California Mental Health Care Management Program (CalMEND): A Quality Improvement Collaborative

1. Excess Non-Psychiatric Hospitalization and Emergency Department Use Among Medi-Cal Beneficiaries with Serious Mental IllnessPreliminary ResultsCheryl E. Cashin, Ph.D.UC Berkeley School of Public Health California Institute of Mental HealthFebruary 7, 2008 California Mental Health Care Management Program (CalMEND): A Quality Improvement Collaborative

2. Acknowledgments • Funding from the National Institute of Mental Health (Mental Health Economics Research Training Grant) • The CalMEND Team • Special thanks to the research team: • Dr. Barry Handon, DHCS • Marco Gonzales, DHCS • Pauline Chan, DHCS and • Julie Cheung, CalMEND • Karin Kalk, CalMEND • Jim Klein, DHCS

3. The Problem • Compared with the general population, individuals with serious mental illness: • have higher ratesofphysical illness and reduced life expectancy • have greater likelihood of multiple co-occurring chronic conditions • may have less access to timely, appropriate primary health care • Untreated medical conditions may lead to lower quality of life, barriers to recovery, and overuse of costly services

4. Evidence from Other States • Growing awareness that Medicaid beneficiaries with multiple chronic conditions are the costliest: • 4% of Medicaid beneficiaries nationally account for 50% of expenditures • Adults with chronic conditions make up 40% of the Medicaid population but > 80% of expenditures • Little evidence specific to the SMI population • Results from NY suggest total claims for the SMI population can be up to 2x claims for other disabled population (Billings and Mijanovich 2007)

5. Objectives of the Study • Examine differences in the patterns of health care utilization between individuals with and without SMI • Identify excess hospitalization and emergency department use and costs attributable to having a SMI • Identify characteristics of health service delivery and quality of care associated with excess costs that are amenable to intervention

6. Data • Medi-Cal eligibility and claims files for individuals with and without SMI from 2002-2006 • Criteria for identification of SMI: • Short-Doyle claim and/or • Antipsychotic prescription • Other selection criteria: • Continuous Medi-Cal eligibility (2002-2006) • Age between 18 and 64 • Fee-for-service only (not enrolled in managed care)

7. Measures to Protect Confidentiality • CPHS approval of the research project • Protected health information analyzed contains no identifying information (e.g. name, address, SSN) • Data are encrypted, password-protected, and stored in a locked room • Results will be presented as aggregate statistical analysis only

8. Sample Size

9. The Study Population: Total Claims in 2006 billion billion

10. The Study Population: Per Capita Claims in 2006

11. Methods • Comparison of mean hospitalization rates between the SMI and control population • Unadjusted means • Logistic regression to adjust means to control for age, gender and ethnicity • Estimate the probability of hospitalization given specific individual characteristics • Examine statistical significance of the effect of SMI on the probability of hospitalization

12. Results:Unadjusted Means Chi-2 = 710.56 Pr = 0.000**

13. Results:Logistic Regression • SMI is associated with a 31.2% increase in the odds of being hospitalized in a given year, controlling for individual characteristics • This effect is statistically significant at the 1% level • Age, gender and ethnicity also have statistically significant effects

14. Highest Hospitalization Rates Low Impact of SMI Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 % Hospitalized

15. Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 Lowest Hospitalization Rates Low Impact of SMI % Hospitalized

16. Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 Highest Impact of SMI % Hospitalized

17. Highest Impact of SMI Difference= 9% Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 % Hospitalized

18. Ambulatory Care-Sensitive Hospitalization • Ambulatory care sensitive (ACS) hospitalization  a hospital admission that should be avoidable with effective intervention at the primary health care level • ACS hospitalization is widely used: • As an indicator of access, quality and effectiveness of primary health care • To measure/monitor health disparities

19. Ambulatory Care-Sensitive Diabetes Hospitalization • Used Institute of Medicine ICD-9 criteria for ambulatory care-sensitive diabetes hospitalization • Primary diagnosis ICD-9 code = 2500-2503, 2508, or 2509

20. Results:Unadjusted Means Chi-2 = 39.65 Pr = 0.000**

21. Results:Logistic Regression • SMI is associated with a 53.0% increase in the odds of being hospitalized in a given year, controlling for individual characteristics • This effect is statistically significant at the 1% level • Age, gender and ethnicity also have statistically significant effects.

22. Highest hospitalization rates Gender and Ethnic Differences in Impact of SMI on ACS-Diabetes Hospitalization % Hospitalized No significant difference No significant difference

23. Gender and Ethnic Differences in Impact of SMI on ACS-Diabetes Hospitalization Highest impact of SMI % Hospitalized No significant difference No significant difference

24. What Does This Tell Us So Far? • Medi-Cal beneficiaries with SMI have significantly non-psychiatric hospitalization, even relative to another high-need population • African Americans, with and without SMI, have the highest rates of hospitalization • Females and Latinos are particularly vulnerable to the impact of SMI • Specific chronic conditions, such as diabetes, may be important causes of excess hospitalization among the SMI population

25. How can the results be used? Next steps required: • Quantifying the excess costs of excess hospitalization among the SMI population can justify investment in interventions. • Identifying factors associated with increased hospitalization among the SMI population can contribute to the design of interventions.

26. California Mental Health Care Management Program (CalMEND): A Quality Improvement Collaborative Thank you.Cheryl E. Cashin, Ph.D.