1. Determinants of Nursing Home Regulatory Activity in the 50 States: An Analysis from the Political Economy Perspective Christopher M. Kelly, Phoebe S. Liebig, and Lloyd J. Edwards SAMSI Transition Workshop November 10, 2005

2. Acknowledgments Dr. Kelly was supported in part by a postdoctoral fellowship 1 in the Carolina Program in Health and Aging Research (CPHAR) at the University of North Carolina at Chapel Hill 1 Grant ST32AG00272 from the National Institute on Aging

3. Nursing Home Regulation in the United States Under OBRA 87, states survey nursing homes, CMS oversees State surveyors rate nursing home deficiencies according to scope and severity Information is available to consumers on CMS’s Nursing Home Compare website

4. Research Questions What is the extent of nursing home regulatory activity in the 50 states? How did extent change over a three- year period? What factors predict citation volume & severity in the 50 states?

5. Political Economy Perspective State Citizen/Public Sex/Gender Capital Ideology Race Age Class Estes (2001)

6. Linear Mixed Model Used to identify predictors of the volume and severity of state citations Provides estimation and hypothesis testing for modeling population and random effects Can accommodate data missing completely at random

7. Linear Mixed Model is Useful for Studying State Regulatory Activity Longitudinal data (i.e. nursing home quality over several years) Population data - 50 U.S. states. Large sample techniques are challenged. Parsimonious model needed (N =50) Random intercept and slope. Within-subject errors assumed i.i.d.

8. Nursing Home Deficiencies Stable, but Less Severe Number of deficiencies has remained level (about 6 per nursing home) Percentage of severe deficiencies has declined (about 7% of all deficiencies cause actual harm) States vary widely in volume & severity of deficiency citations

9. Possible Predictors of the Extent of State Regulatory Activity External Determinants Urbanization Education Age Political Culture Internal Determinants Nursing Home State Surveying Agency Legislature Interest Groups Governor

10. Linear Mixed Model Predicting State Citation Volume Variableβ Intercept10.3 Time.180 Education-.260 **** Urbanization-.063 ** Total Nursing Home Staffing1.29 ** Total Agency Funding.006 ** Legislative Professionalism-40.2 **** Democratic Governor.669 Time X Democratic Governor-.565 *** Urbanization X Legislative Professionalism.505 *** * p<.1; ** p<.05; *** p<.01; **** p<.005

11. Linear Mixed Model Predicting State Citation Severity Variableβ Intercept.446 Time-1.87 **** Education.482 **** Legislative Professionalism-7.35 ** Democratic Governor6.71 * Education X Democratic Governor-.300 * * p<.1; ** p<.05; *** p<.01; **** p<.005

12. Citation Volume: Effect of Governor’s Political Party

13. Citation Severity: Effect of Governor’s Political Party

14. Future Use of the Linear Mixed Model 1. Repetitive Scheduling of Annual Inspections: States are to avoid inspecting a nursing home during the same month in consecutive years 2. Deficiency Resolution: States are to resolve non-actual harm deficiencies within 60 days and actual harm deficiencies within 30 days

15. Contact Information Christopher M. Kelly, Ph.D. CPHAR Post Doctoral Fellow Institute on Aging University of North Carolina at Chapel Hill Tel 919 843 8065 ckelly@schsr.unc.edu