Understanding contributors to racial and ethnic inequities in COVID-19 incidence and mortality rates.

BACKGROUND: Racial inequities in Coronavirus 2019 (COVID-19) have been reported over the course of the pandemic, with Black, Hispanic/Latinx, and Native American individuals suffering higher case rates and more fatalities than their White counterparts. METHODS: We used a unique statewide dataset of confirmed COVID-19 cases across Missouri, linked with historical statewide hospital data. We examined differences by race and ethnicity in raw population-based case and mortality rates. We used patient-level regression analyses to calculate the odds of mortality based on race and ethnicity, controlling for comorbidities and other risk factors. RESULTS: As of September 10, 2020 there were 73,635 confirmed COVID-19 cases in the State of Missouri. Among the 64,526 case records (87.7% of all cases) that merged with prior demographic and health care utilization data, 12,946 (20.1%) were Non-Hispanic (NH) Black, 44,550 (69.0%) were NH White, 3,822 (5.9%) were NH Other/Unknown race, and 3,208 (5.0%) were Hispanic. Raw cumulative case rates for NH Black individuals were 1,713 per 100,000 population, compared with 2,095 for NH Other/Unknown, 903 for NH White, and 1,218 for Hispanic. Cumulative COVID-19-related death rates for NH Black individuals were 58.3 per 100,000 population, compared with 38.9 for NH Other/Unknown, 19.4 for NH White, and 14.8 for Hispanic. In a model that included insurance source, history of a social determinant billing code in the patient's claims, census block travel change, population density, Area Deprivation Index, and clinical comorbidities, NH Black race (OR 1.75, 1.51-2.04, p<0.001) and NH Other/Unknown race (OR 1.83, 1.36-2.46, p<0.001) remained strongly associated with mortality. CONCLUSIONS: In Missouri, COVID-19 case rates and mortality rates were markedly higher among NH Black and NH Other/Unknown race than among NH White residents, even after accounting for social and clinical risk, population density, and travel patterns during COVID-19.

Generating Subcounty Health Data Products: Methods and Recommendations From a Multistate Pilot Initiative.

BACKGROUND: County Health Rankings & Roadmaps (CHR&R) makes data on health determinants and outcomes available at the county level, but health data at subcounty levels are needed. Three pilot projects in California, Missouri, and New York explored multiple approaches for defining measures and producing data at subcounty geographic and demographic levels based on the CHR&R model. This article summarizes the collective technical and implementation considerations from the projects, challenges inherent in analyzing subcounty health data, and lessons learned to inform future subcounty health data projects. METHODS: The research teams used 12 data sources to produce 40 subcounty measures that replicate or approximate county-level measures from the CHR&R model. Using varying technical methods, the pilot projects followed similar stages: (1) conceptual development of data sources and measures; (2) analysis and presentation of small-area and subpopulation measures for public health, health care, and lay audiences; and (3) positioning the subcounty data initiatives for growth and sustainability. Unique technical considerations, such as degree of data suppression or data stability, arose during the project implementation. A compendium of technical resources, including samples of automated programs for analyzing and reporting subcounty data, was also developed. RESULTS: The teams summarized the common themes shared by all projects as well as unique technical considerations arising during the project implementation. Furthermore, technical challenges and implementation challenges involved in subcounty data analyses are discussed. Lessons learned and proposed recommendations for prospective analysts of subcounty data are provided on the basis of project experiences, successes, and challenges. CONCLUSIONS: This multistate pilot project offers 3 successful approaches for creating and disseminating subcounty data products to communities. Subcounty data often are more difficult to obtain than county-level data and require additional considerations such as estimate stability, validating accuracy, and protecting individual confidentiality. We encourage future projects to further refine techniques for addressing these critical considerations.

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program.

OBJECTIVE: Medicare's Hospital Readmissions Reduction Program (HRRP) does not account for social risk factors in risk adjustment, and this may lead the program to unfairly penalize safety-net hospitals. Our objective was to determine the impact of adjusting for social risk factors on HRRP penalties. STUDY DESIGN: Retrospective cohort study. DATA SOURCES/STUDY SETTING: Claims data for 2 952 605 fee-for-service Medicare beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia from December 2012 to November 2015. PRINCIPAL FINDINGS: Poverty, disability, housing instability, residence in a disadvantaged neighborhood, and hospital population from a disadvantaged neighborhood were associated with higher readmission rates. Under current program specifications, safety-net hospitals had higher readmission ratios (AMI, 1.020 vs 0.986 for the most affluent hospitals; pneumonia, 1.031 vs 0.984; and CHF, 1.037 vs 0.977). Adding social factors to risk adjustment cut these differences in half. Over half the safety-net hospitals saw their penalty decline; 4-7.5 percent went from having a penalty to having no penalty. These changes translated into a $17 million reduction in penalties to safety-net hospitals. CONCLUSIONS: Accounting for social risk can have a major financial impact on safety-net hospitals. Adjustment for these factors could reduce negative unintended consequences of the HRRP.

Measuring Subcounty Differences in Population Health Using Hospital and Census-Derived Data Sets: The Missouri ZIP Health Rankings Project.

