A quantitative method for cost reimbursement and length of stay quality assurance in multiple trauma patients

To develop a statistically valid method for trauma reimbursement and quality assurance (QA) length-of-stay filters. This is needed because diagnosis related group (DRG)-based trauma payment systems assume a random sampling of injury severities from a normally distributed population and thus result in economic disincentives to level I trauma centers.

142 trauma patients with MVC blunt multisystem injuries (MSI) (ISS > or = 16) were studied concurrently during their hospital course.

Level I regional trauma center.

Outcome measures were (dependent variables) length of stay (LOS) and state-approved hospital charges (COST).

Mean acute care COST was $74,310, but the distribution of COST was log normal, rather than Gaussian normal as assumed by DRGs. The LOS for MSI was more than twice the average for all trauma (22 vs. 9 days), reflecting skewed severities of level I patients and was related to COST (r2 = 0.802; p < 0.0001). The ISS alone was a weak determinant of COST or LOS (r2 = 0.05; p < 0.0001). The best single determinant of COST and LOS was survival (r2 = 0.15; p < 0.0001): as it increased, it increased LOS. The most costly injuries (all p < 0.0001) involved the lower extremity (LE) or hip joint (HIP), whereas sepsis and pulmonary and surgical complications constituted the most costly complications (all p < 0.0001). Regression models that accounted for the log-normal distribution of the dependent variable and based on binary variables for survival, LE and HIP injuries, and the complications of sepsis, ARDS, pulmonary failure, MOFS, plus ISS, explained nearly two thirds of the variability in COST (r2 = 0.621; p < 0.0001) or LOS (r2 = 0.687; p < 0.0001) and the residuals were normally distributed.

These models provide a valid method of reimbursement for MSI trauma for level I trauma centers, since the data imply that good care associated with survival from specific complications of MSI are the major determinants of COST, rather than the specific type of injury or the resultant ISS. Moreover, using survival and ISS plus the disease-related complications as determinants of LOS, this method can be applied to any U.S. region since local factors can be used to adjust hospital COST as a highly correlated function of LOS. This method also permits identification of LOS outliers for QA, taking into account the influence of injury complications.