Gavin Tansley1, Nadine Schuurman2, Mete Erdogan3, Matthew Bowes4, Robert Green5, Mark Asbridge6, Natalie Yanchar1. 1. *Department of Surgery,Dalhousie University,Halifax,NS. 2. †Department of Geography,Simon Fraser University,Burnaby,BC. 3. ‡Trauma Nova Scotia,Halifax,NS. 4. §Nova Scotia Medical Examiner Service,Dartmouth,NS. 5. ¶Department of Critical Care Medicine,Dalhousie University,Halifax,NS. 6. ††Department of Community Health and Epidemiology,Dalhousie University,Halifax,NS.
Abstract
OBJECTIVES: Trauma systems have been widely implemented across Canada, but access to trauma care remains a challenge for much of the population. This study aims to develop and validate a model to quantify the accessibility of definitive care within one provincial trauma system and identify populations with poor access to trauma care. METHODS: A geographic information system (GIS) was used to generate models of pre-scene and post-scene intervals, respectively. Models were validated using a population-based trauma registry containing data on prehospital time intervals and injury locations for Nova Scotia (NS). Validated models were then applied to describe the population-level accessibility of trauma care for the NS population as well as a cohort of patients injured in motor vehicle collisions (MVCs). RESULTS: Predicted post-scene intervals were found to be highly correlated with documented post-scene intervals (β 1.05, p<0.001). Using the model, it was found that 88.1% and 42.7% of the population had access to Level III and Level I trauma care within 60 minutes of prehospital time from their residence, respectively. Access for victims of MVCs was lower, with 84.3% and 29.7% of the cohort having access to Level III and Level I trauma care within 60 minutes of the location of injury, respectively. CONCLUSION: GIS models can be used to identify populations with poor access to care and inform service planning in Canada. Although only 43% of the provincial population has access to Level I care within 60 minutes, the majority of the population of NS has access to Level III trauma care.
OBJECTIVES: Trauma systems have been widely implemented across Canada, but access to trauma care remains a challenge for much of the population. This study aims to develop and validate a model to quantify the accessibility of definitive care within one provincial trauma system and identify populations with poor access to trauma care. METHODS: A geographic information system (GIS) was used to generate models of pre-scene and post-scene intervals, respectively. Models were validated using a population-based trauma registry containing data on prehospital time intervals and injury locations for Nova Scotia (NS). Validated models were then applied to describe the population-level accessibility of trauma care for the NS population as well as a cohort of patients injured in motor vehicle collisions (MVCs). RESULTS: Predicted post-scene intervals were found to be highly correlated with documented post-scene intervals (β 1.05, p<0.001). Using the model, it was found that 88.1% and 42.7% of the population had access to Level III and Level I trauma care within 60 minutes of prehospital time from their residence, respectively. Access for victims of MVCs was lower, with 84.3% and 29.7% of the cohort having access to Level III and Level I trauma care within 60 minutes of the location of injury, respectively. CONCLUSION: GIS models can be used to identify populations with poor access to care and inform service planning in Canada. Although only 43% of the provincial population has access to Level I care within 60 minutes, the majority of the population of NS has access to Level III trauma care.
Entities:
Keywords:
GIS; Geographic Information Systems; access; trauma
Authors: Gavin Tansley; Nadine Schuurman; Matthew Bowes; Mete Erdogan; Robert Green; Mark Asbridge; Natalie Yanchar Journal: Can J Surg Date: 2019-04-01 Impact factor: 2.089
Authors: Gregory C Knapp; Gavin Tansley; Olalekan Olasehinde; Funmilola Wuraola; Adewale Adisa; Olukayode Arowolo; M O Olawole; Anya M Romanoff; May Lynn Quan; Antoine Bouchard-Fortier; Olusegun I Alatise; T Peter Kingham Journal: Cancer Date: 2020-12-28 Impact factor: 6.860