Differences in COVID-19 Hospitalizations by Self-Reported Race and Ethnicity in a Hospital in Honolulu, Hawaii

Abstract

Introduction The true extent of racial and ethnic disparities in COVID-19 hospitalizations may be hidden by misclassification of race and ethnicity. This study aimed to quantify this inaccuracy in a hospital’s electronic medical record (EMR) against the gold standard of self-identification and then project data onto state-level COVID-19 hospitalizations by self-identified race and ethnicity. Methods To identify misclassification of race and ethnicity in the EMRs of a hospital in Honolulu, Hawaii, research and quality improvement staff members surveyed all available patients (N = 847) in 5 cohorts in 2007, 2008, 2010, 2013, and 2020 at randomly selected hospital and ambulatory units. The survey asked patients to self-identify up to 12 races and ethnicities. We compared these data with data from EMRs. We then estimated the number of COVID-19 hospitalizations by projecting racial misclassifications onto publicly available data. We determined significant differences via simulation-constructed medians and 95% CIs. Results EMR–based and self-identified race and ethnicity were the same in 86.5% of the sample. Native Hawaiians (79.2%) were significantly less likely than non–Native Hawaiians (89.4%) to be correctly classified on initial analysis; this difference was driven by Native Hawaiians being more likely than non–Native Hawaiians to be multiracial (93.4% vs 30.3%). When restricted to multiracial patients only, we found no significant difference in accuracy ( P = .32). The number of COVID-19–related hospitalizations was 8.7% higher among Native Hawaiians and 3.9% higher among Pacific Islanders when we projected self-identified race and ethnicity rather than using EMR data. Conclusion Using self-identified rather than hospital EMR data on race and ethnicity may uncover further disparities in COVID-19 hospitalizations.

COVID-19 Hospitalization in Hawaiʻi and Patterns of Insurance Coverage, Race and Ethnicity, and Vaccination

“…Limitations of this study include the inherent variability in collecting self-identified race and ethnicity data for entry into the EHR, with a 2022 study 6 suggesting that this approach underestimates identification of Native Hawaiian and Pacific Islander patients in COVID-19 hospitalizations. 6 Furthermore, the vaccine data are incomplete, given that patients may have received vaccines at other sites not captured in the EHR. In addition, too few uninsured patients were admitted to this hospital to evaluate for associations with race and ethnicity or vaccine status in our analysis.…”

“… 3 , 4 , 5 However, while disaggregation of data can be challenging, several publications early in the COVID-19 pandemic suggested markedly disparate outcomes that merit further exploration. 4 , 6 , 7 …”

Maintaining Our Commitment to Building Scientific Publishing Capacity of Students: PCD’s 2022 Student Paper Contest Winners and Release of 2023 Call for Papers

“…Seto and coauthors of the article “Differences in COVID-19 Hospitalizations by Self-Reported Race and Ethnicity in a Hospital in Honolulu, Hawaii” were selected as winners in the doctoral category ( 7 ). Pointing out that COVID-19 has exacted a tremendous toll on racial and ethnic groups in the US, they sought to identify the extent to which race and ethnicity were misclassified in COVID-19 hospitalizations.…”

“…Over the years, PCD has refined the purpose of the student research publication opportunity to include these 5 primary goals (3): Sixteen student research papers were submitted for the contest in 2022, and all submissions underwent the same peer-review process as any other manuscript submitted to the journal for consideration. Eight of the 16 papers were successful in making it through a rigorous review process before being accepted for publication (4)(5)(6)(7)(8)(9)(10)(11). Student research papers addressed a range of topics: COVID-19 and various aspects of health, food insecurities among caregivers in southern states, the relationship between physical activity and depression among high school students, perceptions of neighborhood development on active living among community residents, use of a cancer index as a predictor of common cancers, and spatial analysis of breast cancer mortality rates in rural states.…”

“…Mortality Rates in a Rural State," is the winner in the master's degree category (6). This article reports findings from a study in South Dakota that assessed what sociodemographic factors contribute to mortality rates and, using spatial analysis, explored how counties' observed age-adjusted mortality rates compared with expected rates.…”