Research Center
Christopher M. Murtaugh, Ph.D., Principal Investigator
Gil A. Maduro Jr., Ph.D. Research Associate
Timothy Peng, Ph.D. Research Associate
Independent Contractor
Stanley Moore, Senior Programmer

Background: There are a total of 41 home health quality measures in the Outcome-Based Quality Improvement (OBQI) program developed and implemented by the Centers for Medicare and Medicaid Services (CMS). The statistical modeling approach currently used to risk adjust these measures so that agencies serving different types of patients can be compared, is a data-driven "stepwise" approach with a separate set of risk factors used for each OBQI measure.

Purpose: The purpose of this project is to develop and test alternative risk adjustment approaches to assessing the quality of home health care. This project will develop a theory- and evidence-based modeling approach where a common set of risk factors will be used for all OBQI measures, supplemented by additional risk factors specific for each indicator, if necessary. The project also will examine the feasibility of using risk factors from other administrative data sources (e.g. Medicare claims) in addition to the Outcome and Assessment Information Set (OASIS), the data source from which the variables used to construct home health quality measures and risk factors are drawn.

Study Design: The project will use OASIS data from the National Repository at CMS. Data analysis will be conducted in two phases: (1) preliminary data analyses will replicate CMS risk-adjustment models for a subset of 11 of the 41 OBQI quality measures and test alternative models, and (2) final data analyses will replicate and then test alternative risk adjustment models for all 41 outcome measures used in the OBQI framework.

Findings from this project will contribute to CMS's future plans for continued refinement of risk adjustment and outcome measures. The findings also will provide home health care providers with a better understanding of current and alternative modeling approaches for risk adjustment of home health quality indicators. Finally, the findings will be instrumental in supporting efforts to streamline the OASIS instrument by identifying the relative contribution of each OASIS item in risk adjustment models and outlining what items can be excluded from the instrument without jeopardizing the reliability of the risk-adjusted quality indicators and explanatory power of the risk adjustment models.

Sponsor: Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services.