An eye on equity: faricimab-driven health equity improvements in diabetic macular oedema using a distributional cost-effectiveness analysis from a UK societal perspective.

BACKGROUND/OBJECTIVES: Diabetic macular oedema (DMO) is a leading cause of blindness in developed countries, with significant disease burden associated with socio-economic deprivation. Distributional cost-effectiveness analysis (DCEA) allows evaluation of health equity impacts of interventions, estimation of how health outcomes and costs are distributed in the population, and assessments of potential trade-offs between health maximisation and equity. We conducted an aggregate DCEA to determine the equity impact of faricimab. METHODS: Data on health outcomes and costs were derived from a cost-effectiveness model of faricimab compared with ranibizumab, aflibercept and off-label bevacizumab using a societal perspective in the base case and a healthcare payer perspective in scenario analysis. Health gains and health opportunity costs were distributed across socio-economic subgroups. Health and equity impacts, measured using the Atkinson inequality index, were assessed visually on an equity-efficiency impact plane and combined into a measure of societal welfare. RESULTS: At an opportunity cost threshold of £20,000/quality-adjusted life year (QALY), faricimab displayed an increase in net health benefits against all comparators and was found to improve equity. The equity impact increased the greater the concerns for reducing health inequalities over maximising population health. Using a healthcare payer perspective, faricimab was equity improving in most scenarios. CONCLUSIONS: Long-acting therapies with fewer injections, such as faricimab, may reduce costs, improve health outcomes and increase health equity. Extended economic evaluation frameworks capturing additional value elements, such as DCEA, enable a more comprehensive valuation of interventions, which is of relevance to decision-makers, healthcare professionals and patients.

Health Equity Adjustment and Hospital Performance in the Medicare Value-Based Purchasing Program.

Importance: Medicare's Hospital Value-Based Purchasing (HVBP) program will provide a health equity adjustment (HEA) to hospitals that have greater proportions of patients dually eligible for Medicare and Medicaid and that offer high-quality care beginning in fiscal year 2026. However, which hospitals will benefit most from this policy change and to what extent are unknown. Objective: To estimate potential changes in hospital performance after HEA and examine hospital patient mix, structural, and geographic characteristics associated with receipt of increased payments. Design, Setting, and Participants: This cross-sectional study analyzed all 2676 hospitals participating in the HVBP program in fiscal year 2021. Publicly available data on program performance and hospital characteristics were linked to Medicare claims data on all inpatient stays for dual-eligible beneficiaries at each hospital to calculate HEA points and HVBP payment adjustments. Exposures: Hospital Value-Based Purchasing program HEA. Main Outcomes and Measures: Reclassification of HVBP bonus or penalty status and changes in payment adjustments across hospital characteristics. Results: Of 2676 hospitals participating in the HVBP program in fiscal year 2021, 1470 (54.9%) received bonuses and 1206 (45.1%) received penalties. After HEA, 102 hospitals (6.9%) were reclassified from bonus to penalty status, whereas 119 (9.9%) were reclassified from penalty to bonus status. At the hospital level, mean (SD) HVBP payment adjustments decreased by $4534 ($90 033) after HEA, ranging from a maximum reduction of $1 014 276 to a maximum increase of $1 523 765. At the aggregate level, net-positive changes in payment adjustments were largest among safety net hospitals ($28 971 708) and those caring for a higher proportion of Black patients ($15 468 445). The likelihood of experiencing increases in payment adjustments was significantly higher among safety net compared with non-safety net hospitals (574 of 683 [84.0%] vs 709 of 1993 [35.6%]; adjusted rate ratio [ARR], 2.04 [95% CI, 1.89-2.20]) and high-proportion Black hospitals compared with non-high-proportion Black hospitals (396 of 523 [75.7%] vs 887 of 2153 [41.2%]; ARR, 1.40 [95% CI, 1.29-1.51]). Rural hospitals (374 of 612 [61.1%] vs 909 of 2064 [44.0%]; ARR, 1.44 [95% CI, 1.30-1.58]), as well as those located in the South (598 of 1040 [57.5%] vs 192 of 439 [43.7%]; ARR, 1.25 [95% CI, 1.10-1.42]) and in Medicaid expansion states (801 of 1651 [48.5%] vs 482 of 1025 [47.0%]; ARR, 1.16 [95% CI, 1.06-1.28]), were also more likely to experience increased payment adjustments after HEA compared with their urban, Northeastern, and Medicaid nonexpansion state counterparts, respectively. Conclusions and Relevance: Medicare's implementation of HEA in the HVBP program will significantly reclassify hospital performance and redistribute program payments, with safety net and high-proportion Black hospitals benefiting most from this policy change. These findings suggest that HEA is an important strategy to ensure that value-based payment programs are more equitable.

Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance.

Importance: Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes. Objectives: To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non-dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value). Design, Setting, and Participants: Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019. Main Outcomes and Measures: We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method). Exposures: Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance-quality, cost, and value (quality relative to cost). Results: Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P < .01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P = .01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P < .01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity. Conclusion and Relevance: A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals.

Addressing Racial Capitalism's Impact on Black Essential Workers During the COVID-19 Pandemic: Policy Recommendations.

Black Americans are more likely to be essential workers due to racial capitalism. Because of the COVID-19 pandemic, essential workers are less able to adhere to social distancing and stay-at-home guidelines due to the nature of their work, because they are more likely to occupy crowded households, and are more likely to possess pre-existing health conditions. To assist Black essential workers in preventing infection or reducing the intensity of symptoms if contracted, vaccination against the virus is essential. Unfortunately, Black essential workers face considerable barriers to accessing vaccinations and are hesitant to receive the vaccine due to widespread misinformation and justified historical mistrust of the American medical system. The purpose of this work is to (1) describe the disproportionate impact of COVID-19 on Black essential workers due to racial capitalism, (2) outline the socioeconomic and racial barriers related to vaccination within this population, and (3) to suggest policy-related approaches to facilitate vaccination such as access to on-site vaccination opportunities, the funding of community outreach efforts, and the mandating of increased employee benefits.

SAFER model: Strategic allocation of fundamental epidemic resources.

BACKGROUND: To describe the Strategic Allocation of Fundamental Epidemic Resources (SAFER) model as a method to inform equitable community distribution of critical resources and testing infrastructure. METHODS: The SAFER model incorporates a four-quadrant design to categorize a given community based on two scales: testing rate and positivity rate. Three models for stratifying testing rates and positivity rates were applied to census tracts in Milwaukee County, Wisconsin: using median values (MVs), cluster-based classification and goal-oriented values (GVs). RESULTS: Each of the three approaches had its strengths. MV stratification divided the categories most evenly across geography, aiding in assessing resource distribution in a fixed resource and testing capacity environment. The cluster-based stratification resulted in a less broad distribution but likely provides a truer distribution of communities. The GVs grouping displayed the least variation across communities, yet best highlighted our areas of need. CONCLUSIONS: The SAFER model allowed the distribution of census tracts into categories to aid in informing resource and testing allocation. The MV stratification was found to be of most utility in our community for near real time resource allocation based on even distribution of census tracts. The GVs approach was found to better demonstrate areas of need.

Incorporating health inequality impact into economic evaluation in low- and middle-income countries: a systematic review.

INTRODUCTION: As well as improving population health, promoting equity in health is one of the key goals of health policy in low- and middle-income countries (LMICs). However, it is less clear how equity is defined, or how it may impact on resource allocation decisions. We investigated the degree to which health inequalities have been considered in economic evaluation of health interventions in LMICs, and what demographic or socioeconomic characteristics were used to define equity relevant subgroups. AREAS COVERED: We reviewed publications since 2010 from three main databases following the search strategy developed by including the key terms 'health inequalities/health disparities/health equity,' 'economics' and 'low- and middle-income countries' in the title or abstract. Twelve studies were identified, mainly focusing on interventions for the more vulnerable groups such as children and women. EXPERT OPINION: Some attempts have been made to assess interventions' impact on health inequality and there is increasing interest in evaluating it, although research in this area is lacking. Population subgroups highlighted in the included studies were those differing in socioeconomic status. Most studies reported the results across subgroups to illustrate inequality impact, and the newly developed methods, extended cost-effectiveness analysis and distributional cost-effectiveness analysis, have also been applied.