CONTEXT: Measures of population health at the subcounty level are needed to identify areas for focused interventions and to support local health improvement activities. OBJECTIVE: To extend the County Health Rankings population health measurement model to the ZIP code level using widely available hospital and census-derived data sources. DESIGN: Retrospective administrative data study. SETTING: Missouri. POPULATION: Missouri FY 2012-2014 hospital inpatient, outpatient, and emergency department discharge encounters (N = 36 176 377) and 2015 Nielsen data. MAIN OUTCOME MEASURES: ZIP code-level health factors and health outcomes indices. RESULTS: Statistically significant measures of association were observed between the ZIP code-level population health indices and published County Health Rankings indices. Variation within counties was observed in both urban and rural areas. Substantial variation of the derived measures was observed at the ZIP code level with 20 (17.4%) Missouri counties having ZIP codes in both the top and bottom quintiles of health factors and health outcomes. Thirty of the 46 (65.2%) counties in the top 2 county quintiles had ZIP codes in the bottom 2 quintiles. CONCLUSIONS: This proof-of-concept analysis suggests that readily available hospital and census-derived data can be used to create measures of population health at the subcounty level. These widely available data sources could be used to identify areas of potential need within counties, engage community stakeholders, and target interventions.

Adding socioeconomic data to hospital readmissions calculations may produce more useful results.

To better understand the degree to which risk-standardized thirty-day readmission rates may be influenced by social factors, we compared results for hospitals in Missouri under two types of models. The first type of model is currently used by the Centers for Medicare and Medicaid Services for public reporting of condition-specific hospital readmission rates of Medicare patients. The second type of model is an "enriched" version of the first type of model with census tract-level socioeconomic data, such as poverty rate, educational attainment, and housing vacancy rate. We found that the inclusion of these factors had a pronounced effect on calculated hospital readmission rates for patients admitted with acute myocardial infarction, heart failure, and pneumonia. Specifically, the models including socioeconomic data narrowed the range of observed variation in readmission rates for the above conditions, in percentage points, from 6.5 to 1.8, 14.0 to 7.4, and 7.4 to 3.7, respectively. Interestingly, the average readmission rates for the three conditions did not change significantly between the two types of models. The results of our exploratory analysis suggest that further work to characterize and report the effects of socioeconomic factors on standardized readmission measures may assist efforts to improve care quality and deliver more equitable care on the part of hospitals, payers, and other stakeholders.

Ethical aspects of placebo groups in pain trials: lessons from psychiatry.

Placebo control use in clinical research is contentious in areas where effective treatments already exist. Determination of appropriate standards for placebo use is especially difficult in areas such as pain treatment and psychiatry, in which substantial placebo responses can occur. Debates are characterized by three common themes: (a) whether the state of existing treatments forbids placebo use, (b) whether the nature of the condition being treated and the level of additional risk permit placebo control use, and (c) whether methodological concerns are sufficient to justify placebo use. A review of these themes in the psychiatric research literature suggests possible strategies for analysis of this issue in the area of pain research.

Geographic and racial aspects of herpes zoster.

Geographic and racial factors have been reported in studies of the epidemiology of varicella and herpes zoster. To clarify further these relationships, data from five multicenter clinical trials of the antiviral agent famciclovir were examined (total N = 2074). Non-Caucasian racial group and tropical region were each significantly associated with younger age at zoster onset. In analyses of the non-Caucasian subgroups, Black and Asian patients did not significantly differ in age or sex; however, Black and Asian patients from tropical regions had significantly younger mean ages at onset and greater rash duration at enrollment than those from temperate regions. Controlling for sex and rash duration at enrollment, both tropical region and non-Caucasian racial group were found to be independently associated with a younger age at zoster onset. These results suggest that racial group and geographic region may be independent factors associated with age at onset in patients with herpes zoster.

Rash severity in herpes zoster: correlates and relationship to postherpetic neuralgia.

Baseline and follow-up data from 4 samples of immunocompetent patients with herpes zoster who participated in clinical trials of the antiviral agent famciclovir were examined (N = 1778). In both univariate and multivariate analyses, severe rash (ie, >50 lesions, defined as papules, vesicles, or crusted vesicles) was significantly associated with older age, male sex, severe pain, primary involvement of nontrigeminal dermatomes, and a greater number of affected dermatomes. In addition, severe rash predicted the presence of pain 3 months later. The results indicate that severe rash is more common in patients with herpes zoster who are older and who have more severe acute pain and confirm that severe rash is a risk factor for prolonged pain.

Acute pain in herpes zoster: the famciclovir database project.

The results of a considerable number of recent prospective studies have demonstrated that greater acute pain severity in herpes zoster patients is associated with a significantly greater risk of developing postherpetic neuralgia (PHN). Only a few studies have examined the relationships between acute pain severity and demographic characteristics and clinical features of patients with herpes zoster, however, and the results of these studies have been inconsistent. To clarify these relationships, data from 1778 herpes zoster patients studied within 72 h of rash onset in four clinical trials of the antiviral agent famciclovir were examined. Univariate and multivariate analyses indicated that greater acute pain severity was significantly associated with greater age, female sex, greater rash severity, the presence of a prodrome, and primary involvement of non-trigeminal dermatomes. These results demonstrate that three of the established risk factors for PHN - older age, greater rash severity, and the presence of a prodrome - are also associated with more severe acute pain assessed soon after rash onset in patients with herpes zoster. The results of this study are consistent with the recommendation that herpes zoster patients who are older, who have had a prodrome, or who have severe rash or severe acute pain should be targeted for interventions designed to prevent PHN.