DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192

Traffic accidents produce high morbidity and mortality in several countries, including Brazil. The initial care to victims of accidents, by a specialized team, has tools for evaluating the severity of trauma, which guide the priorities. This study aimed to develop a decision model applied to pre...

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Main Authors: Rackynelly Alves Sarmento Soares, Ana Paula de Jesus Tomé Pereira, Ronei Marcos de Moraes, Rodrigo Pinheiro de Toledo Vianna
Format: Article
Language:Portuguese
Published: Universidade Estadual do Sudoeste da Bahia 2012-08-01
Series:Revista Saúde.com
Subjects:
Online Access:http://www.uesb.br/revista/rsc/ojs/index.php/rsc/article/view/180/215
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spelling doaj-e30a2344fc0d4179b567f0bea3f15b712020-11-24T23:08:00ZporUniversidade Estadual do Sudoeste da BahiaRevista Saúde.com1809-07611809-07612012-08-0192216DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192Rackynelly Alves Sarmento Soares0Ana Paula de Jesus Tomé Pereira1Ronei Marcos de Moraes2Rodrigo Pinheiro de Toledo Vianna3Universidade Federal da Paraíba - UFPBUniversidade Federal da Paraíba - UFPBUniversidade Federal da Paraíba - UFPBUniversidade Federal da Paraíba - UFPBTraffic accidents produce high morbidity and mortality in several countries, including Brazil. The initial care to victims of accidents, by a specialized team, has tools for evaluating the severity of trauma, which guide the priorities. This study aimed to develop a decision model applied to pre-hospital care, using the Abbreviated Injury Scale, to define the severity of the injury caused by the AT, as well to describe the features of accidents and their victims, occurred in Joao Pessoa, Paraiba. This is a descriptive epidemiological investigation, sectional, which analyzed all victims of traffic accidents attended by the SAMU 192, João Pessoa-PB, in January, April and June 2010. Data were collected in the medical regulation sheets of SAMU 192. Most of victims were male (76%), aged between 20 and 39 years (60%). Most injuries were classified as AIS1 (62.5%). The model of decision support implemented was Suporte a vitimas de acidente de trânsito atendidas pelo SAMU 192 the decision tree that managed to correctly classify 95.98% of the severity of injuries. By this model, it was possible to extract 29 rules of gravity classification of injury, which may be used for decisionmaking teams of the SAMU 192. http://www.uesb.br/revista/rsc/ojs/index.php/rsc/article/view/180/215Traffic accidentsclassificationabbreviated injury scaleDecision Support Techniquesdecision trees
collection DOAJ
language Portuguese
format Article
sources DOAJ
author Rackynelly Alves Sarmento Soares
Ana Paula de Jesus Tomé Pereira
Ronei Marcos de Moraes
Rodrigo Pinheiro de Toledo Vianna
spellingShingle Rackynelly Alves Sarmento Soares
Ana Paula de Jesus Tomé Pereira
Ronei Marcos de Moraes
Rodrigo Pinheiro de Toledo Vianna
DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
Revista Saúde.com
Traffic accidents
classification
abbreviated injury scale
Decision Support Techniques
decision trees
author_facet Rackynelly Alves Sarmento Soares
Ana Paula de Jesus Tomé Pereira
Ronei Marcos de Moraes
Rodrigo Pinheiro de Toledo Vianna
author_sort Rackynelly Alves Sarmento Soares
title DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
title_short DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
title_full DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
title_fullStr DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
title_full_unstemmed DECISION MODEL SUPPORT OF SEVERITY OF INJURY TRAFFIC ACCIDENT VICTIMS CARE BY SAMU 192
title_sort decision model support of severity of injury traffic accident victims care by samu 192
publisher Universidade Estadual do Sudoeste da Bahia
series Revista Saúde.com
issn 1809-0761
1809-0761
publishDate 2012-08-01
description Traffic accidents produce high morbidity and mortality in several countries, including Brazil. The initial care to victims of accidents, by a specialized team, has tools for evaluating the severity of trauma, which guide the priorities. This study aimed to develop a decision model applied to pre-hospital care, using the Abbreviated Injury Scale, to define the severity of the injury caused by the AT, as well to describe the features of accidents and their victims, occurred in Joao Pessoa, Paraiba. This is a descriptive epidemiological investigation, sectional, which analyzed all victims of traffic accidents attended by the SAMU 192, João Pessoa-PB, in January, April and June 2010. Data were collected in the medical regulation sheets of SAMU 192. Most of victims were male (76%), aged between 20 and 39 years (60%). Most injuries were classified as AIS1 (62.5%). The model of decision support implemented was Suporte a vitimas de acidente de trânsito atendidas pelo SAMU 192 the decision tree that managed to correctly classify 95.98% of the severity of injuries. By this model, it was possible to extract 29 rules of gravity classification of injury, which may be used for decisionmaking teams of the SAMU 192.
topic Traffic accidents
classification
abbreviated injury scale
Decision Support Techniques
decision trees
url http://www.uesb.br/revista/rsc/ojs/index.php/rsc/article/view/180/215
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