Citation

Smits E, Brakenridge CL, Gane E, Warren J, Heron-Delaney M, Kenardy J, Johnston V. Accid. Anal. Prev. 2019; 132: 105280.

Affiliation

The University of Queensland, RECOVER Injury Research Centre, 288 Herston Road, Herston, Queensland, 4006, Australia. Electronic address: V.Johnston@uq.edu.au.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.aap.2019.105280

PMID

31514086

Abstract

This study aimed to develop an industry-specific tool to identify risk of poor physical and mental recovery following minor to moderate injuries sustained in a road traffic crash (RTC). Existing tools are often designed for implementation by health professionals rather than insurer case managers who may not have a background in health. This study is a secondary analysis of a longitudinal cohort study using data collected at 2-6 months and 24 months post-RTC. Participants were claimants (n = 254; Mean age = 50 years; 65% female) with mild-moderate injuries recruited through the common-law 'fault-based' compulsory third party scheme in Queensland, Australia. Sociodemographic, functional and psychological health factors were collected at baseline (2-6 months post RTC) and used as potential predictors for physical and mental health-related quality of life (Short Form 36 v2) at the 2-year follow-up. The LASSO (Least Absolute Shrinkage and Selection Operator) analysis identified six disability items (from the World Health Organization Disability Assessment Schedule 2) to predict poor physical and one item to predict poor mental health-related quality of life. Logistic regressions of these items in addition to age and gender were used to develop a screening tool. Using the tool, 90% of those at risk of poor physical and 80% of those at risk of poor mental health-related quality of life were identified correctly. To conclude, this study presents an 8-item, context-specific tool to help injury managers identify individuals at risk of poor physical and mental health recovery following mild-moderate RTC-related injuries. The tool requires validation in a new cohort and confirmation of acceptability by end-users.

Crown Copyright © 2019. Published by Elsevier Ltd. All rights reserved.

Language: en

Keywords

Decision support techniques; Mental Health Recovery; Recovery of function; Traffic accidents