The Impact of BBA, HMOs, and Hospital Competition on Quality of Cardiac Care

1. The Impact of BBA, HMOs, and Hospital Competition on Quality of Cardiac Care Hsueh-Fen Chen Gloria J. Bazzoli Founded by the Agency for HealthCare Research and Quality (HS 010730-04)

2. Rationale for The Study (I) • Limited generalizability of evidence for the impact of BBA on patient outcomes (Volpp, et al., 2005; Sesahmani et al., 2006; 2006b). • Updated evidence for the HMO effect on patient outcomes is needed due to market power change (Devers, 2003; Ginsburg, 2005; Berenson et al. 2006). • Limited evidence about influence of payment methods (i.e. fixed or negotiated rate) on patient outcomes in markets with different levels of competition (Gaynor, 2006).

3. Rationale for The Study (II) • Quality of cardiac care • Cardiac disease is a high risk, high cost, and high volume disease in the US (CDC, 2006). • Competition in cardiac services has increased (Pauly, 2004; Bazzoli et al., 2006; Berenson et al., 2006). • The quality of care for entire range of cardiac services has not been studied.

4. Research Questions • What is the relationship between quality of cardiac care and BBA financial pressure? • What is the relationship between quality of cardiac care and HMO market characteristics? • How does hospital competition mediate the relationship between quality of cardiac care and BBA/HMOs?

5. Study Method (I) – Research Design and Data Source • Research Design • A two-period panel study design—1995 and 2002 • Data Source • HCUP-SID: AZ, CA, CO, FL, NJ, NY, WA, WI • AHA Annual survey, BBA estimated payment factors. • ARF • HealthLeader-Interstudy • Medicare cost report.

6. Study Method (II)-Sample • Three categories of cardiac services • High-intensity surgery category: • DRG: 104-111, 514-515, and 527 • Low/moderate-intensity surgery category: • DRG: 112-120, 478-479, and 516-518 • Medical-service category: • DRG: 121-145 excluding 129. • Non-federal general urban hospitals with at least 5 admissions in any group of services.

7. Study Method (III)-Measurement • DV: • Total number of observed deaths. • IVs: • BBA pressure index (H-BBA, M-BBA, and L-BBA). • HMO penetration and the number of HMOs at the MSA level (H-HMOp/ L-HMOp, H-HMOn/ L-HMOn). • Mediators: • Hospital competition (H-comp/ L-comp).

8. Study Method (IV)-Measurement (Cont.) • Control Variables: • Hospital characteristics: • ownership, size, high technology, system affiliation, teaching status, RN per adjusted patient day, DRG case mix, payer-mix, volume. • Market characteristics: • per capita income, aged 65 and over, occupancy rate • Patient characteristics: • ALOS, % of female, % of minority, 2nd Dxs • Risk adjusted indicator: log( predicted deaths). • State and Year

9. Analytical Approach • The unit of analysis: hospital. • Poisson Fixed Effect Model.

10. Results- Outcomes for All Payers (Incident Rate Ratio) **: P<0.05; *P<0.1

11. Study Limitations • Limitations • Administrative data used for constructing risk adjusted mortality. • Strictly examine in-hospital mortality not mortality that occurs after discharge or other quality indicators. • Endogeneity from competition measure.

12. Preliminary Findings • Hospitals with high BBA pressure have higher mortality than those with low BBA pressure in low/moderate intensive surgery group. • Hospital competition mitigates the positive effect of BBA on mortality in low/moderate intensive surgery group.

13. Questions and Suggestions