Introduction Health outcomes are increasingly compared between providers with the aim to benchmark quality of care. In such benchmarks adjusting for patient characteristics is of major importance to avoid unfair comparisons between providers. We developed a case-mix adjustment model for comparing 30-, 90-day mortality and anastomotic leakage rates after oesophagus gastric (O-G) cancer resections between NHS hospitals.
Method We reviewed the literature for existing prediction models for 30-, 90-day mortality and anastomotic leakage after oesophago-gastric cancer resections. Based on this review we selected predictors that were consequently used to develop a case-mix adjustment model in the national audit data of 4,882 O-G cancer patients undergoing surgery in the years 2012 and 2013. Models were developed with logistic regression analysis. Discriminative ability was quantified with the Area under the ROC curve and internal validity was assessed using a bootstrap procedure.
Results The risk prediction models identified in the literature were not suitable for case-mix adjustment in the NHS audit data as they required detailed laboratory data that are not available at the national level. Moreover, the majority of existing models were methodologically weak and developed based on data pooled over long periods of time during which outcomes improved considerably in the UK. In the data used for model development, 30-day mortality was 2.3%, 90-day mortality was 4.4% and 6.2% of the patients developed an anastomotic leakage. Discriminative ability in the model development dataset was 0.70, 0.69 and 0.63 for 30-day mortality, 90-day mortality and anastomotic leakage, respectively. The internally validated AUCs were well calibrated and showed moderate discriminative ability (area under ROC curve 0.65 for 30-day mortality, 0.66 for 90-day mortality, yet only 0.59 for anastomotic leakage).
Conclusion Based on nationally available data, we developed three case mix adjustment models for postoperative outcomes in the largest contemporary cohort of O-G patients undergoing curative surgery. These models should be used for the risk adjustment when assessing hospital performance in the NHS.
Disclosure of interest None Declared.