Racial Disparities in Pulse Oximeter Device Inaccuracy and Estimated Clinical Impact on COVID-19 Treatment Course.

Arterial blood oxygen saturation measured by pulse oximetry (SpO2) may be differentially less accurate for people with darker skin pigmentation, which could potentially affect COVID-19 treatment course. We analyzed pulse oximeter accuracy and association with COVID-19 treatment outcomes using electronic health record (EHR) data from Sutter Health, a large, mixed-payer, integrated healthcare delivery system in northern California, United States (US). We analyzed two cohorts: (1) 43,753 concurrent arterial blood gas (ABG) oxygen saturation (SaO2)/SpO2 measurement pairs taken January 2020-February 2021 for Non-Hispanic white (NHW) or Non-Hispanic Black/African American (NHB) adults, and (2) 8,735 adults who went to the emergency department (ED) with COVID-19 July 2020-February 2021. Pulse oximetry systematically overestimated blood oxygenation by 1% more in NHB individuals than in NHW individuals. For people with COVID-19, this was associated with lower admission probability (-3.1 percentage-points), dexamethasone treatment (-3.1 percentage-points), and supplemental oxygen treatment (-4.5 percentage-points), as well as increased time-to-treatment: +37.2 minutes before dexamethasone initiation and +278.5 minutes before initiation of supplemental oxygen. These results call for additional investigation of pulse oximeters, and suggest that current guidelines for development, testing, and calibration of these devices should be revisited, investigated, and revised.

Racial and sociodemographic predictors of COVID-19 compared with influenza, appendicitis, and all-cause hospitalization: retrospective cohort analysis.

OBJECTIVE: To determine whether inequities in COVID-19 infection and hospitalization differ from those for common medical conditions: influenza, appendicitis, and all-cause hospitalization. DESIGN: Retrospective study based on electronic health records of three healthcare systems in San Francisco (university, public, and community) examining (1) racial/ethnic distribution in cases and hospitalization among patients with diagnosed COVID-19 (March-August 2020) and patients with diagnosed influenza, diagnosed appendicitis, or all-cause hospitalization (August 2017-March 2020), and (2) sociodemographic predictors of hospitalization among those with diagnosed COVID-19 and influenza. RESULTS: Patients 18 years or older with diagnosed COVID-19 (N = 3934), diagnosed influenza (N = 5932), diagnosed appendicitis (N = 1235), or all-cause hospitalization (N = 62,707) were included in the study. The age-adjusted racial/ethnic distribution of patients with diagnosed COVID-19 differed from that of patients with diagnosed influenza or appendicitis for all healthcare systems, as did hospitalization from these conditions compared to any cause. For example, in the public healthcare system, 68% of patients with diagnosed COVID-19 were Latine, compared with 43% of patients with diagnosed influenza, and 48% of patients with diagnosed appendicitis (p < 0.05). In multivariable logistic regressions, COVID-19 hospitalizations were associated with male sex, Asian and Pacific Islander race/ethnicity, Spanish language, and public insurance in the university healthcare system, and Latine race/ethnicity and obesity in the community healthcare system. Influenza hospitalizations were associated with Asian and Pacific Islander and other race/ethnicity in the university healthcare system, obesity in the community healthcare system, and Chinese language and public insurance in both the university and community healthcare systems. CONCLUSIONS: Racial/ethnic and sociodemographic inequities in diagnosed COVID-19 and hospitalization differed from those for diagnosed influenza and other medical conditions, with consistently higher odds among Latine and Spanish-speaking patients. This work highlights the need for disease-specific public health efforts in at-risk communities in addition to structural upstream interventions.

Disparities in COVID-19 testing and outcomes among Asian American and Pacific Islanders: an observational study in a large health care system.

