Understanding racial/ethnic disparities in COVID-19 mortality using a novel metric: COVID excess mortality percentage.

Prior research on racial/ethnic disparities in COVID-19 mortality has often not considered to what extent they reflect COVID-19-specific factors, versus preexisting health differences. This study examines how racial/ethnic disparities in COVID-19 mortality vary with age, sex, and time period over April-December 2020 in the United States, using mortality from other natural causes as a proxy for underlying health. We study a novel measure, the COVID excess mortality percentage (CEMP), defined as the COVID-19 mortality rate divided by the non-COVID natural mortality rate, converted to a percentage, where the CEMP denominator controls (albeit imperfectly) for differences in population health. Disparities measured using CEMP deviate substantially from those in prior research. In particular, we find very high disparities (up to 12:1) in CEMP rates for Hispanics versus Whites, particularly for nonelderly men. Asians also have elevated CEMP rates versus Whites, which were obscured in prior work by lower overall Asian mortality. Native Americans and Blacks have significant disparities compared with White populations, but CEMP ratios to Whites are lower than ratios reported in other work. This is because the higher COVID-19 mortality for Blacks and Native Americans comes partly from higher general mortality risk and partly from COVID-specific risk.

How Mixed-Methods Research Can Improve the Policy Relevance of Impact Evaluations.

This paper describes how mixed methods can improve the value and policy relevance of impact evaluations, paying particular attention to how mixed methods can be used to address external validity and generalization issues. We briefly review the literature on the rationales for using mixed methods; provide documentation of the extent to which mixed methods have been used in impact evaluations in recent years; describe how we developed a list of recent impact evaluations using mixed methods and the process used to conduct full-text reviews of these articles; summarize the findings from our analysis of the articles; discuss three exemplars of using mixed methods in impact evaluations; and discuss how mixed methods have been used for studying and improving external validity and potential improvements that could be made in this area. We find that mixed methods are rarely used in impact evaluations, and we believe that increased use of mixed methods would be useful because they can reinforce findings from the quantitative analysis (triangulation), and they can also help us understand the mechanism by which programs have their impacts and the reasons why programs fail.

A more complete measure of vertical integration between physicians and hospitals.

OBJECTIVE: To develop an accurate and reproducible measure of vertical integration between physicians and hospitals (defined as hospital or health system employment of physicians), which can be used to assess the impact of integration on healthcare quality and spending. DATA SOURCES AND STUDY SETTING: We use multiple data sources including from the Internal Revenue Service, the Centers for Medicare and Medicaid Services, and others to determine the Tax Identification Numbers (TINs) that hospitals and physicians use to bill Medicare for services, and link physician billing TINs to hospital-related TINs. STUDY DESIGN: We developed a new measure of vertical integration, based on the TINs that hospitals and physicians use to bill Medicare, using a broad set of sources for hospital-related TINs. We considered physicians as hospital-employed if they bill Medicare primarily or exclusively using hospital-related TINs. We assessed integration status for all physicians who billed Medicare from 1999 to 2019. We compared this measure with others used in the existing literature. We conducted a simulation study which highlights the importance of accurately identifying integrated physicians when study the effects of integration. DATA COLLECTION/EXTRACTION METHODS: We extracted physician and hospital-related TINs from multiple sources, emphasizing specificity (a small proportion of nonintegrated physicians identified as integrated). PRINCIPAL FINDINGS: We identified 12,269 hospital-related TINs, used for billing by 546,775 physicians. We estimate that the percentage of integrated physicians rose from 19% in 1999 to 43% in 2019. Our approach identifies many additional physician practices as integrated; a simpler TIN measure, comparable with prior work, identifies only 30% (3877) of the TINs we identify. A service location measure, used in prior work, has both many false positives and false negatives. CONCLUSION: We developed a new measure of hospital-physician integration. This measure is reproducible and identifies many additional physician practices as integrated.

Evidence on COVID-19 Mortality and Disparities Using a Novel Measure, COVID excess mortality percentage: Evidence from Indiana, Wisconsin, and Illinois.

