Evidence‐based Community Consultation for Traumatic Brain Injury

• Published in: Academic emergency medicine Vol. 18; no. 9; pp. 972 - 976
• Main Authors: Lynch, Catherine A., Houry, Debra E., Dai, Dajun, Wright, David W.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.09.2011; Wiley Subscription Services, Inc
• Subjects: Adult; Aged; Brain damage; Brain Injuries - classification; Brain Injuries - epidemiology; Clinical trials; Clinical Trials as Topic; Cluster analysis; Disclosure; Emergency medical care; Emergency Medicine - ethics; Evidence-Based Emergency Medicine; Female; Geographic Information Systems; Head Injuries, Closed - classification; Head Injuries, Closed - epidemiology; Humans; Incidence; Informed Consent; Male; Middle Aged; Referral and Consultation; Registries; Residence Characteristics; Retrospective Studies; Trauma Severity Indices; Young Adult
• ISSN: 1069-6563; 1553-2712
• DOI: 10.1111/j.1553-2712.2011.01153.x

ACADEMIC EMERGENCY MEDICINE 2011; 18:972–976 © 2011 by the Society for Academic Emergency Medicine Objectives:  The objective was to determine if geospatial techniques can be used to inform targeted community consultation (CC) and public disclosure (PD) for a clinical trial requiring emergency exception from informed consent (EFIC). Methods:  Data from January 2007 to December 2009 were extracted from a Level I trauma center’s trauma database using the National Trauma Registry of the American College of Surgeon (NTRACS). Injury details, demographics, geographic codes, and clinical data necessary to match core elements of the clinical trial inclusion criteria (Glasgow Coma Scale [GCS] 3–12 and blunt head injury) were collected on all patients. Patients’ home zip codes were geocoded to compare with population density and clustering analysis. Results:  Over a 2‐year period, 179 patients presented with moderate to severe traumatic brain injury (TBI). Mapping the rate and frequency of TBI patients presenting to the trauma center delineated at‐risk populations for moderate to severe head injury. Four zip codes had higher incidences of TBI than the rest, with one zip code having a very high rate of 80 per 100,000 population. Conclusions:  Geospatial techniques and hospital data records can be used to characterize potential subjects and delineate a high‐risk population to inform directed CC and public disclosure strategies.