BACKGROUND: The COVID-19 pandemic has disproportionately impacted racial and ethnic minorities in the United States, including Asian Americans, Native Hawaiians and Pacific Islanders (Asian Americans and NH/PIs). However, few studies have highlighted nor disaggregated these disparities by Asian Americans and NH/PIs ethnic subgroups. METHODS: This retrospective, cross-sectional observational study aimed to assess variation of Asian Americans and NH/PIs COVID-19 testing and outcomes compared to non-Hispanic Whites (NHW). The study utilized data from the electronic health records (EHR) and the COVID-19 Universal Registry for Vital Evaluations (CURVE) from all patients tested for SARS-CoV-2 (n = 556,690) at a large, health system in Northern and Central California between February 20, 2020 and March 31, 2021. Chi-square tests were used for testing differences in the severity of COVID-19 (hospitalization, ICU admission, death) and patient demographic and clinical characteristics across the Asian Americans and NH/PIs subgroups and NHW. Unadjusted and adjusted Odds Ratios (ORs) were estimated for measuring effect of race ethnicity on severity of COVID-19 using multivariable logistic regression. RESULTS: Of the entire tested population, 70,564/556,690 (12.7%) tested positive for SARS-CoV-2. SARS-CoV-2 positivity of Asian subgroups varied from 4% in the Chinese and Korean populations, to 11.2%, 13.5%, and 12.5% for Asian Indian, Filipino, and "other Asian" populations respectively. Pacific Islanders had the greatest subgroup test positivity at 20.1%. Among Asian Americans and NH/PIs patients with COVID-19 disease, Vietnamese (OR = 2.06, 95% CI = 1.30-3.25), "Other Asian" (OR = 2.13, 95% CI = 1.79-2.54), Filipino (OR = 1.78, 95% CI = 1.34-2.23), Japanese (OR = 1.78, 95% CI = 1.10-2.88), and Chinese (OR = 1.73, 95% CI = 1.34-2.23) subgroups had almost double the odds of hospitalization compared to NHW. Pacific Islander (OR = 1.58, 95% CI = 1.19-2.10) and mixed race subgroups (OR = 1.55, 95% CI = 1.10-2.20) had more than one and a half times odds of hospitalization compared to NHW. Adjusted odds of ICU admission or death among hospitalized patients by different Asian subgroups varied but were not statistically significant. CONCLUSIONS: Variation of COVID-19 testing and hospitalization by Asian subgroups was striking in our study. A focus on the Asian Americans and NH/PIs population with disaggregation of subgroups is crucial to understand nuances of health access, utilization, and outcomes among subgroups to create health equity for these underrepresented populations.

Evaluation of a social determinants of health screening questionnaire and workflow pilot within an adult ambulatory clinic.

BACKGROUND: There is increased recognition in clinical settings of the importance of documenting, understanding, and addressing patients' social determinants of health (SDOH) to improve health and address health inequities. This study evaluated a pilot of a standardized SDOH screening questionnaire and workflow in an ambulatory clinic within a large integrated health network in Northern California. METHODS: The pilot screened for SDOH needs using an 11-question Epic-compatible paper questionnaire assessing eight SDOH and health behavior domains: financial resource, transportation, stress, depression, intimate partner violence, social connections, physical activity, and alcohol consumption. Eligible patients for the pilot receiving a Medicare wellness, adult annual, or new patient visits during a five-week period (February-March, 2020), and a comparison group from the same time period in 2019 were identified. Sociodemographic data (age, sex, race/ethnicity, and payment type), visit type, length of visit, and responses to SDOH questions were extracted from electronic health records, and a staff experience survey was administered. The evaluation was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: Two-hundred eighty-nine patients were eligible for SDOH screening. Responsiveness by domain ranged from 55 to 67%, except for depression. Half of patients had at least one identified social need, the most common being stress (33%), physical activity (22%), alcohol (12%), and social connections (6%). Physical activity needs were identified more in females (81% vs. 19% in males, p < .01) and at new patient/transfer visits (48% vs. 13% at Medicare wellness and 38% at adult wellness visits, p < .05). Average length of visit was 39.8 min, which was 1.7 min longer than that in 2019. Visit lengths were longer among patients 65+ (43.4 min) and patients having public insurance (43.6 min). Most staff agreed that collecting SDOH data was relevant and accepted the SDOH questionnaire and workflow but highlighted opportunities for improvement in training and connecting patients to resources. CONCLUSION: Use of evidence-based SDOH screening questions and associated workflow was effective in gathering patient SDOH information and identifying social needs in an ambulatory setting. Future studies should use qualitative data to understand patient and staff experiences with collecting SDOH information in healthcare settings.

COVID-19 in pregnancy by race and ethnicity: Implications for development of a vaccination strategy.

OBJECTIVE: COVID-19 and associated morbidity and mortality has disproportionately affected minoritized populations. The epidemiology of spread of COVID-19 among pregnant women by race/ethnicity is not well described. Using data from a large healthcare system in California, we estimated prevalence and spread during pregnancy and recommend a vaccination approach based on minimizing adverse outcomes. METHODS: Patients delivering at Sutter Health are tested (molecular) for COVID-19. These results were combined with antibody test results, using samples drawn at delivery. For each racial/ethnic group, we estimated prevalence of COVID-19, using logistic regression to adjust for known sociodemographic and comorbid risk factors. Testing for immunoglobulin G and immunoglobulin M provided insight into timing of infections. RESULTS: Among 17,446 women delivering May-December, 460 (2.6%) tested positive (molecular). Hispanic women were at 2.6 times the odds of being actively infected as White women (odds ratio = 2.6, 95% confidence interval = 2.0-3.3). August and December were the highest risk periods for active infection (odds ratio = 3.5, 95% confidence interval = 2.1-5.7 and odds ratio = 6.1, 95% confidence interval = 3.8-9.9, compared with May, respectively). Among 4500 women delivering October-December, 425 (9.4%) had positive molecular or antibody tests, ranging from 4.0% (Asian) to 15.7% (Hispanic). Adjusting for covariables, compared with White patients, odds of infection was similar for Black and Asian patients, with Hispanic at 2.4 (1.8-3.3) times the odds. CONCLUSION: COVID-19 prevalence was higher among Hispanic women at delivery and in the last trimester than their White counterparts. Higher rates in Black patients are explained by other risk factors. Resources should be directed to increase vaccination rates among Hispanic women in early stages of pregnancy.