COVID-19 mortality rates increase rapidly with age, are higher among men than women, and vary across racial/ethnic groups, but this is also true for other natural causes of death. Prior research on COVID-19 mortality rates and racial/ethnic disparities in those rates has not considered to what extent disparities reflect COVID-19-specific factors, versus preexisting health differences. This study examines both questions. We study the COVID-19-related increase in mortality risk and racial/ethnic disparities in COVID-19 mortality, and how both vary with age, gender, and time period. We use a novel measure validated in prior work, the COVID Excess Mortality Percentage (CEMP), defined as the COVID-19 mortality rate (Covid-MR), divided by the non-COVID natural mortality rate during the same time period (non-Covid NMR), converted to a percentage. The CEMP denominator uses Non-COVID NMR to adjust COVID-19 mortality risk for underlying population health. The CEMP measure generates insights which differ from those using two common measures-the COVID-MR and the all-cause excess mortality rate. By studying both CEMP and COVID-MRMR, we can separate the effects of background health from Covid-specific factors affecting COVID-19 mortality. We study how CEMP and COVID-MR vary by age, gender, race/ethnicity, and time period, using data on all adult decedents from natural causes in Indiana and Wisconsin over April 2020-June 2022 and Illinois over April 2020-December 2021. CEMP levels for racial and ethnic minority groups can be very high relative to White levels, especially for Hispanics in 2020 and the first-half of 2021. For example, during 2020, CEMP for Hispanics aged 18-59 was 68.9% versus 7.2% for non-Hispanic Whites; a ratio of 9.57:1. CEMP disparities are substantial but less extreme for other demographic groups. Disparities were generally lower after age 60 and declined over our sample period. Differences in socio-economic status and education explain only a small part of these disparities.

Understanding COVID-19 Vaccine Effectiveness against Death Using a Novel Measure: COVID Excess Mortality Percentage.

COVID-19 vaccines have saved millions of lives; however, understanding the long-term effectiveness of these vaccines is imperative to developing recommendations for booster doses and other precautions. Comparisons of mortality rates between more and less vaccinated groups may be misleading due to selection bias, as these groups may differ in underlying health status. We studied all adult deaths during the period of 1 April 2021-30 June 2022 in Milwaukee County, Wisconsin, linked to vaccination records, and we used mortality from other natural causes to proxy for underlying health. We report relative COVID-19 mortality risk (RMR) for those vaccinated with two and three doses versus the unvaccinated, using a novel outcome measure that controls for selection effects. This measure, COVID Excess Mortality Percentage (CEMP), uses the non-COVID natural mortality rate (Non-COVID-NMR) as a measure of population risk of COVID mortality without vaccination. We validate this measure during the pre-vaccine period (Pearson correlation coefficient = 0.97) and demonstrate that selection effects are large, with non-COVID-NMRs for two-dose vaccinees often less than half those for the unvaccinated, and non-COVID NMRs often still lower for three-dose (booster) recipients. Progressive waning of two-dose effectiveness is observed, with an RMR of 10.6% for two-dose vaccinees aged 60+ versus the unvaccinated during April-June 2021, rising steadily to 36.2% during the Omicron period (January-June, 2022). A booster dose reduced RMR to 9.5% and 10.8% for ages 60+ during the two periods when boosters were available (October-December, 2021; January-June, 2022). Boosters thus provide important additional protection against mortality.

Selection Effects and COVID-19 Mortality Risk after Pfizer vs. Moderna Vaccination: Evidence from Linked Mortality and Vaccination Records.

Prior research generally finds that the Pfizer-BioNTech (BNT162b2) and Moderna (mRNA1273) COVID-19 vaccines provide similar protection against mortality, sometimes with a Moderna advantage due to slower waning. However, most comparisons do not address selection effects for those who are vaccinated and with which vaccine. We report evidence on large selection effects, and use a novel method to control for these effects. Instead of directly studying COVID-19 mortality, we study the COVID-19 excess mortality percentage (CEMP), defined as the COVID-19 deaths divided by non-COVID-19 natural deaths for the same population, converted to a percentage. The CEMP measure uses non-COVID-19 natural deaths to proxy for population health and control for selection effects. We report the relative mortality risk (RMR) for each vaccine relative to the unvaccinated population and to the other vaccine, using linked mortality and vaccination records for all adults in Milwaukee County, Wisconsin, from 1 April 2021 through 30 June 2022. For two-dose vaccinees aged 60+, RMRs for Pfizer vaccinees were consistently over twice those for Moderna, and averaged 248% of Moderna (95% CI = 175%,353%). In the Omicron period, Pfizer RMR was 57% versus 23% for Moderna. Both vaccines demonstrated waning of two-dose effectiveness over time, especially for ages 60+. For booster recipients, the Pfizer-Moderna gap is much smaller and statistically insignificant. A possible explanation for the Moderna advantage for older persons is the higher Moderna dose of 100 µg, versus 30 µg for Pfizer. Younger persons (aged 18-59) were well-protected against death by two doses of either vaccine, and highly protected by three doses (no deaths among over 100,000 vaccinees). These results support the importance of a booster dose for ages 60+, especially for Pfizer recipients. They suggest, but do not prove, that a larger vaccine dose may be appropriate for older persons than for younger persons.

