Variability in length of stay after uncomplicated pulmonary lobectomy: is length of stay a quality metric or a patient metric?†.

ABSTRACT

OBJECTIVES: Previous studies have identified predictors of prolonged length of stay (LOS) following pulmonary lobectomy. LOS is typically described to have a direct relationship to postoperative complications. We sought to determine the LOS and factors associated with variability after uncomplicated pulmonary lobectomy. METHODS: Analysing the State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality database, we reviewed lobectomies performed (2009-11) on patients in California, Florida and New York. LOS and comorbidities were identified. Multivariable regression analysis (MVA) was used to determine factors associated with LOS greater than the median. Patients with postoperative complications or death were excluded. RESULTS: Among 22 647 lobectomies performed, we identified 13 099 patients (58%) with uncomplicated postoperative courses (mean age = 66 years; 56% female; 76% white, 57% Medicare; median DEYO comorbidity score = 3, 55% thoracotomy, 45% thoracoscopy/robotic). There was a wide distribution in LOS [median LOS = 5 days; interquartile range (IQR) 4-7]. By MVA, predictors of prolonged LOS included, age ≥ 75 years [odds ratio (OR) 1.7, 95% confidence interval (CI) 1.4-2.0], male gender (OR 1.2, 95% CI 1.1-1.2), chronic obstructive pulmonary disease (OR 1.6, 95% CI 1.5-1.7) and other comorbidities, Medicaid payer (OR 1.7, 95% CI 1.4-2.1) versus private insurance, thoracotomy (OR 3.0, 95% CI 2.8-3.3) versus video-assisted thoracoscopic surgery/robotic approach and low hospital volume (OR 2.4, 95% CI 2.1-2.6). CONCLUSIONS: Variability exists in LOS following even uncomplicated pulmonary lobectomy. Variability is driven by clinical factors such as age, gender, payer and comorbidities, but also by surgical approach and volume. All of these factors should be taken into account when designing clinical care pathways or when allocating payment resources. Attempts to define an optimal LOS depend heavily upon the patient population studied.