and Black/African American Patients Across COVID years
      Pre-COVIDCOVID Year 1COVID Year 2
      Non-Hispanic White (n=58)Black/Afr.

      American

      (n=1)
      pNon-Hispanic White (n=51)Black/Afr.

      American

      (n=6)
      pNon-Hispanic White (n=71)Black/Afr.

      American

      (n=7)
      p
      Age (years)79.34 (8.12)81.0 (NA)0.29579.96 (8.86)72.67 (7.09)0.29578.97 (8.15)80.0 (10.63)0.295
      Sex (female)23 (39.65)0 (0.0)121 (41.17)3 (50.0)129 (40.84)3 (42.85)1
      Insurance provider0.8540.3360.738
      Commercial5 (8.62)0 (0.0)1 (1.96)0 (0.0)5 (7.04)0 (0.0)
      Medi-Cal0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (2.81)0 (0.0)
      Medicare44 (75.86)1 (100.0)37 (72.54)6 (100.0)60 (84.50)7 (100.0)
      Other0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)
      Managed Care9 (15.51)0 (0.0)13 (25.4)0 (0.0)4 (5.63)0 (0.0)
      Pre-procedure admission status0.1090.0210.668
      Same day admit40 (68.96)0 (0.0)40 (78.43)2 (33.33)57 (80.28)5 (71.42)
      Inpatient8 (13.79)0 (0.0)6 (11.76)1 (16.66)4 (5.63)1 (14.28)
      ED admit10 (17.24)1 (100.0)5 (9.80)3 (50.0)10 (14.08)1 (14.28)
      Socioeconomic factors (ZCTA-based)
      Median income deciles (USD)100244 (35357.25)84505.0 (NA)<0.005104471 (31567.08)64990 (21515.43)<0.005109082 (38331.42)49679 (6508.79)<0.005
      Families in poverty (%)5.48 (3.57)5.4 (NA)<0.0055.93 (3.71)13.85 (7.52)<0.0055.07 (3.35)17.36 (6.51)<0.005
      Unemployed (%)5.97 (1.87)5.5 (NA)<0.0055.44 (1.57)6.8 (1.89)<0.0055.69 (1.74)9.3 (0.79)<0.005
      Outcomes
      Hospital length of stay (hours)123.69 (121.92)191.0 (NA)0.706121.75 (155.78)229.83 (123.04)0.706147.49 (349.69)90.71 (109.9)0.706
      ICU length of stay (hours)16.98 (26.78)0.0 (NA)0.65954.96 (229.05)40.43 (99.04)0.65935.19 (130.43)0.0 (0.0)0.659
      Table 4Comparison of population-adjusted incidence rates of cardiac procedures per 100,000 persons in Los Angeles County by race and ethnicity
      Pre-COVIDCOVID Year 1COVID Year 2
      Non-Hispanic WhiteBlack/Afr.AmericanDifferenceNon-Hispanic WhiteBlack/Afr.AmericanDifferenceNon-Hispanic WhiteBlack/Afr.AmericanDifference
      AF ablation4.420.793.635.060.344.726.960.456.51
      CABG3.461.242.222.090.571.522.850.792.06
      TAVR2.330.112.222.050.681.372.850.792.06
      Latino or HispanicNon-Latino or HispanicDifferenceLatino or HispanicNon-Latino or HispanicDifferenceLatino or HispanicNon-Latino or HispanicDifference
      AF ablation0.152.722.570.222.922.70.564.103.54
      CABG0.562.592.030.721.690.970.62.201.6
      TAVR0.121.451.330.191.431.240.351.681.33

      Funding

      None

      Presentation declarations

      This material was presented at Society of Cardiovascular Anesthesiologist's 44th Annual Meeting in May 2022 as a poster.

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      Declaration of interests

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.