Background
Incomplete lung cancer resection connotes poor prognosis, the incidence varies with patient demographic, clinical, and institutional factors. We sought to develop a valid, survival-impactful facility-based surgical quality metric which adjusts for related patient demographic and clinical characteristics.
Methods
Facilities performing resections for patients diagnosed with stage I-IIIA non-small-cell lung cancer in National Cancer Data Base between 2004-2011 were identified. Multivariate logistic regression modeling was used to estimate the expected number of margin-positive cases by adjusting for patient risk-mix and calculate the observed: expected (O/E) ratio for each facility. Facilities were categorized as outperformers (O/E ratio<1, p<.05), non-outliers (p>.05), and underperformers (O/E ratio>1, p<.05); and their characteristics across performance categories were compared by chi-square tests. Multivariate Cox proportional hazard analyses were conducted, adjusting for patient demographic and clinical characteristics.
Results
A total of 96,324 patients underwent surgery at 809 facilities. The overall observed margin-positive rate was 4.4%. Sixty-one facilities (8%) were outperformers, 644(80%) were non-outliers, and 104(13%) were underperformers. One-third (36%) of National Cancer Institute-designated facilities, 13% Academic-Comprehensive-Cancer-Programs, 5% Comprehensive-Community-Cancer-Programs, and 13% ‘other’ facilities achieved outperforming status but no Community-Cancer-Programs did. Interestingly, 9% of National Cancer Institute-designated facilities and 11% of Academic-Comprehensive-Cancer-program facilities were underperformers. Adjusting for patient demographic and clinical characteristics, outperformers had a 5-year all-cause hazard ratio of 0.88 (95%CI: 0.85–0.91, p<.0001) compared to non-outliers; and 0.80 (95%CI: 0.77–0.84, p<.0001) compared to underperformers.
Conclusions
Facility performance in lung cancer surgery can be captured by the risk-adjusted margin- positivity rate, potentially providing a valid quality improvement metric.