Predicting failure to return to work

Generalizability of a Musculoskeletal Therapist Electronic Health Record for Modelling Outcomes to Work-Related Musculoskeletal Disorders

PURPOSE

Electronic Health Records (EHRs) can contain vast amounts of clinical information that could be reused in modelling outcomes of work-related musculoskeletal disorders (WMSDs). Determining the generalizability of an EHR dataset is an important step in determining the appropriateness of its reuse. The study aims to describe the EHR dataset used by occupational musculoskeletal therapists and determine whether the EHR dataset is generalizable to the Australian workers' population and injury characteristics seen in workers' compensation claims.

METHODS

Variables were considered if they were associated with outcomes of WMSDs and variables data were available. Completeness and external validity assessment analysed frequency distributions, percentage of records and confidence intervals.

RESULTS

There were 48,434 patient care plans across 10 industries from 2014 to 2021. The EHR collects information related to clinical interventions, health and psychosocial factors, job demands, work accommodations as well as workplace culture, which have all been shown to be valuable variables in determining outcomes to WMSDs. Distributions of age, duration of employment, gender and region of birth were mostly similar to the Australian workforce. Upper limb WMSDs were higher in the EHR compared to workers' compensation claims and diagnoses were similar.

CONCLUSION

The study shows the EHR has strong potential to be used for further research into WMSDs as it has a similar population to the Australian workforce, manufacturing industry and workers' compensation claims. It contains many variables that may be relevant in modelling outcomes to WMSDs that are not typically available in existing datasets.

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

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.

Predicting Return to Work in a Heterogeneous Sample of Recently Injured Workers Using the Brief ÖMPSQ-SF

Purpose (1) to examine the ability of the Örebro Musculoskeletal Pain Screening Questionnaire-short version (ÖMPSQ-SF) to predict time to return to pre-injury work duties (PID) following a work-related soft tissue injury (regardless of body location); and (2) to examine the appropriateness of 50/100 as a suitable cut-off score for case identification. Methods Injured workers (IW) from six public hospitals in Sydney, Australia, who had taken medically-sanctioned time off work due to their injury, were recruited by insurance case managers within 5-15 days of their injury. Eligible participants (N = 213 in total) were administered the ÖMPSQ-SF over the telephone by the case manager. For objective (1) Cox proportional hazards regression analysis was used to predict days to return to PID using the ÖMPSQ-SF. For objective (2) receiver operator characteristic (ROC) analysis was used to determine the ÖMPSQ-SF total score that optimises sensitivity and specificity in detecting whether or not participants had returned to PID within 2-7 weeks. Results The total ÖMPSQ-SF score significantly predicted number of days to return to PID, such that for every 1-point increase in the total ÖMPSQ-SF score the predicted chance of returning to work reduced by 4% (i.e., hazard ratio = 0.96), p < 0.001. Sensitivity and specificity for the ROC analysis comparing ÖMPSQ-SF total score to return to PID within 2-7 weeks suggested 48 as the optimal cut off (sensitivity = 0.65, specificity = 0.79). Conclusion The results provide strong support for the use of the ÖMPSQ-SF in an applied setting for identifying those IW likely to have delayed RTW when administered within 15 days of the injury. While a score of 48/100 was the optimal cut point for sensitivity and specificity, pragmatically, 50/100 should be acceptable as a cut-off in future studies of this type.