Explaining COVID-19 related mortality disparities in American Indians and Alaska Natives.

American Indian and Alaska Native (AI/AN) individuals are more likely to die with COVID-19 than other groups, but there is limited empirical evidence to explain the cause of this inequity. The objective of this study was to determine whether medical comorbidities, area socioeconomic deprivation, or access to treatment can explain the greater COVID-19 related mortality among AI/AN individuals. The design was a retrospective cohort study of harmonized electronic health record data of all inpatients with COVID-19 from 21 United States health systems from February 2020 through January 2022. The mortality of AI/AN inpatients was compared to all Non-Hispanic White (NHW) inpatients and to a matched subsample of NHW inpatients. AI/AN inpatients were more likely to die during their hospitalization (13.2% versus 7.1%; odds ratio [OR] = 1.98, 95% confidence interval [CI] = 1.48, 2.65) than their matched NHW counterparts. After adjusting for comorbidities, area social deprivation, and access to treatment, the association between ethnicity and mortality was substantially reduced (OR 1.59, 95% CI 1.15, 2.22). The significant residual relation between AI/AN versus NHW status and mortality indicate that there are other important unmeasured factors that contribute to this inequity. This will be an important direction for future research.

Racial and Educational Disparities in Cumulative Exposure to Hardships of the 2008 Great Recession and Inflammation.

OBJECTIVE: This cross-sectional analysis examined self-reported economic hardships of the 2008 Great Recession, race/ethnicity, educational attainment, and psychological well-being (PWB) as predictors of systemic inflammatory physiology at midlife. We also tested for differential vulnerability in the relationship between recession hardship and inflammatory physiology by race/ethnicity, education, and PWB. METHODS: Adults from the Midlife in the United States Refresher sample completed a survey and biomedical assessments after the recession ( n = 592 non-Hispanic White respondents, n = 158 Black/African American respondents, n = 108 respondents with other race/ethnicity). Cumulative recession hardship was the sum of financial, housing, and employment-related events. Outcomes included circulating levels of interleukin 6 and C-reactive protein. General linear regression models tested main effects interactions between primary predictor variables. RESULTS: Educational attainment was inversely associated with recession hardships ( b = -0.18, 95% confidence interval = -0.26 to -0.11, p < .001). Black/African American respondents reported more recession hardships than White respondents ( b = 1.17, 95% confidence interval = 0.67 to 1.68, p < .001). More recession hardships predicted higher levels of interleukin 6 ( b = 0.06, p < .001) and C-reactive protein ( b = 0.04, p = .004). Analyses did not support race/ethnicity, education, and PWB as moderators of the association between recession hardship and inflammatory markers. CONCLUSIONS: Race/ethnicity and education independently predicted disparities in cumulative recession hardship exposure. Recession hardship predicted higher blood levels of inflammatory proteins associated with long-term health. The lack of findings for differential vulnerability in the relationship between recession hardship and inflammatory markers by race/ethnicity, education, or PWB was possibly due to the limited sample size.

Factors associated with 60-day readmission among inpatients with COVID-19 at 21 United States health systems.

Identifying patients at risk for readmission after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could facilitate care planning and prevention. This retrospective cohort study of 60-day readmission included 105 543 COVID-19 patients at 21 US healthcare systems who were discharged alive between February 2020 and November 2021. Generalized linear mixed regression analyses tested predictors of 60-day readmission and severity. The all-cause readmission rate was 15% (95% confidence interval [CI] = 10%-21%), with 22% (95% CI = 18%-26%) of readmitted patients needing intensive care, and 6% (95% CI = 05%-07%) dying. Factors associated with readmission included male sex, government insurance, positive smoking history, co-morbidity burden, longer index admissions, and diagnoses at index admission (e.g., cancer, chronic kidney disease, and liver disease). Death and intensive care rates at readmission declined postvaccine availability. Receiving at least two COVID-19 vaccine doses, which were more common among older patients and those with comorbid conditions, was not independently associated with readmission but predicted a reduced risk of death at readmission. This retrospective cohort study identified factors associated with all-cause readmission for patients re-admitted to the same health system after hospitalization with SARS-CoV-2 infection. Patients who are male, who smoke, who have a higher comorbidity burden, and have government insurance may benefit from additional postacute care planning.

Smoking Status, Nicotine Medication, Vaccination, and COVID-19 Hospital Outcomes: Findings from the COVID EHR Cohort at the University of Wisconsin (CEC-UW) Study.

INTRODUCTION: Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown. METHODS: Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission. RESULTS: Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97). CONCLUSIONS: Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers. IMPLICATIONS: Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin.

BACKGROUND: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics. METHODS: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined. RESULTS: 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90). CONCLUSIONS: Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types. IMPACT: This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.

Electronic health record closed-loop referral ("eReferral") to a state tobacco quitline: a retrospective case study of primary care implementation challenges and adaptations.

