Bariatric Surgery: Outcomes and Safety MISS 2010 Bruce M. Wolfe, MD Professor of Surgery Oregon Health & Science University

Iezzoni’s “Algebra of Effectiveness” Patient Factors + Effectiveness of Care + Random Events = Outcome Lezzoni. Ann Thorac Surg 1994;58:1822 2

Goals of Databases Define volume of care Determine outcomes Basis for determination of expected outcomes or ratio of actual/expected outcomes Risk adjustment 3

Uses of Databases Self Assessment Quality Assurance Credentialing/Certification Patient Information Promotion Research 4

Types of Databases Administrative – Based on claims data – Coding by administrative personnel Clinical – Data collected by clinical personnel 5

Administrative Database Discharge abstract data Population based 6

Administrative Database Advantages – Completeness of data – Available – Low cost to acquire 7 Disadvantages – Coding imperfect – Done by administrative personnel – Inpatient only – Not procedure or disease specific – Needed data not present

Examples of Administrative Databases Medicare national claims history Nationwide Inpatient Sample (NIS) University Healthsystem Consortium (UHC) Patient discharge database (states) 8

Charlson Comorbidity Index JAMA October Flum 94%6%0.5%0.1% Santry Zingmond

Society of Thoracic Surgeons Database (STS) Variations of outcomes in cardiac surgery Hospital/surgeon volume an important factor 10

Society of Thoracic Surgeons Database (STS) Prospective clinical data Multiple parameters – Possible risk factors – Outcomes Voluntary, self-reported Agree to audit 11

Society of Thoracic Surgeons Database (STS) 1989 – Data collection begun Present > 2 million cases 12

Compare STS with Administrative Database CABG Source of Data Risk- Adjusting Algorithm Reported Volume In-Hospital Mortality Rate Predicted Mortality Risk- Adjusted Rate STS Database STS MedicareNone4234.7N/A 13 Mack. J Thoracic Cardiovascular Surgery 2005;129:1309

Reasons for Data Variation Medicare not primary payer Coding problems Variations of definitions No risk adjustment 14

STS Controversies Low numbers at a site limit identification of variance from expected outcomes Volume-outcomes relationship is inconsistent Factors involved include: – High volume team at low volume center – Past experience – Process of care 15

Bariatric Surgery Databases Single institution reports Multiple institution reports Meta-analysis LABS: NIH multicenter consortium BOLD: ASMBS/SRC Bariatric NSQIP: ACS 16

Obesity Surgery Mortality Risk Score BMI > 50kg/m² Male Hypertension DVT/PE risk Age ≥ 45y DeMaria: SOARD 2007;3:

Obesity Surgery Mortality Risk Score 1 point for each risk factor: 0-1A : Lowest risk 2-3B : Intermediate risk 4-5C : Highest Risk DeMaria: SOARD 2007;3:

Obesity Surgery Mortality Risk Score: Validation 4 centers, 4431 patients DeMaria: Ann Surg 2007;246: ClassMortality A0.2% B1.1% C2.4% All0.7%

Development of Bariatric Surgery-Specific Risk Assessment Tool Databases: National Hospital Discharge Summary AHRQ/NIS 25,000+ bariatric surgery cases 20Livingston: SOARD 2007;3:14-20

Correlated with Adverse Event Chronic Pulmonary Disease Hypertension Diabetes Complications Deficiency Anemia Depression Age Male 21