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The pay equity component measures the difference in compensation of a hospital executives compared to health care workers without advanced degrees.

We obtained data for Chief Executive Officer (CEO) compensation from three different sources: the Securities and Exchange Commission’s (SEC) database, public payroll data, and IRS 990 filings. When CEO pay was unavailable, this information was imputed (estimated) using known values in regression models. For hospitals within systems (2 or more hospitals), we distributed the system CEO’s salary among the constituent hospitals using the percentage of total revenue each hospital generated.

We obtained average worker wages from two sources: the CMS Healthcare Cost Report Information System (HCRIS) and the Bureau of Labor Statistics (BLS). We included lower wage staff, such as janitorial and kitchen staff, and medical records personnel, and excluded professional staff such as physicians and nurse practitioners, whose jobs require specialized degrees. For hospitals that had incomplete wage index information in HCRIS, we used BLS estimates of healthcare industry employment data for metropolitan and non-metropolitan statistical areas. These wage estimates also did not include highly paid workers such as executives and physicians. We then estimated hourly wages for CEOs based on the work hours listed in their IRS forms, defaulting to 40 when the hours were not listed, and calculated a ratio of CEO pay to average worker pay.

The community benefit metric measures hospital spending on charity care and other community health initiatives, as well as their service of Medicaid patients. Community benefit is a composite of three details: Charity care, Medicaid revenue, and Other community benefit spending. For hospitals with data available for all three metrics, each metric was weighed equally in the composite at ⅓ of the total score. For hospitals with data for two of the metrics available, each metric was weighed equally in the composite as half of the total score.

Charity care, or financial assistance, is free or discounted care provided on the basis of the patient’s financial situation. We measured charity care as a share of total expenses using the Centers for Medicare and Medicaid’s Hospital Cost Reports (HCRIS). Medicaid patient revenue was measured as a proportion of total patient revenue using HCRIS data from 2018.

Hospital spending on certain other types of community benefits, as a share of total expenses, was calculated using 2018 IRS data. For hospitals that filed with multiple hospitals as one tax entity, each individual hospital’s community benefit spending was estimated by prorating based on each hospital’s share of system revenue.

This metric includes a subset of community benefit spending that we deemed to be meaningful: subsidized health services, such as free clinics, some emergency services, telehealth services, and other services provided at a loss to the hospital; community health improvement activities such as health fairs, community health education classes, immunizations, interpreter services; contributions to community organizations; and community building activities that help increase the capacity of the community to address health needs and often address the "upstream" factors, or social determinants, which impact health, such as education, air quality, and access to nutritious food.

The inclusivity component evaluates the extent to which a hospital’s patient population reflects the demographics of the community in which it is located, based on race, income, and education levels. To create this metric, we used Medicare claims from 2018 and the U.S. Census Bureau’s American Community Survey from 2018.

Each hospital’s inclusivity score shows how the demographics of the hospitals’ community area (who the hospital could serve) compare to their actual patient population (who the hospital does serve). The “community area” radius is defined by the distance from which about 90% of the hospital’s Medicare patients travel.

To calculate community area demographics, we applied Census data for people over the age of 65 on race, income, and education levels within all zip codes that fell within the defined hospital community area. We exponentially reduced the contribution from zip codes beyond the point at which 50% of a hospital’s patients had come. These demographics were then compared to the zip code demographics of the hospital’s actual patient counts.

Hospitals received higher scores if they had higher patient counts from zip codes with greater proportions of non-white patients, lower incomes, and lower levels of education, compared to their community area. Inclusivity by race, income, and education were weighted equally to create the overall inclusivity score. Hospitals in racially homogenous areas (97% or more white) were only scored on inclusivity by income and education.