BACKGROUND: Health system change can increase the reach of evidence-based smoking cessation treatments. Proactive electronic health record (EHR)-enabled, closed-loop referral ("eReferral") to state tobacco quitlines increases the rates at which patients who smoke accept cessation treatment. Implementing such system change poses many challenges, however, and adaptations to system contexts are often required, but are understudied. This retrospective case study identified adaptations to eReferral EHR tools and implementation strategies in two healthcare systems. METHODS: In a large clustered randomized controlled trial (C-RCT; NCT02735382) conducted in 2016-2017, 11 primary care clinics in two healthcare systems implemented quitline eReferral, starting with 1 pilot clinic per system followed by 2 phases of implementation (an experimental phase in 5-6 test clinics per system and then a system-wide dissemination phase in both systems). Adaptations were informed by stakeholder input from live trainings, follow-up calls and meetings in the first month after eReferral launch, emails, direct observation by researchers, and clinic staff survey responses. Retrospective, descriptive analysis characterized implementation strategy modifications and adaptations using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS). A pre- and post-implementation survey assessed staff ratings of eReferral acceptability and implementation barriers and facilitators. FINDINGS: Major modifications to closed-loop eReferral implementation strategies included aligning the eReferral initiative with other high-priority health system objectives, modifying eReferral user interfaces and training in their use, modifying eReferral workflows and associated training, and maintaining and enhancing interoperability and clinician feedback functions. The two health systems both used Epic EHRs but used different approaches to interfacing with the quitline vendor and integrating eReferral into clinician workflows. Both health systems engaged in iterative refinement of the EHR alert prompting eReferral, the eReferral order, trainings, and workflows. Staff survey comments suggested moderate acceptability of eReferral processes and identified possible targets for future modifications in eReferral, including reducing clinician burden related to EHR documentation and addressing clinicians' negative beliefs about patient receptivity to cessation treatment. CONCLUSIONS: System-wide implementation of tobacco quitline eReferral in primary care outpatient clinics is feasible but requires extensive coordination across stakeholders, tailoring to local health system EHR configurations, and sensitivity to system- and clinic-specific workflows. TRIAL REGISTRATION: www. CLINICALTRIALS: gov, NCT02735382 . Registered on 12 August 2016.

The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems.

MAIN OBJECTIVE: There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic. STUDY DESIGN AND METHODS: University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission. RESULTS AND SIGNIFICANCE: The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months. CONCLUSIONS: Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).

Scientific imperatives vis-à-vis growing inequality in America.

A landmark article published in the American Psychologist (Adler et al., 1994) encouraged psychologists to engage in research on socioeconomic inequality and health. Numerous contributions followed to fill in psychosocial and behavioral pathways. Specifically, we review advances on health inequalities research from a large public-use study (Midlife in the United States [MIDUS]). The Great Recession of 2007 to 2009 and its lingering effects are then reviewed to underscore widening inequality in access to education, employment, and income. Two MIDUS national samples of same-aged adults recruited 2 decades apart are then compared to assess historical changes in socioeconomic, physical health, and well-being profiles from the 1990s to postrecession. Despite historical gains in educational attainment over time, we show that indicators of socioeconomic status, health, and well-being are more compromised in the postrecession sample relative to the 1990s sample. Building on these preliminary findings, we elaborate opportunities for further inquiry by the scientific community to examine whether widening socioeconomic inequalities exacerbated by the Great Recession translate to widening health inequalities. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Hardships of the Great Recession and health: Understanding varieties of vulnerability.

The Great Recession of 2007-2009 is regarded as the most severe economic downturn since World War II. This study examined relationships between reported recession hardships and physical health in a national survey of American adults (N = 1275). Furthermore, education and psychological resources (perceived control, purpose in life, and conscientiousness) were tested as moderators of the health impacts of the recession. A greater number of hardships predicted poorer health, especially among the less educated. Psychological resources interacted with education and hardships to predict health outcomes. Although typically viewed as protective factors, such resources became vulnerabilities among educationally disadvantaged adults experiencing greater recession hardships.

Comparing Visible and Invisible Social Support: Non-evaluative Support Buffers Cardiovascular Responses to Stress.

Previous research suggests that in contrast to invisible social support, visible social support produces exaggerated negative emotional responses. Drawing on work by Bolger and colleagues, this study disentangled social support visibility from negative social evaluation in an examination of the effects of social support on negative emotions and cardiovascular responses. As part of an anticipatory speech task, 73 female participants were randomly assigned to receive no social support, invisible social support, non-confounded visible social support or visible social support as delivered in a 2007 study by Bolger and Amarel. Twelve readings, each for systolic blood pressure, diastolic blood pressure and heart rate were taken at 5-min intervals throughout the periods of baseline, reactivity and recovery. Cardiovascular outcomes were tested by incorporating a series of theoretically driven planned contrasts into tests of stress reactivity conducted through piecewise growth curve modelling. Linear and quadratic trends established cardiovascular reactivity to the task. Further, in comparison to the control and replication conditions, the non-confounded visible and invisible social support conditions attenuated cardiovascular reactivity over time. Pre- and post-speech negative emotional responses were not affected by the social support manipulations. These results suggest that appropriately delivered visible social support may be as beneficial as invisible social support.