Using a National Burn Registry to Develop a Model for Risk-Adjusted Length of Stay Benchmarking

Abstract

Length of stay (LOS) is a frequently reported outcome after a burn injury. LOS benchmarking will benefit individual burn centers as a way to measure their performance and set expectations for patients. We sought to create a nationwide, risk-adjusted model to allow for LOS benchmarking based on the data from a national burn registry. Using data from the American Burn Association's Burn Care Quality Platform, we queried admissions from 7/2015 to 6/2020 and identified 130,729 records reported by 103 centers. Using 22 predictor variables, comparisons of unpenalized linear regression and Gradient boosted (CatBoost) regressor models were performed by measuring the R2 and concordance correlation coefficient on the application of the model to the test dataset. The CatBoost model applied to the bootstrapped versions of the entire dataset was used to calculate O/E ratios for individual burn centers. Analyses were run on 3 cohorts: all patients, 10-20% TBSA, >20% TBSA. The CatBoost model outperformed the linear regression model with a test R2 of 0.67 and CCC of 0.81 compared with the linear model with R2=0.50, CCC=0.68. The CatBoost was also less biased for higher and lower LOS durations. Gradient-boosted regression models provided greater model performance than traditional regression analysis. Using national burn data, we can predict LOS across contributing burn centers while accounting for patient and center characteristics, producing more meaningful O/E ratios. These models provide a risk-adjusted LOS benchmarking using a robust data source, the first of its kind, for burn centers.