1. Impact of Public Reporting of CABG Hospital Mortality Data on Market Share, Mortality, and Patient Selection Patrick S. Romano, MD, MPH James P. Marcin, MD, MPH Jian J. Dai, PhD Richard L. Kravitz, MD, MSPH David M. Rocke, PhD Madan Dharmar, MBBS Zhongmin Li, PhD AcademyHealth Annual Research Meeting June 10, 2008 Support from the California Office of Statewide Health Planning and Development (OSHPD)

2. Impact of Public Reporting:Conflicting Data on Policy-relevant Questions • Do hospital report cards lead to changes in market share for outliers? • Do hospital report cards lead to improved risk-adjusted mortality, either overall or especially at high mortality outliers? • Do hospital report cards lead to changes in patient selection for surgery, either overall or especially at high mortality outliers?

3. Prior literature on CABG report cards • Volume and market share • NY report cards had no significant effects on hospital volume or market share (Mukamel&Mushlin, Hannan), very transient effects (Romano& Zhou), or effects limited to low-severity patients (Cutler) and/or Medicare beneficiaries (Romano&Zhou) • NY report cards had larger effects on surgeon volume (Mukamel&Mushlin) • Risk-adjusted mortality • NY report cards were associated with reduced mortality statewide (Hannan, Peterson), largely due to exit of low volume surgeons (Smith, Landrum) and focused efforts at high-mortality outlier hospitals (Chassin, Hannan, Cutler) • Report cards in NJ and PA (Hannan), but not Cleveland (Baker, Clough), may also have had favorable overall effects • Patient selection • No overall effects on severity of illness in NY (Hannan) • NY and PA report cards led to clustering of severely ill patients at teaching hospitals (Dranove), with limited evidence of increased selection of low-risk patients after AMI (Dranove) and minimal out-migration (Omoigui) • NY data show increased racial/ethnic disparities in CABG use after AMI (Werner) and sorting of low income/Medicaid/uninsured/African-American patients into high-mortality surgeons (Kreier)

4. History of California CABG Reports

5. Methods: Outcome Variables • Change in volume • % of total statewide market share • Change in outcomes • Risk-adjusted inpatient mortality based on coded data (%) • Risk-adjusted inpatient mortality based on clinical data (%) • Change in patient selection • Expected inpatient mortality based on coded data (%) • Expected inpatient mortality based on clinical data (%) • Prevalence of key risk factors (%) • Prevalence (%) of very high-risk (top 5%) and very low-risk (bottom 5%) patients

6. Methods: Change in Volume – Market Share • Change in total statewide market share after public release of reports • Aggregated PDD data into equal periods of 3, 6, or 12 months before and after each of the first 3 reports (CCMRP) • Student’s T-test (crude) • Multivariable linear mixed regression (“difference-in-differences” model) including independent variables: • Hospital (random intercept) • Time (pre-1, post-1, pre-2, post-2, pre-3, post-3) • Hospital classification status (low outlier, non-outlier, high outlier, non-participant) • Time*Classification status interactions

7. Methods: Change in Quality of Care • Change in risk-adjusted inpatient mortality (based on either clinical or administrative data, and a constant risk model) after public release of reports • Aggregated PDD and CCMRP data (separately) into roughly equal periods of 11-18 months before and after each of the first 3 reports (CCMRP) • Student’s T-test (crude) • Multivariable linear mixed regression (“difference-in-differences” model) including independent variables: • Hospital (random intercept) • Time (pre-1, post-1, pre-2, post-2, pre-3, post-3) • Hospital classification status (low outlier, non-outlier, high outlier, non-participant) • Time*Classification status interactions

8. Methods: Change in Patient Selection • Change in expected inpatient mortality (based on either clinical or administrative data, and a constant risk model) after public release of reports • Aggregated PDD and CCMRP data (separately) into roughly equal periods of 11-18 months before and after each of the first 3 reports (CCMRP) • Student’s T-test (crude) • Multivariable linear mixed regression (“difference-in-differences” model) as previously described • Change in proportion of high risk patients after public release of reports, using either PDD or CCMRP data • Proportion of patients with risk factors with largest Wald (likelihood ratio) statistics in mortality prediction model • Proportion of patients in the highest and lowest 5th percentile of estimated mortality risk

9. Results – Market Share Low-mortality hospitals experienced increased market share relative to high-mortality hospitals (p=0.005), non-outlier hospitals (p=0.002), and non-participating hospitals (p=0.002).

10. Results – Risk Adjusted MortalityAdministrative (PDD) data

11. Results – Risk Adjusted MortalityClinical (CCMRP) data

12. Results – Expected MortalityUsing Administrative (PDD) Data

13. Results – Expected MortalityUsing Clinical (CCMRP) Data

14. Statewide results – patient selectionUsing PDD data

15. Statewide results – patient selectionUsing CCMRP data

16. Results – Patient SelectionUsing PDD data

17. Results – Patient SelectionUsing CCMRP data

18. Conclusions • The release of 3 voluntary public reports on hospital mortality for CABG surgery in California was associated with: • Small but significant increases in market share for low mortality outliers (at 3, 6, and 12 months after publication) • No significant trend in market share for high-mortality outliers, non-outliers, or non-participating hospitals • No significant changes within or across strata in observed or risk-adjusted mortality using administrative data, but overall risk-adjusted mortality increased using clinical data • No evidence of risk selection by high-mortality outliers or non-outliers, but limited evidence of slight risk selection by low-mortality outliers

19. Policy Implications • Voluntary public report cards on hospital CABG mortality appear to have modest effects in the expected direction for market share, but minimal or no effects on quality of care and patient selection. • To achieve the desired effects on quality of care, public reporting on surgeon-specific outcomes and/or mandatory participation may be necessary (but undesired effects on patient selection may also be unleashed)