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Abstract #154659

Dana B. Mukamel, PhD, Department of Medicine, Center for Health Policy Research, University of California, Irvine, 111 Academy, Suite 220, Irvine, CA 92697, 949-824-8873, dmukamel@uci.edu, David L. Weimer, PhD, LaFollette School of Public Affairs, University of Wisconsin - Madison, 1225 Observatory Drive, Madison, WI 53706, Yue Li, PhD, MS, Department of Medicine, SUNY at Buffalo, ECMC, Clinical Center CC-163, 462 Grider Street, Buffalo, NY 14215, Laurent Glance, MD, Department of Anesthesiology, University of Rochester Medical Center, 601 Elmwood Ave., Box 604, Rochester, NY 14642, William D. Spector, PhD, Agency for Healthcare Research & Quality, 540 Gaither Road, Room 5125, Rockville, MD 20850, Jacqueline S. Zinn, PhD, Fox School of Business & Management, Temple University, 413 Ritter Annex, Philadelphia, PA 19122-6091, and Laura Mosqueda, Family Medicine/Program in Geriatrics, University of California Irvine Medical Center, 101 The City Drive, Building 200, Suite 835, Route 81, Orange, CA 92868.

The Centers for Medicare & Medicaid Services (CMS) publishes quality measures (QMs) for nursing homes. We examined several of the measures to determine if a more comprehensive risk adjustment changes conclusions about the quality of individual nursing homes. The analysis included measures for pressure sores, physical restraints, pain for long and for short stay patients. We used the Minimum Data Set (MDS) to obtain information about all nursing home residents in the period 2001-2005. We estimated random effects logistic models. The dependent variables were defined based on the CMS definition of its QMs. The independent variables included individual level risk factors that were identified by a geriatrician as those likely to influence the health outcome. These models were used to calculate facility-level risk-adjusted quality measures that were then compared to the CMS QMs. To measure the agreement between the two types of quality measures we calculated Kappa statistics, nationally and stratified by state. Kappa values for pressure sores averaged 0.89 for low quality outliers and 0.59 for high quality outliers (defined as those in the 5th percentile of the distribution), pain for long stay patients averaged 0.84 and 0.79, and for short stay patients 0.80 and 0.61, respectively. Because of the skewed distribution of physical restraints we calculated Kappa for terciles and it averaged 0.86. These Kappa values suggest a moderate to very good agreement between the CMS QMs and the risk adjusted QMs. However, these findings also suggest that the CMS measures could be improved by additional risk adjustment.

Learning Objectives:

• Be familiar with the Nursing Home Compare Quality report card
• Understand issues related to quality measurement in nursing homes
• Gain knowledge about risk-adjustment for outcome based quality measures
• Assess the importance of risk-adjustment of the CMS published QMs

Keywords: Nursing Homes, Quality of Care

Related Web page: www.medicare.gov/NHCompare/Home

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.