A comprehensive analysis of undertriage in a mature trauma system using geospatial mapping. Issue 1 (July 2021)

• Record Type: Journal Article
• Authors: Maish, George; Horst, Michael; Ting Brown, Catherine; Morgan, Madison; Bradburn, Eric; Cook, Alan; Rogers, Frederick B.
• Is Part Of: Journal of trauma and acute care surgery. Volume 91:Issue 1(2021)
• Publication Date: 2021-07
• Subjects: Trauma -- undertriage -- geospatial mapping; Surgical intensive care -- Periodicals; Surgical emergencies -- Periodicals; Wounds and injuries -- Surgery -- Periodicals; 617.026
• DOI: 10.1097/TA.0000000000003113
• Languages: English
• ISSNs: 2163-0755

Abstract

Abstract : INTRODUCTION: The correct triage of trauma patients to trauma centers (TCs) is essential. We sought to determine the percentage of patients who were undertriaged within the Pennsylvania (PA) trauma system and spatially analyze areas of undertriage (UTR) in PA for all age groups: pediatric, adult, and geriatric. We hypothesized that there would be certain areas that had high UTR for all age groups. METHODS: From 2003 to 2015, all admissions from the Pennsylvania Trauma Systems Foundation registry and those meeting trauma criteria ( International Classification of Diseases, Ninth Diseases : 800–959) from the Pennsylvania Health Care Cost Containment Council (PHC4) database were included. Admissions were divided into age groups: pediatric (<15 years), adult (15–64 years), and geriatric (≥65 years). All pediatric trauma cases were included from the Pennsylvania Trauma Systems Foundation and PHC4 registry, while only cases with Injury Severity Score of >9 were included in adult and geriatric age groups. Undertriage was defined as patients not admitted to level I/II adult TCs (n = 24), pediatric (n = 3), or adult and pediatric combined facility (n = 3) divided by the total number of patients from the PHC4 database. ArcGIS Desktop (version 10.7; ESRI, Redlands, CA) and GeoDa (version 1.14.0; CSDS, Chicago, IL) open source license were used for geospatial mapping of UTR with a spatial empirical Bayesian smoothed UTR by zip code tabulation area (ZCTA) and Stata (version 16.1; Stata Corp., College Station, TX) for statistical analyses. RESULTS: There were significant percentages of UTR for all age groups. One area of high UTR for all age groups had TCs and large nontrauma centers in close proximity. There were high rates of UTR for all ages in rural areas, specifically in the upper central regions of PA, with limited access to TCs. CONCLUSION: It appears there are two patterns leading to UTR. The first is in areas where TCs are in close proximity to large competing nontrauma centers, which may lead to inappropriate triage. The second has to do with lack of access to TCs. Geospatial mapping is a valuable tool that can be used to ascertain where trauma systems should focus scarce resources to decrease UTR. LEVEL OF EVIDENCE: Epidemiological, level III; Care management, level III.