Top Management Stability’s Impact on Turnover and Deficiencies

1. Top Management Stability’s Impact on Turnover and Deficiencies Christopher E. Johnson, Ph.D. Associate Professor Director, MHA Program Department of Health Policy and Management

2. Acknowledgements • Research team • Kathryn Hyer, Ph.D. - University of South Florida • Jeffrey Harman, Ph.D – University of Florida • Mishu Popa – University of South Florida • Robert Weech-Maldonado, Ph.D. – University of Florida • Lloyd Dewald – University of Florida • The research reported here was supported by The Commonwealth Fund and the US Administration on Aging.

3. Background • Multiple studies have examined staffing turnover and how it impacts quality in nursing homes. • A few studies have examined administrator and director of nursing tenure’s impact on turnover and quality in nursing homes. • Almost all of these studies are cross-sectional. • Almost all of these studies use primary data collection tools to gather turnover/tenure information. • “Bad” vs. “good” top management turnover.

4. Research Questions • What are the impacts of top management stability on nurse staff turnover in Florida nursing homes? • What are the impacts of top management stability on the number of licensing survey deficiency cites against Florida nursing homes?

5. Data • Florida’s Nurse Staffing Reports 2002 - 2004 • Florida’s Medicaid Cost Reports 2002 - 2004. • CMS OSCAR data was used for structural characteristics. • Area Resource File was used for county level demographic data.

6. Dependent Variables • CNA Turnover – total terminated divided by yearly average employees. • LN Turnover – total all licensed nurses terminated divided by yearly average total licensed nurses. • Quality of Care Deficiencies – Total annual quality of care citations. • Quality of Life Deficiencies – Total annual quality of life deficiencies. • Total Deficiencies – Total of all annaul deficiencies cited against facility.

7. Explanatory Variables • Stable management – dichotomous variable that measures if both administrator and DoN were employed continuously during the year. • Stable administrator – dichotomous variable that measures if an administrator was continuously employed by facility during the year. • Stable DoN - dichotomous variable that measures if a DoN was continuously employed by facility during the year.

8. Control Variables • Organizational characteristics – CNA hours per resident day, RN hours per resident day, for profit ownership, size, Medicaid ratio, Medicare ratio, acuity index, system membership, and occupancy rates. • Market characteristics – located in metropolitan area, county African American population, county Hispanic population, county population women work, Medicaid market, county RNs per 1000, county LPN per 1000, average RN county wage, average CNA county wage, and county personal income per capita.

9. Methods • CNA and LN turnover were classified as high, medium, or low. • Ordered logit for turnover models. • We believe that the relationship between stability and turnover is ordered as opposed to multinomial. • Negative binomial regression for deficiency models. • Chosen because of the number of zeroes in the dependent variable.

10. Descriptive Statistics

11. Descriptive Statistics

12. Results - Turnover

13. Results - Deficiencies

14. Discussion • Top management stability appears to have some impact on turnover and deficiencies cited against nursing homes. • This sort of “bad” turnover among top management could be used as a flag for policy makers when trying to identify potential problem facilities in their states. • Nursing homes may want to consider ways of hiring top management teams that will be in place for 12 continuous months.

15. Conclusion • Limitations • Turnover is calculated post three months employment. • Endogeneity relationship between stability and turnover. • Future research • Multi-year stability and turnover/deficiencies • Impact of stability on quality indicators • Impact of stability on change in quality

16. Questions?