Literature DB >> 30874999

Predictors of Return to Work for Occupational Rehabilitation Users in Work-Related Injury Insurance Claims: Insights from Mental Health.

Hadi Akbarzadeh Khorshidi1,2, Miriam Marembo3, Uwe Aickelin4.   

Abstract

Purpose This study evaluates the Occupational Rehabilitation (OR) initiatives regarding return to work (RTW) and sustaining at work following work-related injuries. This study also identifies the predictors and predicts the likelihoods of RTW and sustainability for OR users. Methods The study is conducted on the compensation claim data for people who are injured at work in the state of Victoria, Australia. The claims which commenced OR services between the first of July 2012 and the end of June 2015 are included. The claims which used original employer services (OES) have been separated from claims which used new employer services (NES). We investigated a range of predictors categorised into four groups as claimant, injury, and employment characteristics and claim management. The RTW and sustaining at work are outcomes of interest. To evaluate the predictors, we use Chi-squared test and logistic regression modelling. Also, we prioritized the predictors using Akaike Information Criterion (AIC) measure and Cross-validation error. Four predictive models are developed using significant predictors for OES and NES users to predict RTW and sustainability. We examined the multicollinearity of the developed models using Variance Inflation Factor (VIF). Results About 75% and 60% of OES users achieved RTW and have been sustained at work respectively, whilst just approximately 30% of NES users have been placed at a new employer and 25% of them have been sustained at work. The predictors which have the most association with OES and NES outcomes are the use of psychiatric services and age groups respectively. We found that having mental conditions is as an important indicator to allocate injured workers into OES or NES initiatives. Our study shows that injured workers with mental issues do not always have lower RTW rate. They just need special consideration. Conclusion Understanding the predictors of RTW and sustainability helps to develop interventions to ensure sustained RTW. This study will assist decision makers to improve design and implementation of OR services and tailor services according to clients' needs.

Entities:  

Keywords:  Injuries; Mental health; Occupational rehabilitation; Return to work; Workers’ compensation

Year:  2019        PMID: 30874999     DOI: 10.1007/s10926-019-09835-4

Source DB:  PubMed          Journal:  J Occup Rehabil        ISSN: 1053-0487


  14 in total

1.  Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

Authors:  E W Steyerberg; F E Harrell; G J Borsboom; M J Eijkemans; Y Vergouwe; J D Habbema
Journal:  J Clin Epidemiol       Date:  2001-08       Impact factor: 6.437

2.  Improving return to work research.

Authors:  Glenn Pransky; Robert Gatchel; Steven J Linton; Patrick Loisel
Journal:  J Occup Rehabil       Date:  2005-12

3.  Determinants of physical therapy use by compensated workers with musculoskeletal disorders.

Authors:  Janneke Berecki-Gisolf; Alex Collie; Roderick J McClure
Journal:  J Occup Rehabil       Date:  2013-03

4.  The effect of mental health on employment: evidence from Australian panel data.

Authors:  Paul Frijters; David W Johnston; Michael A Shields
Journal:  Health Econ       Date:  2014-07-24       Impact factor: 3.046

5.  Validation of the Readiness for Return-To-Work Scale in Outpatient Occupational Rehabilitation in Canada.

Authors:  Joanne Park; Mary Roduta Roberts; Shaniff Esmail; Fahreen Rayani; Colleen M Norris; Douglas P Gross
Journal:  J Occup Rehabil       Date:  2018-06

6.  Patterns and Predictors of Failed and Sustained Return-to-Work in Transport Injury Insurance Claimants.

Authors:  Shannon E Gray; Behrooz Hassani-Mahmooei; Ian D Cameron; Elizabeth Kendall; Justin Kenardy; Alex Collie
Journal:  J Occup Rehabil       Date:  2018-12

Review 7.  Vocational rehabilitation for enhancing return-to-work in workers with traumatic upper limb injuries.

Authors:  Wen-Hsuan Hou; Ching-Chi Chi; Heng-Lien Lo; Yun-Yun Chou; Ken N Kuo; Hung-Yi Chuang
Journal:  Cochrane Database Syst Rev       Date:  2017-12-06

8.  Mental health claims management and return to work: qualitative insights from Melbourne, Australia.

Authors:  Bianca Brijnath; Danielle Mazza; Nabita Singh; Agnieszka Kosny; Rasa Ruseckaite; Alex Collie
Journal:  J Occup Rehabil       Date:  2014-12

9.  Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.

Authors:  Gary S Collins; Johannes B Reitsma; Douglas G Altman; Karel G M Moons
Journal:  BMC Med       Date:  2015-01-06       Impact factor: 8.775

10.  Predicting Employment Status of Injured Workers Following a Case Management Intervention.

Authors:  Halimah Awang; Norma Mansor
Journal:  Saf Health Work       Date:  2017-11-20
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  2 in total

1.  Relationship between workers' return to work, job retention and income in industrial accidents in Korea: a longitudinal study.

Authors:  Suk Won Bae; Inchul Jeong; Jin-Ha Yoon; Seung Wook Lee; Tae Hyun Kim; Jong-Uk Won
Journal:  BMJ Open       Date:  2021-04-09       Impact factor: 2.692

2.  Return-to-Work Predictions for Chinese Patients With Occupational Upper Extremity Injury: A Prospective Cohort Study.

Authors:  Zhongfei Bai; Jiaqi Zhang; Chaozheng Tang; Lejun Wang; Weili Xia; Qi Qi; Jiani Lu; Yuan Fang; Kenneth N K Fong; Wenxin Niu
Journal:  Front Med (Lausanne)       Date:  2022-07-05
  2 in total

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