Abstract
This study investigates the predictive capacity of the biopsychosocial ‘Generic Screening Tool’ (GST) in the early identification of delayed recovery in workers’ compensation patients. Consecutive musculo-skeletal workers’ compensation patients (n = 102, age = 41 ± 12 years and 32% female) were prospectively screened and measured at baseline with follow-up measures at two to four week intervals. Insurer databases provided absentee and costs whilst ISMAM© software provided global measures and the time required to reach 80% of pre-injury status (t80). Delayed recovery was measured by: 1) absenteeism at ≥ 28 paid days off; 2) claim cost at ≥ $10,000; and 3) t80 at ≥ 6 weeks. Analysis at different GST cut-offs used sensitivity, specificity and subsequent Likelihood Ratios (LR). Mean GST-score was statistically higher (t-test, p < 0.001) for delayed recovery in each outcome group. The use of a 110 GST-point cut-off score provided sensitivity and specificity levels with subsequent LRs for each outcome where: absenteeism ≥ 28 days showed 83%: 77% (LR = 3.6); cost ≥ $10 000 showed 88%: 65% (LR = 2.5); and t80 ≥ 6 weeks showed 92%: 80% (LR = 4.5). These values were similar in the non-delayed trait but at a lower cut-off of 100 GST-points. Direct correlation between GST-score and each outcome was only significant for Log-t80 (r = 0.72, p < 0.001). The GST provides reliable early identification of workers’ compensation patients with a high risk of delayed recovery as measured by absenteeism of ≥ 28 days off, claim costs ≥ $10 000 and ≥ 6 weeks to reach 80% of the individual’s pre-injury status.