Case Study 1: Use of AI to identify claims suitable for vocational rehabilitation support
It may be surprising to learn that AI technology has been used since 1991 to automate the screening and identification of cases suitable for vocational rehabilitation.16
That year, In response to funding cuts, New York State’s Department of Social Services Office of Disability Determination (ODD), together with the state’s Department of Education Office of Vocational and Educational Services for Individuals with Disabilities (VESID), developed, piloted, and deployed DISXPERT. This intelligent rules-based technology system, intended to refer members of the Social Security Disability Insurance (SSDI) program for vocational rehabilitation services, was not only successful at in identifying cases suitable for such referrals. For vocational services, it also did so with greater precision and objectivity than human rehabilitation subject matter experts (SMEs), and at greater speed and with lower associated costs.16
DISXPERT’s knowledge base was created using a combination of empirical research findings of the factors that predict successful vocational rehabilitation outcomes. A machine learning approach was used to analyze the statistical data of 9,000 cases to discern among factors that positively contributed to a RTW outcome, and the rules-based system created from a review of 225 cases by subject matter experts.16
Notably, at the time DISXPERT was piloted, results showed it accurately identified 93% of the cases that would benefit from rehabilitation intervention.
DISXPERT was piloted at a single site for a nine-month period, during which the system screened and assessed a total of 12,431 cases. Its progress was closely tracked. During the testing process, two changes were made to improve DISXPERT’s efficiency. In the first, the rules used for orthopedic disabilities were modified to more closely match the thinking of the vocational rehabilitation counselors. In the second, modifications to the rules were made in response to a new disability coding scheme from the U.S. Social Security Administration. Using the new coding scheme allowed DISXPERT to more clearly delineate disability cases.16
Upon completion of the pilot, its accuracy and performance were validated by comparing the decisions it provided on 200 cases with those reached by each of the SMEs on their manual review of the same cases. Results of this validation showed the determinations by DISXPERT and the SMEs aligned in 198 of the 200 cases, reflecting an overall agreement rate of 99%.16
Following the rollout of the DISXPERT intelligent screening system to all district offices in New York State from 1992 onwards, benefits continued to be realized. The offices saw a significant increase in productivity (more cases screened for rehabilitation suitability with less staff), reduced time to reach decisions, an 80% decline in the drop-out rate of participants who commenced vocational rehabilitation programs, and enhanced training opportunities for junior staff on how decisions and determinations were reached.16
As one of the primary functions of case managers and rehabilitation consultants in the life insurance industry is the identification of claimants who would benefit from rehabilitation intervention, this case study presents a blueprint for how life insurers might leverage AI capabilities to realize similar gains.