Volume-Outcome Relationship: An Econometric Approach to CABG Surgery

1. Volume-Outcome Relationship: An Econometric Approach to CABG Surgery Hsueh-Fen Chen (VCU) Gloria J. Bazzoli (VCU) Askar Chukmaitov (FSU) Funded by the Agency for Healthcare Research and Quality (HS 13094-03)

2. Rationale for the Study • Clinicians and policymakers continue to debate the basis for volume-quality relationships: • Practice makes perfect • Selective referral • Outcomes of CABG surgery are of great interest: • one of the most common surgeries in the US • volume thresholds have been recommended by Leapfrog Group • regionalization vs non-regionalization

3. Research Question • Do volume-outcome relationships for CABG surgery in hospitals reflect selective referral, practice makes perfect, or both?

4. Findings from Prior Research • Several studies have found high CABG volume does not lead to better outcomes at the hospital level • (Luft, 1980; Luft, et al., 1987; Shroyer, 1996) • At patient level, mixed results exist about CABG volume-outcome relationship • (Hannan, et al., 1989; 1991; Shroyer, et al., 1996; Sollano et al., 1999; Birkmeyer, et al., 2002; Wu, et al., 2004; Peterson et al., 2004).

5. Limitations of Prior Research: Contribution of Current Study • Is volume exogenous or endogenous? • Use of cross-sectional study design versus longitudinal study design • Generalizability of findings

6. Study Methods and Data Sources • Research Approach • A longitudinal design: 1995 - 2000 • Data Sources • HCUP-SID (AZ, CA, CO, FL, IA, MD, MA, NJ, NY, WA, WI) • AHA • ARF • InterStudy • Sample • 1,760 nonfederal, general short-term hospitals with at least 6 CABG surgeries a year • 1,200 of them had complete data

7. Analytical Approach • The model for Practice Makes Perfect • Qualityit = β0+ β1 log( Volumeit )+ β2 Hospitalit + β3 Marketit + β4 IVQit+ β5 Statei + β6 Timeit + θi + εit • The model for Selective Referral • log(Volume)it = γ0 + γ1Qualityit + γ2 Hospitalit + γ3 Marketit + γ4 IVVit + γ5 Statei + γ6 Timeit + Ψi + μit

8. Measures • Primary Variables of Interest: • Quality: risk-adjusted in-hospital CABG mortality rate; calculated with AHRQ IQI software • Volume: log of the sum of discharges with the procedure ICD-9-CM codes: 3610-3619 • Control Variables • Hospital Characteristics: ownership, teaching status, log (total surgical operations), system/ network affiliation, case-mixed adjusted length of stay • Market factors: log (per capita income) and HMO penetration at the MSA level • State and time dummy variables

9. Results of Specification Tests • Instruments are valid. • Instruments of volume (IVV): log (size), HHI, and tertiary services. • Instruments of quality (IVQ): • Staffing: RN and LPN per 1,000 inpatient days. • Severity of illness: patient acuity and case mix index. • Hospital-specific component of error exists (i.e., θi ≠0 and Ψi ≠0 ). • Fixed effects found to be preferred estimation method to random effects

10. Results • Practice makes perfect (DV: mortality) • Selective Referral (DV: log (volume))

11. Study Limitations • Administrative data used for constructing risk adjusted mortality rates • Strictly examine in-hospital mortality not mortality that occurs after discharge • Lack of data on physician volume • May be that practice makes perfect hypothesis is more relevant for physicians than for hospitals

12. Study Implications • Longitudinal study design with instruments is recommended in future research on volume-quality relationships • From hospital perspective: • Regionalization of care based on volume thresholds may need to be reconsidered • Competition based on quality may be preferred.

13. Questions and Suggestions