Volume 49 | Number 4 | August 2014

Abstract List

Mario Schootman, Min Lian, Sandi L. Pruitt, Anjali D. Deshpande, Samantha Hendren, Matthew Mutch, Donna B. Jeffe, Nicholas Davidson


To assess hospital and geographic variability in 30‐day mortality after surgery for and examine the extent to which sociodemographic, area‐level, clinical, tumor, treatment, and hospital characteristics were associated with increased likelihood of 30‐day mortality in a population‐based sample of older patients.

Data Sources/Study Setting

Linked Surveillance Epidemiology End Results () and Medicare data from 47,459 patients aged 66 years or older who underwent surgical resection between 2000 and 2005, resided in 13,182 census tracts, and were treated in 1,447 hospitals.

Study Design

An observational study using multilevel logistic regression to identify hospital‐ and patient‐level predictors of and variability in 30‐day mortality.

Data Collection/Extraction Methods

We extracted sociodemographic, clinical, tumor, treatment, hospital, and geographic characteristics from Medicare claims, , and census data.

Principal Findings

Of 47,459 patients, 6.6 percent died within 30 days following surgery. Adjusted variability in 30‐day mortality existed across residential census tracts (predicted mortality range: 2.7–12.3 percent) and hospitals (predicted mortality range: 2.5–10.5 percent). Higher risk of death within 30 days was observed for patients age 85+ (12.7 percent), census‐tract poverty rate >20 percent (8.0 percent), two or more comorbid conditions (8.8 percent), stage at diagnosis (15.1 percent), undifferentiated tumors (11.6 percent), and emergency surgery (12.8 percent).


Substantial, but similar variability was observed across census tracts and hospitals in 30‐day mortality following surgery for in patients 66 years and older. Risk of 30‐day mortality is driven not only by patient and hospital characteristics but also by larger social and economic factors that characterize geographic areas.