The Effect of the COVID-19 Pandemic on the Elderly: Population Fatality Rates, COVID Mortality Percentage, and Life Expectancy Loss.

The COVID-19 pandemic has disproportionately affected the elderly. This Article provides a detailed analysis of those effects, drawing primarily on individual-level mortality data covering almost three million persons aged 65+ in three Midwest states (Indiana, Illinois, and Wisconsin). We report sometimes surprising findings on population fatality rates ("PFR"), the ratio of COVID to non-COVID deaths, reported as a percentage, which we call the "Covid Mortality Percentage," and mean life expectancy loss ("LEL"). We examine how these COVID-19 outcomes vary with age, gender, race/ethnicity, socio-economic status, and time period during the pandemic. For all persons in the three Midwest areas, COVID PFR through year-end 2021 was 0.22%, mean years of life lost ("YLL") was 13.0 years, the COVID Mortality Percentage was 12.4%, and LEL was 0.028 years (eleven days). In contrast, for the elderly, PFR was 1.03%; YLL was 8.8 years, the COVID Mortality Percentage was 13.2%, and LEL was 0.091 years (thirty-four days). Controlling for gender, PFR and LEL were substantially higher for Blacks and Hispanics than for Whites at all ages. Racial/ethnic disparities for the elderly were large early in the pandemic but diminished later. Although COVID-19 mortality was much higher for the elderly, the COVID Mortality Percentage over the full pandemic period was only modestly higher for the elderly, at 13.2%, than for non-elderly adults aged 25-64, at 11.1%. Indeed, in 2021, this ratio was lower for the elderly than for the middle-aged, reflecting higher elderly vaccination rates.

Understanding COVID-19 Vaccine Effectiveness Against Death Using a Novel Measure: COVID Excess Mortality Percentage.

COVID-19 vaccines have saved millions of lives and prevented countless adverse patient disease outcomes. Understanding the long-term effectiveness of these vaccines is imperative to developing recommendations for precautions and booster doses. Comparisons between more and less vaccinated groups may be misleading due to selection bias, as these groups may differ in underlying health status and thus risk of adverse COVID-19 outcomes. We study all adult deaths over April 1, 2021-June 30, 2022 in Milwaukee County, Wisconsin, linked to vaccination records, use mortality from other natural causes to proxy for underlying health, and report relative COVID-19 mortality risk (RMR) for vaccinees versus the unvaccinated, using a novel outcome measure that controls for selection effects. This measure, COVID Excess Mortality Percentage (CEMP) uses the non-COVID natural mortality rate (Non-Covid-NMR) as a measure of population risk of COVID mortality without vaccination. We validate this measure during the pre-vaccine period (r = 0.97) and demonstrate that selection effects are large, with Non-Covid-NMRs for two-dose vaccinees less than half those for the unvaccinated, and Non-COVID NMRs still lower for three dose (booster) recipients. Progressive waning of two-dose effectiveness is observed, with relative mortality risk (RMR) for two-dose vaccinees aged 60 + versus the unvaccinated of 11% during April-June 2021, rising steadily to 36% during the Omicron period (January-June, 2022). Notably, a booster dose reduced RMR to 10-11% for ages 60+. Boosters thus provide important additional protection against mortality.

Understanding Why Nurse Practitioner (NP) and Physician Assistant (PA) Productivity Varies Across Community Health Centers (CHCs): A Comparative Qualitative Analysis.

This study asks how much and why the productivity of advanced practice clinicians (APCs; nurse practitioners and physician assistants) varies across community health centers (CHCs), as measured in their marginal contribution to overall patient visits. We found APCs in the 90th percentile CHCs provide about 1,840 adjusted-visits per year, whereas APCs in the 10th percentile CHCs provide about 978 adjusted-visits per year. We interviewed leadership at 14 high APC and 16 low APC productivity CHCs to elicit organizational conditions that could explain the difference. Using content analysis and then qualitative comparative analysis, we found several important conditions were more common among high productivity CHCs, including scheduling APCs and physicians for the same number of visits, parity in terms of any financial incentives, and formal education programs for new APCs during onboarding/transition to practice.