Assessment of a new tool to improve case manager identification of delayed return to work in the first two weeks of a workers’ compensation claim

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

Objective: To determine whether the Plan of Action for a Case (PACE) tool improved identification of workers at risk of delayed return to work. Design: Prospective cohort of workers with accepted workers’ compensation claims in the state of New South Wales, Australia. Interventions: The 41-item PACE tool was completed by the case manager within the first two weeks of a claim. The tool gathered information from the worker, employer and treating practitioner. Multivariate logistic regression models predicted work time loss of at least one and three months. Results: There were 524 claimants with complete PACE information. A total of 195 (37.2%) had work time loss of at least one month and 83 (15.8%) had time loss of at least three months. Being male, injury location, an Orebro Musculoskeletal Pain Screening Questionnaire–Short Form score >50, having a small employer, suitable duties not being available, being certified unfit, and the worker having low one-month recovery expectations predicted time loss of over one month. For three months, injury location, a Short Form Orebro score >50, no return-to-work coordinator, and being certified unfit were significant predictors. The model incorporating PACE information provided a significantly better prediction of both one- and three-month outcomes than baseline information (area-under-the-curve statistics—one month: 0.85 and 0.68, respectively; three months: 0.85 and 0.69, respectively; both P < 0.001) Conclusion: The PACE tool improved the ability to identify workers at risk of ongoing work disability and identified modifiable factors suited to case manager–led intervention.

Original languageEnglish
Pages (from-to)656-666
Number of pages11
JournalClinical Rehabilitation
Volume34
Issue number5
DOIs
Publication statusPublished - May 2020

Keywords

  • prediction
  • Return to work
  • screening

Cite this