Administrative Data

The authors conducted a landscape scan to identify environmental data suitable for health services research (HSR) and patient centered outcomes research (PCOR). Additional research was done to uncover examples of and opportunities for data linkage with other HHS 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 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 implementati

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).

Program Integrity and Effectiveness through Data and Analysis (PIEDA) aims to enhance the capacity to share and link data between state child welfare and Medicaid agencies on issues at the nexus of the two systems. PIEDA intends to sustainably improve the data infrastructure of states to increase their ability to analyze challenges experienced by families involved in child welfare systems.

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.