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1.
Am J Epidemiol ; 2022 Sep 29.
Article in English | MEDLINE | ID: covidwho-2319613

ABSTRACT

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.

2.
Ethn Health ; : 1-17, 2023 Mar 12.
Article in English | MEDLINE | ID: covidwho-2277786

ABSTRACT

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.

3.
BMC Public Health ; 22(1): 1882, 2022 10 10.
Article in English | MEDLINE | ID: covidwho-2064765

ABSTRACT

BACKGROUND: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. There has been limited systematic evaluation of variation in U.S. local COVID-19-related policies. This study introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. METHODS: In January-March 2021, we collected an initial wave of cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health. We characterized the presence and comprehensiveness of policies using univariate analyses. We also examined the correlation of policies with one another using bivariate Spearman's correlations. Finally, we examined geographical variation in policies across and within states. RESULTS: There was substantial variation in the presence and comprehensiveness of county policies during January-March 2021. For containment and closure policies, the percent of counties with no restrictions ranged from 0% (for public events) to more than half for public transportation (67.8%), hair salons (52.6%), and religious gatherings (52.0%). For economic policies, 76.6% of counties had housing support, while 64.9% had utility relief. For public health policies, most were comprehensive, with 70.8% of counties having coordinated public information campaigns, and 66.7% requiring masks outside the home at all times. Correlations between containment and closure policies tended to be positive and moderate (i.e., coefficients 0.4-0.59). There was variation within and across states in the number and comprehensiveness of policies. CONCLUSIONS: This study introduces the UCCP Database, presenting granular data on local governments' responses to the COVID-19 pandemic. We documented substantial variation within and across states on a wide range of policies at a single point in time. By making these data publicly available, this study supports future research that can leverage this database to examine how policies contributed to and continue to influence pandemic-related health and socioeconomic outcomes and disparities. The UCCP database is available online and will include additional time points for 2020-2021 and additional counties nationwide.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Cross-Sectional Studies , Humans , Policy , Public Health , United States/epidemiology
4.
BMC Fam Pract ; 22(1): 256, 2021 12 24.
Article in English | MEDLINE | ID: covidwho-1630383

ABSTRACT

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.


Subject(s)
Health Inequities , Social Determinants of Health , Aged , Female , Humans , Male , Medicare , Referral and Consultation , Surveys and Questionnaires , United States , Workflow
5.
Am J Epidemiol ; 190(11): 2300-2313, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1493670

ABSTRACT

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.


Subject(s)
COVID-19/ethnology , Health Status Disparities , Hospitalization/statistics & numerical data , Intensive Care Units/statistics & numerical data , Racial Groups/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/therapy , COVID-19/virology , California/epidemiology , Comorbidity , Female , Health Policy , Humans , Male , Middle Aged , Pandemics , SARS-CoV-2 , Young Adult
6.
Nurse Lead ; 19(6): 571-575, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1428270

ABSTRACT

Devastating disparities in COVID-19 infection and outcomes among socioeconomically marginalized groups have resulted in a public outcry to address longstanding societal inequities that have contributed to the present situation. Nurse leaders have an opportunity and an obligation in this moment to lend their skills as scientists, innovators, advocates, and educators to lead in these efforts, advancing health equity for all.

7.
Int J Environ Res Public Health ; 18(18)2021 Sep 08.
Article in English | MEDLINE | ID: covidwho-1403607

ABSTRACT

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.


Subject(s)
COVID-19 , SARS-CoV-2 , California/epidemiology , Hospitalization , Humans , Pandemics
8.
Health Equity ; 5(1): 476-483, 2021.
Article in English | MEDLINE | ID: covidwho-1307502

ABSTRACT

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.

9.
Mayo Clin Proc Innov Qual Outcomes ; 5(1): 171-176, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1043886
10.
Non-conventional | WHO COVID | ID: covidwho-327330

ABSTRACT

As the coronavirus disease (COVID-19) pandemic spreads throughout the United States, evidence is mounting that racial and ethnic minorities and socioeconomically disadvantaged groups are bearing a disproportionate burden of illness and death. We conducted a retrospective cohort analysis of COVID-19 patients at Sutter Health, a large integrated health care system in northern California, to measure potential disparities. We used Sutter's integrated electronic health record to identify adults with suspected and confirmed COVID-19, and used multivariable logistic regression to assess risk of hospitalization, adjusting for known risk factors, such as race/ethnicity, sex, age, health, and socioeconomic variables. We analyzed 1,052 confirmed cases of COVID-19 from January 1-April 8, 2020. Among our findings, we observed that, compared with non-Hispanic white patients, African Americans had 2.7 times the odds of hospitalization, after adjusting for age, sex, comorbidities, and income. We explore possible explanations for this, including societal factors that either result in barriers to timely access to care or create circumstances in which patients view delaying care as the most sensible option. Our study provides real-world evidence that there are racial and ethnic disparities in the presentation of COVID-19. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

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