Persistence of Disparities Among Racially/Ethnically Marginalized Groups in the Coronavirus Disease 2019 Pandemic Regardless of Statewide Shelter-in-Place Policies: An Analysis From Northern California.

To measure disparities in coronavirus disease 2019 (COVID-19) hospitalization and intensive care unit (ICU) transfer among racially/ethnically marginalized groups before and after implementation of the California statewide shelter-in-place (SIP) policy, we conducted a retrospective cohort study within a health-care system in California. COVID-19 patients diagnosed from January 1, 2020, to August 31, 2020, were identified from electronic health records. We examined hospitalizations and ICU transfers by race/ethnicity and pandemic period using logistic regression. Among 16,520 people with COVID-19 (mean age = 46.6 (standard deviation, 18.4) years; 54.2% women), during the post-SIP period, patients were on average younger and a larger proportion were Hispanic. In adjusted models, odds of hospitalization were 20% lower post-SIP as compared with the SIP period, yet all non-White groups had higher odds (odds ratios = 1.6-2.1) than non-Hispanic White individuals, regardless of period. Among hospitalized patients, odds of ICU transfer were 33% lower post-SIP than during SIP. Hispanic and Asian patients had higher odds than non-Hispanics. Disparities in hospitalization persisted and ICU risk became more pronounced for Asian and Hispanic patients post-SIP. Policy-makers should consider ways to proactively address racial/ethnic inequities in risk when considering future population-level policy interventions for public health crises.

Public Protests and the Risk of Novel Coronavirus Disease Hospitalizations: A County-Level Analysis from California.

The objective of this study was to assess the relationship between public protests and county-level, novel coronavirus disease (COVID-19) hospitalization rates across California. Publicly available data were included in the analysis from 55 of 58 California state counties (29 March-14 October 2020). Mixed-effects negative binomial regression models were used to examine the relationship between daily county-level COVID-19 hospitalizations and two main exposure variables: any vs. no protests and 1 or >1 protest vs. no protests on a given county-day. COVID-19 hospitalizations were used as a proxy for viral transmission since such rates are less sensitive to temporal changes in testing access/availability. Models included covariates for daily county mobility, county-level characteristics, and time trends. Models also included a county-population offset and a two-week lag for the association between exposure and outcome. No significant associations were observed between protest exposures and COVID-19 hospitalization rates among the 55 counties. We did not find evidence to suggest that public protests were associated with COVID-19 hospitalization within California counties. These findings support the notion that protesting during a pandemic may be safe, ostensibly, so long as evidence-based precautionary measures are taken.

Measuring and Promoting SARS-CoV-2 Vaccine Equity: Development of a COVID-19 Vaccine Equity Index.

Purpose: The coronavirus pandemic has created the greatest public health crisis in a century, causing >500,000 deaths in the United States alone. Minoritized and socioeconomically disadvantaged groups have borne a disproportionate burden of severe illness, hospitalization, and death from COVID-19. Recently developed FDA-approved vaccines have been shown to significantly reduce severe COVID-19-related outcomes. Vaccination campaigns have the potential to advance health equity by prioritizing allocation to those at highest risk while striving for herd immunity. Large integrated health systems have been faced with the daunting task of meeting the rapidly evolving needs of diverse patient populations for the provision of population-based testing, treatment, education, and now vaccine distribution. We have designed a COVID-19 vaccine equity index (CVEI) to guide health system vaccination strategy. Methods: We considered proportion unvaccinated within a health care system. We then used real-time readily available electronic health record (EHR) COVID-19 testing positivity and proportion hospitalized to measure burden of illness by race/ethnicity. We used conditional probability and statistical theory to measure equity for unvaccinated individuals and to derive an index to highlight these inequities for specific subgroups. Results: We present an illustrative hypothetical example using simulated data for which we calculated the CVEI for non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, and Hispanic patients. In the example, non-Hispanic Black and Hispanic patients had inequitable outcomes. Conclusion: The index can be widely implemented to promote more equitable outcomes among racial/ethnic groups, reducing morbidity and mortality within the overall population as we pursue the collective goal of herd immunity through mass vaccination.

Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response.

Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored. We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.