Appl Ergon. Author manuscript; available in PMC 2010 May 1.
Published in final edited form as:
Published online 2008 November 22.
PMCID: PMC2765332
NIHMSID: NIHMS101600

Estimating investment worthiness of an ergonomic intervention for preventing low back pain from a firm's perspective

Abstract

A mathematical model was developed for estimating the net present value (NPV) of the cash flow resulting from an investment in an intervention to prevent occupational low back pain (LBP). It combines biomechanics, epidemiology, and finance to give an integrated tool for a firm to use to estimate the investment worthiness of an intervention based on a biomechanical analysis of working postures and hand loads. The model can be used by an ergonomist to estimate the investment worthiness of a proposed intervention. The analysis would begin with a biomechanical evaluation of the current job design and post-intervention job. Economic factors such as hourly labor cost, overhead, workers' compensation costs of LBP claims, and discount rate are combined with the biomechanical analysis to estimate the investment worthiness of the proposed intervention. While this model is limited to low back pain, the simulation framework could be applied to other musculoskeletal disorders. The model uses Monte Carlo simulation to compute the statistical distribution of NPV, and it uses a discrete event simulation paradigm based on four states: (1) working and no history of lost time due to LBP, (2) working and history of lost time due to LBP, (3) lost time due to LBP, and (4) leave job. Probabilities of transitions are based on an extensive review of the epidemiologic review of the low back pain literature. An example is presented.

Keywords: spine, cost-benefit, investment, intervention

RESULTS

The median NPV of the cash flow resulting from the intervention in the example was $3,598, which means that there was a 50% chance that the NPV will be greater than this value. The average NPV was$4,851. The 5th and 95th-percentiles of the distribution were $-24,574 and$37,201, respectively. Figure 3 shows the relative frequency plot of NPV when a discount rate of 7% is used. In fact, 61% of the simulation runs produced a positive NPV; therefore, it is more likely than not that this investment would meet the investment criteria of having a positive NPV when a rate of return of 7% was used in the analysis. The wide confidence interval means that the actual NPV could vary widely depending on the specific injury experience with that job.

Relative frequency histogram of net present value (NPV) for example. Although it spans zero (95% C.I. is [−24,574, 37,201]), the mean is \$4,851. A discount rate of 7% was used in the simulation.

Sensitivity analyses showed that the planning horizon, discount rate, transition probabilities, and lost work days affected NPV (figure 4). A longer planning horizon provides more time for benefits of the intervention to accrue, which increases NPV. On the other hand, increasing the discount rate reduces the current value of the benefits that occur in the future, so a higher discount rate reduces NPV. The probability of going from state 1 to state 3 (i.e. becoming injured) affected NPV, as expected. This clearly points to the importance of reducing injury risk through ergonomic intervention. Reducing the amount of time loss each time there is a back injury, which models effective return-to-work programs, mitigated the economic benefit of the ergonomic intervention. However, such an analysis does not account for the contribution of the ergonomic intervention to the return-to-work program.

Sensitivity analysis for planning horizon (A), discount rate (B), increase in injury probability (from state 1 to state 3) (C), and decreasing time loss for each back injury episode (D). Box-and-whisker plots show the range produced for each set of 10 ...

DISCUSSION

A stochastic model based on epidemiologic data and biomechanical modeling was developed to estimate the net present value of the cash flow over a finite time horizon resulting from an investment in an ergonomic intervention to prevent lifting-related occupational low back pain. The material handling example illustrated how the model can be used to evaluate the investment worthiness of an intervention. While the model is limited to occupational low back pain, the stochastic simulation framework could be applied to other musculoskeletal disorders.

The model goes beyond existing cost-benefit methods by synthesizing biomechanics, epidemiology, and finance into one analysis tool. Other methods of cost-justification in ergonomics do not quantitatively link biomechanical job analyses to changes in injury costs. Moreover, the most detailed model yet developed by Oxenburgh (Oxenburgh, 1991; Oxenburgh et al., 2004) is based on pay-back period as a metric of investment worthiness. Unfortunately for practicing ergonomists who would like to use that model, many firms use NPV or internal rate of return as methods for evaluating capital budgeting decisions and pay-back period is used less often (Graham and Harvey, 2001). Proprietary methods, such the Return on Health, Safety, and Environmental Investments (ROHSEI) software tool developed by ORC Worldwide (Washington, DC, USA), do not include a tool for linking changes in biomechanical stresses on the low back to changes in injury costs.

We chose to model NPV using Monte Carlo simulation because some of the most important cost-drivers in the model, such as lost time, are best described using probability distributions. Monte Carlo simulation is a well-accepted method in engineering economics (Park and Sharp-Bette, 1990). We chose to use NPV instead of IRR as the primary metric of investment worthiness because the IRR is not mathematically well-behaved when the cash flow changes sign over the planning horizon. Specifically, the IRR can be an irrational number when the cash flow switches from positive to negative multiple times. Using Monte Carlo simulation to model parameters as random variables creates situations where this may occur. Therefore, NPV was selected to avoid the problem of interpreting irrational rates of return.

Erector spinae moment arm is a critical parameter in low back models because it is inversely related to spinal compression. Although more recent models have used a larger moment arm, we chose to use a moment arm value that was consistent with what Chaffin used to derive the exposure-injury relationship reported in the 1981 NIOSH Work Practices Guide from his epidemiological study (Chaffin and Park, 1973). At the time Chaffin was conducting the re-analysis of his epidemiological data for NIOSH, his research group was using an erector spinae moment arm value of 5.0 cm for all low back modeling (Chaffin, 1969; Chaffin and Andersson, 1984). While it would be possible to integrate our approach with many biomechanical models of the low back, it is important to note if the assumed erector spinae moment arm differs from this value.

The model has several limitations. It does not include the effects of low back pain for employees who do not file workers' compensation claims, which may include reduced productivity and increased sick leave. The model also limits the use of the four-state transition scheme to labor costs and does not extend it to productivity and quality, which must be modeled using $Btproduction&quality$. A departure from employment with the firm is not broken down into disability claim vs. non-disability claim; a retirement due to permanent LBP disability is modeled as a very prolonged stay in state 3. This infrequent but very costly event is included in the model by the long tail of the Weibull distribution.

The range of applications for the model is also limited by the study population studied by Chaffin and Park (1973), which was a manufacturing workforce. Thus, the model is not suitable for studying seating and light work in the office environment. However, the jobs studied by Chaffin and Park (1973) had heavy biomechanical exposures, which suggests that their results should apply to jobs with similar heavy exposures. For example, other occupations with heavy exposures include manufacturing, health care, and construction.

We chose to model the investment worthiness of interventions to prevent occupational LBP because LBP is a significant public health problem and cost driver for firms. It is important to recognize, however, that firms invest in ergonomics for many reasons beyond project return-on-investment, including the ethical obligation of providing a safe workplace, regulatory compliance, remaining competitive in the market for talented employees, and collective bargaining. Demonstrating a positive NPV should be viewed as one component of making a successful business case for an ergonomics intervention.

ACKNOWLEDGEMENTS

This work was supported by grant AR52565 from the National Institutes of Health. The authors also wish to thank Mike Foley for insight into modeling workers' compensation costs.

Footnotes

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