Report

Executive summary This report describes the research plan and results of a PCOR project that followed a statement of work defined in an intra-agency agreement (IAA) between the Office of the Assistant Secretary for Planning and Evaluation (ASPE) and the National Library of Medicine (NLM). ASPE coordinates efforts to build data capacity for patient-centered outcomes research (PCOR).

This is the final report of an AHRQ study to address the operational gap between CFIs and EFIs. This project focused on validating an established CFI using linked claims-EHR databases of multiple large health systems. The project provides a systematic approach that health systems can use to examine the quality of the EHR data and prepare it for the application of EFI measures.

The Synthetic Health Data Generation to Accelerate PCOR project was launched in 2019 by the Office of the National Coordinator for Health Information Technology (ONC).

The Fiscal Year (FY) HHS 2024 Evaluation plan lists a total of thirty-two (32) evaluations from ten (10) Operating and Staff Divisions across the U.S. Department of Health and Human Services (HHS).

This ASPE Research Report summarizes findings about factors affecting Emergency Department wait times and Primary Care appointment scheduling intervals, and it describes strategies Indian Health Service (IHS) federal facilities have implemented associated with decreased wait times in Emergency Departments.Available Reports:

Zero Suicide is a system-wide approach for health systems to improve the quality and safety of care for those at risk of suicide, with the underlying goal of preventing all suicide deaths among patients. Although evidence has indicated that Zero Suicide is effective in reducing suicide-related outcomes, little is known about how organizations fund and sustain the Zero Suicide initiative.

ASPE recently published a narrative review in PLOS Digital Health exploring how synthetic data are being used. Researchers searched published literature and known, publicly available synthetic datasets.

The Early Childhood Systems Collective Impact Project (ECS Collective Impact Project) will help to re-envision a truly coordinated approach to program implementation designed to advance early childhood and family well-being outcomes across federal programs that support expectant parents, children ages 0 to 8, and their families.

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.

This environmental scan, conducted from September 2016 – September 2021, examines the potential impacts of select strategies on the cost, duration, and phase transition probability associated with drug, preventive vaccine, and therapeutic complex medical device development stages.