Process Compliance and
Surgical Mortality
Lauren Hersch Nicholas
University of Michigan
June 28, 2009
Background
• Poor overall quality and variation in
surgical quality across U.S. hospitals welldocumented
• As large public payer, Medicare can
influence quality for all patients
• Public reporting of quality measures and
performance pay are thought to be ways
to achieve this goal
Hospital Quality Initiative
• Hospital Quality Alliance, voluntary publicprivate collaboration formed to support
public reporting of hospital quality (process
measures)
• Hospital Compare website starts collecting
and reporting performance: voluntary
reporting starts October 2003
• 2003 Medicare Modernization Act requires
hospitals to report to HC to receive full
market update in reimbursement
Hospital Compare Surgical Quality
Measures
• Infection Prevention
– Prophylactic antibiotic receipt within one hour of surgery
– Prophylactic antibiotic discontinuation within 24 hours of
surgery
– Correct antibiotic administration to prevent infection
(2006)
• Blood Clot Prevention (2006)
– Recommended venous thrombosis prophylaxis ordered
– Recommended venous thrombosis prophylaxis given
within 24 hours of surgery
Research Question
• Can public reporting of Surgical Care
Improvement Project (SCIP) measures
help patients choose high-quality
hospitals?
• Are rates of surgical process compliance
correlated with outcomes?
• Infection
• Blood Clots
• Mortality
Data
• Hospital Compare
– Average compliance and number of patients
eligible for measure
– Annual data for 2006
• Medicare MedPAR
– Discharge abstracts for Medicare FFS
hospitalizations 2006
• abdominal aortic aneurism repair, aortic valve repair,
coronary artery bypass graft, esophageal resection,
mitral valve repair, pancreatic resection
– 155,256 admissions at 2,038 hospitals
Methods
• 30-day mortality, Surgical Site Infection, Deep
Vein Thrombosis
• Hierarchical logistic regression
– Hospital level: indicators for highest SCIP compliance
quintile and lowest SCIP compliance quintile, volume
– Patient level: age, race, female, comorbid conditions
(Charlson index), patient zipcode median income
elective or emergent admission, and year of admission
– Hospital random effects are included to account for
clustering of patients in hospitals.
Process Compliance Varies Widely
Across Hospitals
Patients receiving recommended
process (%)
Mean Surgical Process Compliance, 2005-2006
100.0
80.0
60.0
40.0
20.0
0.0
Low
Medium
High
Patient Characteristics By Hospital
SCIP Compliance
Age
Female
Black
Charlson Index Score
Zip Code Income
Lowest
74.4
0.34
0.05
1.21
38,900
Medium
74.7
0.34
0.05
1.22
43,700
Highest
74.8
0.34
0.04
1.21
43,600
Little Variation in Mortality Across
Levels of Compliance
Risk-Adjusted Mortality
Rate (%)
Risk-Adjusted Surgical Mortality by Process
Compliance, 2005-2006
15
10
5
0
AAAR
AVR
Low
CABG
Medium
ESOECT
High
MVR
No Report
PANRES
Surgical Infection and Infection
Compliance
Overall
Abdominal Aortic Aneurysm Repair
Aortic Valve Repair
Coronary Artery Bypass Graft
Esophagectomy
Mitral Valve Repair
Pancreatic Resection
Highest
Lowest
Highest
Lowest
Highest
Lowest
Highest
Lowest
Highest
Lowest
Highest
Lowest
Highest
Lowest
0.99
0.81
0.91
0.96
0.83
0.76
0.96
0.77
2.15***
0.61
0.76
0.36
0.79
1.84
[0.85,1.16]
[0.64,1.02]
[0.62,1.33]
[0.55,1.67]
[0.60,1.13]
[0.45,1.30]
[0.78,1.18]
[0.57,1.04]
[1.39,3.34]
[0.18,2.00]
[0.41,1.42]
[0.09,1.48]
[0.45,1.39]
[0.74,4.58]
Post-Operative Blood Clots and
Process Compliance
Overall
Abdominal Aortic Aneurysm Repair
Aortic Valve Repair
Coronary Artery Bypass Graft
Esophagectomy
Mitral Valve Repair
Pancreatic Resection
0.97
0.89
0.89
0.71
1.1
0.92
0.93
0.93
1.16
0.67
0.85
1.21
0.94
0.85
[0.87,1.09]
[0.73,1.08]
[0.67,1.18]
[0.43,1.17]
[0.88,1.37]
[0.59,1.44]
[0.79,1.08]
[0.71,1.21]
[0.84,1.60]
[0.39,1.17]
[0.49,1.45]
[0.49,2.96]
[0.66,1.34]
[0.49,1.48]
Policy Implications
• Little evidence that SCIP measures reliably
correlate with risk-adjusted patient outcomes.
• Hospital Compare data will not help patients
identify hospitals with better outcomes for highrisk surgery
• CMS should identify higher leverage process
measures for improved public reporting and payfor-performance programs
• Consider increased use of outcomes-based
profiling
Acknowledgements
• Coauthors
John Birkmeyer
Justin Dimick
Nicholas Osborne
• Funding
National Institute on Aging