Injury-specific variables improve risk adjustment and hospital quality assessment in severe traumatic brain injury

摘要: BACKGROUNDHospital benchmarking is essential to quality improvement, but its usefulness depends on the ability of statistical models to adequately control for inter-hospital differences in patient mix. We explored whether the addition of injury-specific clinical variables to the current American College of Surgeons-Trauma Quality Improvement Program (TQIP) algorithm would improve model fit.METHODSWe analyzed a prospective registry containing all adult patients who presented to a regional consortium of 14 trauma centers between 2010 and 2011 with severe traumatic brain injury (TBI). We used hierarchical logistic regression and stepwise forward selection to develop two novel risk-adjustment models. We then tested our novel models against the current TQIP model and ranked hospitals by their risk-adjusted mortality rates under each model to determine how model selection affects quality benchmarking …