Administrative Data

Using a national Medicaid database, the report shows significant racial/ethnic disparities in mental health service use among children during the COVID-19 pandemic.

In recent years several researchers and child welfare agencies have begun developing predictive risk models to support child welfare decision-making. Predictive analytics is a sophisticated form of risk modeling that uses historical data to understand relationships between myriad factors to estimate a probability score for the outcome of interest.

Medicaid pays for nearly half of all births in the United States, including most births by Black and Hispanic pregnant population.

This project focused on validating an established claims-based frailty indexes (CFI) using linked claims-EHR databases of multiple large health systems. Additionally, the project assessed and compared the EHR and claims data of these data sources to ensure sufficient data quality for frailty analysis.

This posting includes a report prepared by the RAND Corporation, “State All Payer Claims Databases Understanding the Current Landscape and Challenges to Use,” which builds on a 2021 report “The History, Promise and Challenges of State All Payer Claims Databases.” The new report provides additional detail on the objectives of and use cases for APCDs, the current APCD landscape, and implementatio

The Assistant Secretary for Planning and Evaluation (ASPE) contracted with RAND Health Care to develop methods for imputing race and ethnicity among people who selected Marketplace plans on HealthCare.gov but did not report their race or ethnicity, and to apply these methods to data from the 2015 to 2022 Open Enrollment Periods.

This report analyzes newly-released data from CMS that provides information on changes in ownership among hospitals and skilled nursing facilities (SNFs), based on information reported to CMS through the Provider Enrollment, Chain, and Ownership System (PECOS).

The Child and Caregiver Outcomes Using Linked Data project provides technical assistance to states to develop state-specific datasets linking the Medicaid administrative claims of parents with the records of their children from the child welfare system. The data will be combined into a multi-state, de-identified data sets for secondary data analysis.

Federal surveys relied on by researchers and policymakers for estimates of the uninsured population have been disrupted by the COVID-19 pandemic, potentially influencing the accuracy of their estimates. This report analyzes evidence from a variety of data sources, including surveys and administrative data, which collectively indicate that the number of uninsured people in the U.S.

The COVID-19 pandemic and policy responses, including stay-at-home orders and expanded use of telework, disrupted data collection for major HHS data systems. This brief identifies the impact of the pandemic on 29 HHS statistical surveys and administrative data systems widely used by policymakers and the public.