Descriptive framework of injury data: a proposal based on a Japanese experience of injury database integration

Kun Zhang, Jinxing Wang, Takabumi Fukuda and Yoshiki Mikami

Journal of Risk Research, 2017, vol. 20, issue 1, 85-98

Abstract: This article proposes a descriptive framework for the comprehensive analysis of injury data on the basis of a Japanese experience of injury database integration during recent years. The framework combines two conceptual models of injury: an epidemiological model set forth in the World Health Organization’s Injury Surveillance Guidelines and a technical model presented in the safety-related standards of the International Organization for Standardization and International Labour Organization. The epidemiological framework composed of host, agent, vector and environment is useful for better understanding social risks in a complex society. However, injuries to consumers caused by various types of hazards are technical, microscopic processes, and their proper description requires a detailed technical framework and appropriate vocabulary, including lists of hazards, classification of products and mechanisms of injury. The proposed descriptive framework is therefore composed of five elements (host, vector, agent, environment and consequences), 30 attributes (three of which are in the Remarks section), and a set of vocabularies for the description of these attributes. The proposed framework will be useful in the data mining work needed for injury prevention at the social and technical levels. While international consensus exists for the descriptive frameworks of mortality statistics and occupational health and safety statistics, no such unanimity exists for product injury data. The proposed framework is designed to fill this gap. Although our proposal is based on Japanese experiences, the use of internationally recognized classifications and vocabularies makes the framework a worthy candidate for the integration of injury data in other countries.

Date: 2017
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DOI: 10.1080/13669877.2015.1042497

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