Gender Differences in Hospital Survival Rates For Medicare Beneficiaries Undergoing

Coronary Artery Bypass Graft Surgery: Does Hospital Performance Ranking Matter

Steven D. Culler, PhDAssociate Professor Rollins School of Public Health Emory University April Simon MRNPresident Cardiac Data SolutionsAtlanta GA

• To report on gender differences in risk-adjusted mortality rates by hospital performance classes based on CABG outcomes among Medicare beneficiaries.

• To identify the number of female Medicare beneficiary deaths that could be avoided by improving outcomes in bottom tier hospitals.

Study Objectives

• Medicare Provide Analysis and Review File (MedPAR): An administrative database containing demographic information, 9 diagnostic and 6 procedure (ICD-9-CM) codes, and the discharge status of all Medicare beneficiaries admitted to any U.S. hospital.

Methods: Data Sources

•Study Period: October 1, 2002 to September 30, 2004 (Fiscal Years 2003 & 2004).

Methods: Study Period

Inclusion Criteria:

• All Medicare beneficiaries undergoing a CABG surgery (Procedure codes of 36.10-36.19 and 36.2).

Exclusion Criteria:

• Patients having any concomitant valve surgery (Procedure codes of 35.00-35.04; 35.10-35.14; 35.20-35.28; & 35.31-35.39).

• All patients in hospitals performing less than 52 surgeries per year or less than 17 surgeries on females per year.

Methods: Study Population

Methods: Study Sample

Final Study Sample FY-2003 FY-2004

Number of Hospitals 802 768

Average Hospital Volume 167±123 159±113

Number of Hospitalizations 134,407 122,231

% Male 66.5% 66.9%

Methods: Analytic Approach

• Step 1: Annual Risk-Adjusted Mortality:

A logistic regression equation (controlling for up to 25 demographic and co-morbid conditions) was estimated to predict each Medicare beneficiary’s probability of experiencing in-hospital mortality for each fiscal year.

Methods: Analytic Approach

• Step 2: Annual Hospital Performance Tiers:

Hospitals were annually ranked into quartiles based on the number of lives saved (or lost) - the difference between a hospital’s risk adjusted expected number of deaths and its observed number of deaths during the fiscal year.

Methods: Analytic Approach

• Step 3: Annual Hospital Risk-Adjusted Mortality Rate by Gender:

A male and female risk-adjusted mortality rate was calculated for each hospital for each fiscal year.

Results: Risk-Adjusted CABG Mortality

FY-2003 FY-2004

All Study Hospitals: 3.68% 3.61%

Male Rate 3.17% 3.09%

Female Rate 4.71% 4.68%

Gender Differential (M-F) -1.55% -1.59%

Results: Risk-Adjusted CABG Mortality

Overall Rates FY-2003 Hospital Performance Tier

I II III IV

Male Rate 1.24% 2.19% 3.59% 5.68%

Female Rate 1.96% 3.40% 5.11% 8.39%

Differential (M-F) -0.72% -1.21% -1.52% -2.71%

Overall Rates FY-2004

Male Rate 1.12% 2.16% 3.49% 5.52%

Female Rate 1.80% 3.31% 5.39% 8.19%

Differential (M-F) -0.68% -1.15% -1.90% -2.67%

Results: Gender Difference Between Top and Bottom Tier

Top Bottom p-Value

FY-2003:

Male Rate 1.24% 5.68% <0.001

Female Rate 1.96% 8.39% <0.001

Differential (M-F) -0.72% -2.71% <0.001

FY-2004:3

Male Rate 1.12% 5.52% <0.001

Female Rate 1.80% 8.19% <0.001

Differential (M-F) -0.68% -2.67% <0.001

Issues: Alternative Goals for Bottom Tier Hospitals

1. The females and males have the same risk-adjusted mortality rate in bottom tier hospitals;

2. The female risk-adjusted mortality rate in bottom tier hospitals improves to the average female risk-adjusted mortality rate; and

3. The female risk-adjusted mortality rate in bottom tier hospitals improves to the female risk-adjusted mortality rate in top tier hospitals.

Goal Three: Bottom Tier Equals Top Tiers

Bottom Tier Females FY-2003 FY-2004 Both Years

Female Hospitalizations 12,215 11,100 23,325

Expected Female Deaths (Current Practice)

1,025 909 1,934

Goal: Female RA-Mortality rate the same in both tiers

Expected Deaths 151 133 284

Expected Deaths Avoided 874 776 1,650

Percent Deaths Avoided 85.3% 85.4% 85.3%

• Female Medicare beneficiaries had significantly higher risk-adjusted hospital mortality rates than males.

• As one moves from the top quartile to the bottom quartile, the gender disparity in the risk-adjusted mortality rate increases.

Summary:

• Improvement Goal:

85.3% of expected female beneficiaries deaths could be avoided if bottom tier hospitals achieved the same risk-adjusted outcomes as top tier CABG hospitals.

Summary:

Limitations:

• Risk-adjusted models are based on co-morbid conditions identified from ICD-9-CM codes reported in an administrative dataset.

• Gender differences for Medicare beneficiaries may not reflect gender differences for CABG surgery among younger patients.

Female Medicare beneficiaries should be much more selective in choosing where to have their CABG surgery performed!

Conclusion

The End

Goal One: No Gender Difference in Bottom Tier Hospitals

Bottom Tier Females FY-2003 FY-2004 Both Years

Female Hospitalizations 12,215 11,100 23,325

Expected Female Deaths (Current Practice)

1,025 909 1,934

Goal: No Gender Difference in Rates in Bottom Tier

Expected Deaths 693 613 1,306

Expected Deaths Avoided 332 296 628

Percent Deaths Avoided 32.4% 32.6% 32.5%

Goal Two: Bottom Tier Hospitals Improve to the Average Female Rate

Bottom Tier Females FY-2003 FY-2004 Both Years

Female Hospitalizations 12,215 11,100 23,325

Expected Female Deaths(Current Practice)

1,025 909 1,934

Goal: Female Rate in Bottom Tier Improves to Average

Expected Deaths 575 519 1,094

Expected Deaths Avoided 450 390 840

Percent Deaths Avoided 43.9% 42.9% 43.4%

Methods: Analytic Approach

Risk-Adjustment: Demographic Variables:

Variables Answer

Age Group Age 65 to 69, Age 70 to 74,Age 75 to 79, and Age 80 or greater

Gender Male or Female

Race White or Non-white

Methods: Analytic Approach

Risk-Adjustment: History of Prior Procedures or Conditions:

Variables Answer

History of Prior CABG Yes or No

History of Prior PCI Yes or No

History of Prior MI Yes or No

History of Hemodialysis

Yes or No

Methods: Analytic Approach

Risk-Adjustment – Co-Morbid Conditions:

Variables Answer

Obesity Yes or No

Diabetes Yes or No

Chronic Obstructive Pulmonary Disease

Yes or No

Current Smoker Yes or No

Chronic Renal Failure Yes or No

Chronic Liver Disorder Yes or No

Hypertension Yes or No

Heart Failure Yes or No

Cardiogenic Shock Yes or No

Aortic Aneurysm Yes or No

Methods: Analytic Approach

Risk-Adjustment: Co-Morbid Conditions

Variables AnswerAtrial Fibrillation Yes or No

Ventricular Fibrillation Yes or No

Cardiac Arrest Yes or No

Type of Primary Acute MI STEMI NSTEMI