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J Safety Res ; 74: 9-15, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32951800

RESUMO

INTRODUCTION: With the significant number of motor-vehicle fatalities occurring on the nation's roadways in recent years, there exists a need to integrate a more complete range of data sources, available at a regional or statewide level, to effectively evaluate existing safety concerns and quantify their impacts. Crash data alone does not provide ample crash-associated citation, injury, and roadway characteristics; therefore, a more cohesive dataset is required to accurately and completely analyze the true impacts of motor-vehicle crashes. Previously developed strategies linked crash data with citation and roadway inventory data to enhance the identification and optimization of highway safety strategies. METHOD: The main objective of this research focused on developing a new deterministic linkage between crash and Emergency Medical Services (EMS) data, by utilizing the Massachusetts Crash Data System (CDS) and the Massachusetts Ambulance Trip Record Information System (MATRIS). RESULTS: After several iterations of match criterion, the validated linkage successfully matched 58.3% of MATRIS records (containing an Injury Cause of Motor Vehicle Crash) to a CDS person record (55011 linked pairs, between 2014 and 2016). The data linkage provided significant insight into injury trends in several highway safety emphasis areas such as roadway departure, speeding-related, and distraction-affected crashes. The findings from this research are twofold: (1) an established process for linking previously separate data sets, and (2) a mechanism for analysis that provides decision-makers and safety professionals with a better measure of crash outcomes.


Assuntos
Acidentes de Trânsito/prevenção & controle , Armazenamento e Recuperação da Informação/métodos , Veículos Automotores , Acidentes de Trânsito/estatística & dados numéricos , Serviços Médicos de Emergência/estatística & dados numéricos , Humanos , Armazenamento e Recuperação da Informação/estatística & dados numéricos , Massachusetts
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