Linked data systems for injury surveillance and targeted prevention planning: Identifying geographical differences in injury in Western Australia, 2009‐2012. (12th January 2018)

• Record Type: Journal Article
• Authors: Lyle, Greg; Hendrie, Delia; Miller, Ted R.; Randall, Sean; Davison, Erica
• Is Part Of: Health promotion journal of Australia. Volume 29:Number 2(2018)
• Page Start: 208
• Page End: 219
• Publication Date: 2018-01-12
• Subjects: Evidence‐based practice -- injury -- public policy; Health promotion -- Periodicals; Health promotion -- Australia -- Periodicals; 613.0994
• DOI: 10.1002/hpja.26
• Languages: English
• ISSNs: 1036-1073

Abstract

Abstract: Issue addressed: Injuries are a leading preventable cause of disease burden in Australia. Understanding how injuries vary by geographical location is important to guide health promotion planning. Therefore, the geographical and temporal distribution of injury across Western Australia from 2009 to 2012 is explored. Methods: Three Western Australian health datasets were linked and the expected number of injury cases per postcode calculated. A Standardised Injury Ratio was calculated by comparing the observed and expected number of injury cases. Priority areas and associated injury mechanisms were identified by postcode based on injury rates and temporal trends. Results: Injury levels varied across health region, health district and postcode. All nonmetropolitan regions had at least one health district classified as High or Medium‐High priority. In contrast, neither metropolitan health region had health districts in these categories. Adopting the finer postcode level of analysis showed localised injury priority areas, even within health districts not classified as High or Medium‐High injury areas. Postcodes classified as High or Medium‐High injury priority were located alongside those with lower priority categories. Conclusion: Injury prevention priority areas had consistent trends both geographically and over time. Finer scale analysis can provide public health policy makers with more robust information to plan, evaluate and support a range of injury prevention programs. So what?: The use of linked data systems and spatial analysis can assist health promotion decision‐makers and practitioners by demonstrating area‐based differences in injury prevention allowing effective targeting of limited resources to populations at the highest risk of injury.