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.
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 TBIpatients 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.
Authors: Maija Holsti; Roger Zemek; Jill Baren; Rachel M Stanley; Prashant Mahajan; Cheryl Vance; Kathleen M Brown; Victor Gonzalez; Denise King; Kammy Jacobsen; Kate Shreve; Katrina van de Bruinhorst; Anne Marie Jones; James M Chamberlain Journal: Clin Trials Date: 2014-11-04 Impact factor: 2.486
Authors: Carrie A Sims; Joshua A Isserman; Daniel Holena; Latha Mary Sundaram; Nikolai Tolstoy; Sarah Greer; Seema Sonnad; Jose Pascual; Patrick Reilly Journal: J Trauma Acute Care Surg Date: 2013-01 Impact factor: 3.313
Authors: Louisa W Whitesides; Jill M Baren; Michelle H Biros; Ross J Fleischman; Prasanthi R Govindarajan; Elizabeth B Jones; Arthur M Pancioli; Rebecca D Pentz; Victoria M Scicluna; David W Wright; Neal W Dickert Journal: Clin Trials Date: 2016-11-15 Impact factor: 2.486
Authors: Neal W Dickert; Kathleen Metz; Michael D Fetters; Adrianne N Haggins; Deneil K Harney; Candace D Speight; Robert Silbergleit Journal: Acad Emerg Med Date: 2021-05-26 Impact factor: 5.221