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

2. 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. 3 The Problem Compared with the general population, individuals with serious mental illness: higher ratesofphysical illnessreduced life expectancy  have higher rates of physical illness and reduced life expectancy greater likelihood of multiple co-occurring chronic conditions  have greater likelihood of multiple co-occurring chronic conditions less access  may have less access to timely, appropriate primary health care lower quality of lifebarriers to recovery overuse of costly services Untreated medical conditions may lead to lower quality of life, barriers to recovery, and overuse of costly services

4. 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. 5 Objectives of the Study patterns of health care utilization Examine differences in the patterns of health care utilization between individuals with and without SMI excess hospitalization emergency department use costs Identify excess hospitalization and emergency department use and costs attributable to having a SMI characteristics of health service deliveryquality of care Identify characteristics of health service delivery and quality of care associated with excess costs that are amenable to intervention

6. 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. 7 Measures to Protect Confidentiality CPHS approval of the research project no identifying information 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. 8 Sample Size

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

10. 10 The Study Population: Per Capita Claims in 2006

11. 11 Methods mean hospitalization rates Comparison of mean hospitalization rates between the SMI and control population Unadjusted means Logistic regression 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. 12 Results: Unadjusted Means Chi-2 = 710.56 Pr = 0.000** HospitalizedNot Hospitalized Total SMI14.2% (12,545) 85.8% (75,931) 88,476 Non-SMI10.7% (19,193) 89.3% (161,063) 180,256 Total11.8% (312,738) 88.2% (236,994) 268,732

13. 13 Results: Logistic Regression 31.2% increase 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. 14 Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 Highest Hospitalization Rates Low Impact of SMI % Hospitalized

15. 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. 16 Gender and Ethnic Differences in Impact of SMI on Non-Psychiatric Hospitalization Age 56-64 Highest Impact of SMI % Hospitalized

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

18. 18 Ambulatory Care-Sensitive Hospitalization Ambulatory care sensitive (ACS) hospitalization  hospital admission that should be avoidable 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. 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. 20 Results: Unadjusted Means Chi-2 = 39.65 Pr = 0.000** Hospitalized for ACS Diabetes Diagnosis Not Hospitalized Total SMI0.30% (265) 99.7% (88,211) 88,476 Non-SMI0.10% (233) 99.9% (180,023) 180,256 Total0.02% (498) 99.8% (268,234) 268,732

21. 21 Results: Logistic Regression 53.0% increase 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. 22 Gender and Ethnic Differences in Impact of SMI on ACS-Diabetes Hospitalization No significant difference No significant difference Highest hospitalization rates % Hospitalized

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

24. 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. 25 How can the results be used? Next steps required: justify investment in interventions Quantifying the excess costs of excess hospitalization among the SMI population can justify investment in interventions. contribute to the design of interventions Identifying factors associated with increased hospitalization among the SMI population can contribute to the design of interventions.

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