RESUMEN
BACKGROUND: Proper triage of critically injured trauma patients to accredited trauma centers (TCs) is essential for survival and patient outcomes. We sought to determine the percentage of patients meeting trauma criteria who received care at non-TCs (NTCs) within the statewide trauma system that exists in the state of Pennsylvania. We hypothesized that a substantial proportion of the trauma population would be undertriaged to NTCs with undertriage rates (UTR) decreasing with increasing severity of injury. METHODS: All adult (age ≥15) hospital admissions meeting trauma criteria (ICD-9, 800-959; Injury Severity Score [ISS], > 9 or > 15) from 2003 to 2015 were extracted from the Pennsylvania Health Care Cost Containment Council (PHC4) database, and compared with the corresponding trauma population within the Pennsylvania Trauma Systems Foundation (PTSF) registry. PHC4 contains all hospital admissions within PA while PTSF collects data on all trauma cases managed at designated TCs (Level I-IV). The percentage of patients meeting trauma criteria who are undertriaged to NTCs was determined and Network Analyst Location-Allocation function in ArcGIS Desktop was used to generate geospatial representations of undertriage based on ISSs throughout the state. RESULTS: For ISS > 9, 173,022 cases were identified from 2003 to 2015 in PTSF, while 255,263 cases meeting trauma criteria were found in the PHC4 database over the same timeframe suggesting UTR of 32.2%. For ISS > 15, UTR was determined to be 33.6%. Visual geospatial analysis suggests regions with limited access to TCs comprise the highest proportion of undertriaged trauma patients. CONCLUSION: Despite the existence of a statewide trauma framework for over 30 years, approximately, a third of severely injured trauma patients are managed at hospitals outside of the trauma system in PA. Intelligent trauma system design should include an objective process like geospatial mapping rather than the current system which is driven by competitive models of financial and health care system imperatives. LEVEL OF EVIDENCE: Epidemiological study, level III; Therapeutic, level IV.
Asunto(s)
Servicio de Urgencia en Hospital/estadística & datos numéricos , Sistema de Registros , Centros Traumatológicos/estadística & datos numéricos , Triaje/organización & administración , Heridas y Lesiones/diagnóstico , Adolescente , Adulto , Factores de Edad , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Incidencia , Puntaje de Gravedad del Traumatismo , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Estados Unidos/epidemiología , Heridas y Lesiones/epidemiología , Adulto JovenRESUMEN
BACKGROUND: The care of patients at individual trauma centers (TCs) has been carefully optimized, but not the placement of TCs within the trauma systems. We sought to objectively determine the optimal placement of trauma centers in Pennsylvania using geospatial mapping. METHODS: We used the Pennsylvania Trauma Systems Foundation (PTSF) and Pennsylvania Health Care Cost Containment Council (PHC4) registries for adult (age ≥15) trauma between 2003 and 2015 (n = 377,540 and n = 255,263). TCs and zip codes outside of PA were included to account for edge effects with trauma cases aggregated to the Zip Code Tabulation Area centroid of residence. Model assumptions included no previous TCs (clean slate); travel time intervals of 45, 60, 90, and 120 minutes; TC capacity based on trauma cases per bed size; and candidate hospitals ≥200 beds. We used Network Analyst Location-Allocation function in ArcGIS Desktop to generate models optimally placing 1 to 27 TCs (27 current PA TCs) and assessed model outcomes. RESULTS: At a travel time of 60 minutes and 27 sites, optimally placed models for PTSF and PHC4 covered 95.6% and 96.8% of trauma cases in comparison with the existing network reaching 92.3% or 90.6% of trauma cases based on PTSF or PHC4 inclusion. When controlled for existing coverage, the optimal numbers of TCs for PTSF and PHC4 were determined to be 22 and 16, respectively. CONCLUSIONS: The clean slate model clearly demonstrates that the optimal trauma system for the state of Pennsylvania differs significantly from the existing system. Geospatial mapping should be considered as a tool for informed decision-making when organizing a statewide trauma system. LEVEL OF EVIDENCE: Epidemiological study/Care management, level III.