Volume-Outcome Relationship: An Econometric Approach to CABG Surgery Hsueh-Fen Chen (VCU) Gloria J....
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Transcript of Volume-Outcome Relationship: An Econometric Approach to CABG Surgery Hsueh-Fen Chen (VCU) Gloria J....
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)
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
Research Question
Do volume-outcome relationships for CABG surgery in hospitals reflect selective referral, practice makes perfect, or both?
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).
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
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
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
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
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
Results
Practice makes perfect (DV: mortality)
Selective Referral (DV: log (volume))
OLS OLS with IVs FE FE with IVs
Log (volume)
-.006(.00009)***
.0003(.0035)
-.0003(.0021)
-.0002(.0205)
OLS OLS with IVs FE FE with IVs
Mortality -3.75(.077)***
2.23(3.34)
-.709(.485)
-4.28(2.14)**
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
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.
Questions and Suggestions