Because the assessment data is quantitative, it can be used as a baseline for comparison to any future post-injury assessment. Likewise, test data is benchmarked against AMA guidelines. These test attributes are compelling in workers compensation cases where a comparison of pre and post injury impairments is the determining factor in claim awards.
So how do these testing differences translate into realizable benefits to an employer considering what method to use? In some cases, post-offer testing might be more expensive because, as a medical test, it requires medical staff to perform. However, the cost savings an employer generally realizes from improved matching of candidates to job requirements far exceed any testing costs. Multiple studies, have shown drastic reductions in job-related injuries when employees are matched to job requirements through PCP test results. Those reductions not only prevent workers compensation claims, they increase the number of healthy work days across an organization.
Similarly, reductions in workers compensation claim payouts are realized when pre-injury impairments are catalogued before an injury occurs. This limits workers compensation to covering only impairments related to on-the-job injuries. In addition, accurate measurement of whether an impairment was job-related is a significant factor in preventing experience rate modification for insurance premiums. In one study2, average annual workers compensation expenses were shown to decline 36% once PCP post-offer testing was instituted as a candidate assessment method.
Beyond monetary considerations, employers can use post-offer PCP testing to create a safer, more effective workforce that is matched to the jobs at hand. For more information on how to utilize post-offer Physical Capacity Profile® testing in your organization, contact us at 785-825-4444.
Harbin G, Olson J, Post-Offer, Pre-Placement Testing in Industry, American Journal of Industrial Medicine, 2005, 47(4):303
Harbin G, et al., Shoulder injury reduction with post-offer testing, Work, 2011, 39(2):113-123