Performance-Based Assessment of Trauma Systems: Estimates for the State of Ohio.

OBJECTIVES: There are no widely accepted metrics to determine the optimal number and geographic distribution of trauma centers (TCs). We propose a Performance-based Assessment of Trauma System (PBATS) model to optimize the number and distribution of TCs in a region using key performance metrics. METHODS: The proposed PBATS approach relies on well-established mathematical programming approach to minimize the number of level I (LI) and level II (LII) TCs required in a region, constrained by prespecified system-related under-triage (srUT) and over-triage (srOT) rates and TC volume. To illustrate PBATS, we collected 6002 matched (linked) records from the 2012 Ohio Trauma and EMS registries. The PBATS-suggested network was compared to the 2012 Ohio network and also to the configuration proposed by the Needs-Based Assessment of Trauma System (NBATS) tool. RESULTS: For this data, PBATS suggested 14 LI/II TCs with a slightly different geographic distribution compared to the 2012 network with 21 LI and LII TC, for the same srUT≈.2 and srOT≈.52. To achieve UT ≤ .05, PBATS suggested 23 LI/II TCs with a significantly different distribution. The NBATS suggested fewer TCs (12 LI/II) than the Ohio 2012 network. CONCLUSION: The PBATS approach can generate a geographically optimized network of TCs to achieve prespecified performance characteristics such as srUT rate, srOT rate, and TC volume. Such a solution may provide a useful data-driven standard, which can be used to drive incremental system changes and guide policy decisions.

Locating trauma centers considering patient safety.

Trauma continues to be the leading cause of death and disability in the U.S. for those under the age of 44, making it a prominent public health problem. Recent literature suggests that geographical maldistribution of Trauma Centers (TCs), and the resultant increase of the access time to the nearest TC, could impact patient safety and increase disability or mortality. To address this issue, we introduce the Trauma Center Location Problem (TCLP) that determines the optimal number and location of TCs in order to improve patient safety. We model patient safety through a surrogate measure of mistriages, which refers to a mismatch in the injury severity of a trauma patient and the destination hospital. Our proposed bi-objective optimization model directly accounts for the two types of mistriages, system-related under-triage (srUT) and over-triage (srOT), both of which are estimated using a notional tasking algorithm. We propose a heuristic based on the Particle Swarm Optimization framework to efficiently derive a near-optimal solution to the TCLP for realistic problem sizes. Based on 2012 data from the state of Ohio, we observe that the solutions are sensitive to the choice of weights for srUT and srOT, volume requirements at a TC, and the two thresholds used to mimic EMS decisions. Using our approach to optimize that network resulted in over 31.5% reduction in the objective with only 1 additional TC; redistribution of the existing 21 TCs led to 30.4% reduction.