A Comparison of State and National Australian Data on External Cause of Injury Due to Falls. Issue 3 (October 2013)

• Record Type: Journal Article
• Authors: Cunningham, Janet; Williamson, Dianne; Robinson, Kerin M.; Paul, Lindsay
• Is Part Of: Health information management journal. Volume 42:Issue 3(2013)
• Page Start: 4
• Page End: 11
• Publication Date: 2013-10
• Subjects: ICD-10-AM -- International Classification of Diseases -- Health Classification -- Health Information -- Health Information Management -- Injuries -- Falls; Medical records -- Management -- Periodicals; Medical records -- Management -- Australia -- Periodicals; Medical records -- Management; Australia; Periodicals; Periodicals; 651.50426105
• DOI: 10.1177/183335831304200303
• Languages: English
• ISSNs: 1833-3583

Abstract

Falls are the leading cause of hospital-treated injuries in Australia. Injury surveillance data are analysed to identify common causes and types of fall injuries, risk factors for particular activities, location of injury occurrence, and age groups at risk of injury. External cause of injury data include cause of injury, place of occurrence, and activity when injured. These are collected in hospitals, where ICD-10-AM codes are assigned by Health Information Managers and clinical coders, based on medical record documentation. The current study examined the extent and quality of Victorian coded data on external cause of injury due to a fall, assessed its usefulness for injury prevention, and compared the Victorian and Australia-wide data. This involved an analysis, using the Victorian Admitted Episode Dataset, of 38, 153 hospital separations in 2007–08 for fall injuries and a comparison with the 2003–04 national data. This showed similar usage of External cause codes in Victoria and Australia-wide. There was overuse of residual categories such as Other and Unspecified, these being assigned in 73.8% of separations in Victoria and 71.6% nationally. The problem of overuse of Unspecified external cause codes for hospitalised fall injuries is arguably multifactorial. Inevitably, this overuse reduces the value of the coded data for injury surveillance and prevention, and for monitoring of the public health.