Readmission after lung cancer resection is associated with a 6-fold increase in 90-day postoperative mortality.
Academic Article
Overview
abstract
OBJECTIVES: Postoperative readmission affects patient care and healthcare costs. There is a paucity of nationwide data describing the clinical significance of readmission after thoracic operations. The purpose of this study was to evaluate the relationship between postoperative readmission and mortality after lung cancer resection. METHODS: Data were extracted for patients undergoing lung cancer resection from the linked Surveillance Epidemiology and End Results-Medicare registry (2006-2011), including demographics, comorbidities, socioeconomic factors, readmission within 30 days from discharge, and 90-day mortality. Readmitting facility and diagnoses were identified. A hierarchical regression model clustered at the hospital level identified predictors of readmission. RESULTS: We identified 11,432 patients undergoing lung cancer resection discharged alive from 677 hospitals. The median age was 74.5 years, and 52% of patients received an open lobectomy. Thirty-day readmission rate was 12.8%, and 28.3% of readmissions were to facilities that did not perform the original operation. Readmission was associated with a 6-fold increase in 90-day mortality (14.4% vs 2.5%, P<.001). The most common readmitting diagnoses were respiratory insufficiency, pneumonia, pneumothorax, and cardiac complications. Patient factors associated with readmission included resection type; age; prior induction chemoradiation; preoperative comorbidities, including congestive heart failure and chronic obstructive pulmonary disease; and low regional population density. CONCLUSIONS: Factors associated with early readmission after lung cancer resection include patient comorbidities, type of operation, and socioeconomic factors. Metrics that only report readmissions to the operative provider miss one-fourth of all cases. Readmitted patients have an increased risk of death and demand maximum attention and optimal care.
