Predictive model to determine cost/benefit of early detection and intervention in occupational low back pain

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Abstract
Low back pain related to work injury has major socioeconomic implications. Theoretically, the early detection of patients at risk for continued work disability after 6 months of work absence, and of those with a recurrence of pain (RP) and leave work once again, should be cost-effective if combined with effective intervention. The objective of this prospective research was to analyze the cost-effectiveness of a detection-intervention system (DIS) developed from a logistic predictive model of work status. A sample of newly injured workers (N=135 males) were assessed following a first episode of compensated low back pain. A predictive biopsychosocial profile was obtained from a series of univariate and multivariate regression analyses. Structural diagnosis, pain rating, length of inactivity before treatment, negative life changes, and self-efficacy expectancies were found to be best predictors. With a correct classification rate of 72% the predictive model parameters (sensitivity and specificity) were chosen in order to reduce the number of false negatives (recurrence of pain or chronic patients not detected). The calculation of the cost/benefit proportions reveals that the detection-intervention system generates savings of up to $39,595 Can./100 patients a year. By combining low treatment expenses ($250 Can to $1,000 Can.) and increasing the success rates (40–75% return to work), the detection-intervention system is potentially more cost effective than the current approach without detection-intervention.