Imputation of Race and Ethnicity in Health Insurance Marketplace Enrollment Data, 2015-2022 Open Enrollment Periods.

Information on the race and ethnicity of individuals enrolled through the HealthCare.gov Health Insurance Marketplace is critical for assessing past enrollment efforts and determining whether outreach campaigns should be modified or tailored moving forward. However, approximately one-third of insurance applicants do not complete the race and Hispanic ethnicity questions on the Marketplace application. When self-reported race and ethnicity information is missing, other information about an individual can be used to infer race and ethnicity, such as surnames, first names, and addresses, with each characteristic contributing meaningfully to the identification of six mutually exclusive racial and ethnic groups: American Indian (AI)/Alaskan Native (AN); Asian American, Native Hawaiian, and Pacific Islander (AANHPI); Black; Hispanic; Multiracial; and White. Surnames are particularly useful for distinguishing people who identify as Hispanic and AANHPI from other racial and ethnic groups. Geocoded address information is particularly useful in distinguishing Black and White individuals who frequently reside in racially segregated neighborhoods. This article presents the results of imputing race and ethnicity for Marketplace enrollees from 2015 through 2022 using the modified Bayesian Improved First Name Surname and Geocoding (BIFSG) method, developed by the RAND Corporation, which uses surnames, first names, and residential addresses to indirectly estimate race and ethnicity.

Practice Expense Data Collection and Methodology: Phase II Final Report.

Each year, Medicare allocates tens of billions of dollars for indirect practice expense (PE) across services on the basis of data from the Physician Practice Information (PPI) Survey, which reflects 2006 expenses. Because these data are not regularly updated, and because there have been significant changes in the U.S. economy and health care system since 2006, there are concerns that continued reliance on PPI Survey data might result in PE payments that do not accurately capture the resources that are typically required to provide services. In this final phase of a study on PE methodology, the authors address how the Centers for Medicare & Medicaid Services (CMS) might improve the methodology used in PE rate-setting, update data that inform PE rates, or both. The authors conclude that this information is best provided by a survey; therefore, they focus on the advantages and disadvantages of survey-based approaches. They also describe the use of a lean model survey instrument, as well as partnering with another agency to collect data. Finally, the authors describe a virtual town hall meeting held in June 2021 to give stakeholders an opportunity to provide feedback on PE data collection and rate-setting. The system of data and methods that CMS uses to support PE rate-setting is complex; thus, CMS must take into account a number of competing priorities when considering changes to the system. With this in mind, the authors offer a number of near- and longer-term recommendations.