Evaluating the specificity of community injury hospitalization data over time
Data(s) |
2016
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Resumo |
This study identified the areas of poor specificity in national injury hospitalization data and the areas of improvement and deterioration in specificity over time. A descriptive analysis of ten years of national hospital discharge data for Australia from July 2002-June 2012 was performed. Proportions and percentage change of defined/undefined codes over time was examined. At the intent block level, accidents and assault were the most poorly defined with over 11% undefined in each block. The mechanism blocks for accidents showed a significant deterioration in specificity over time with up to 20% more undefined codes in some mechanisms. Place and activity were poorly defined at the broad block level (43% and 72% undefined respectively). Private hospitals and hospitals in very remote locations recorded the highest proportion of undefined codes. Those aged over 60 years and females had the higher proportion of undefined code usage. This study has identified significant, and worsening, deficiencies in the specificity of coded injury data in several areas. Focal attention is needed to improve the quality of injury data, especially on those identified in this study, to provide the evidence base needed to address the significant burden of injury in the Australian community. |
Formato |
application/pdf |
Identificador | |
Publicador |
MDPI AG |
Relação |
http://eprints.qut.edu.au/93424/4/93424.pdf http://www.mdpi.com/2313-576X/2/1/6/pdf DOI:10.3390/safety2010006 Vallmuur, Kirsten & Watson, Angela (2016) Evaluating the specificity of community injury hospitalization data over time. Safety, 2(1), Article Number:-6. |
Direitos |
2016 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
Fonte |
Centre for Accident Research & Road Safety - Qld (CARRS-Q); Faculty of Health; Institute of Health and Biomedical Innovation; School of Psychology & Counselling |
Palavras-Chave | #111711 Health Information Systems (incl. Surveillance) #injury surveillance #International Classification of Disease #morbidity data #data quality |
Tipo |
Journal Article |