Aligning Technology with Workers Compensation Results

1. Aligning Technology with Workers Compensation Results James R. Jones CPCU, AIC, ARM Executive Director Katie School Insurance Illinois State University

2. Katie School Project Researchers James R. Jones, CPCU, AIC, AIS, ARM Executive Director - Katie School of Insurance Illinois State University Michael R. Williams, Ph.D. Professor of Marketing Illinois State University Team of academic researchers

3. Corporate Systems sponsored research project to determine the effects of technology on claim practices Katie School of Insurance Research (link to survey)

4. The objective was to determine the current and potential effect of technology on improving workers comp claim results Research Hypotheses • Automation has significant potential to facilitate improved results in the Workers’ Comp claim management process. • Limited automation improvements have been implemented to-date – and those that have are focused on very specific areas, e.g. medical cost management. • The impediments to major automation-supported business process changes are significant.

5. Research Focus • Why research automation impacts on Workers’ Comp claims? • Continued economic challenge for this line of business (Subject of many reform efforts) • The potential for significant savings (both loss and admin costs) • Current archaic technology • Research Participants • Insurance carriers with Net Written Premium exceeding $10 million in workers compensation coverage • Fortune 1000 companies • Third party administrators (Top 20) • Why research both carriers/TPA’s and their customers? • Holistic view • Determine the differences and assess the implication

6. Building on previous research and adding to the body of industry knowledge Research Methodology • Literature search • Phase 1: Qualitative research and analysis • In-depth interviews • Preliminary survey • Phase 2: Quantitative research • Credible results based on survey response • Phase 3: Analysis of research results

7. RESPONSE CREDIBILITY • 426 distinct organizations comprised the sample pool • Top 201 Workers Compensation Carriers [distinct entities] • Top 25 TPAs • 200 Work Comp Buyers- random sample from Fortune 1000 • 108 organizations responded with completed instruments • Response Rate of 25.4 percent • 52 Carriers for 25.9 percent Response Rate • 9 TPAs for a 36 percent Response rate • 47 W C buying organizations for 23.5 percent response rate • High Representation and Statistical Confidence • Points of Pain: 95% CI +/-.40 • Usefulness of Technology: 95% CI +/-.55 • Utilization of Technology: 95% CI +/-.75 • Benefits from Technology: 95% CI +/-.35 • Obstacles to Implementation: 95% CI +/-.55

8. CARRIER RESPONSE CREDIBILITY • 4 Tier Categories based on WC NPW • Tier 1: NPW = $300,000,000 to $1,500,000,000 • Included 18 entities; 8 Respondents for 44.4% Response Rate • Tier 2: NPW = $100,000,000 to $299,000,000 • Included 42 entities; 8 Respondents for 19.0% Response Rate • Tier 3: NPW = $35,000,000 to $99,000,000 • Included 59 entities; 15 Respondents for 25.4% Response Rate • Tier 4: NPW = $10,000,000 to $34,000,000 • Included 82 entities; 21 Respondents for 25.6% Response Rate • High Representation and Statistical Confidence • Points of Pain: 95% CI +/-.60 • Usefulness of Technology: 95% CI +/-.70 • Utilization of Technology: 95% CI +/-.80 • Benefits from Technology: 95% CI +/-.40 • Obstacles to Implementation: 95% CI +/-.60

9. TPA RESPONSE CREDIBILITY • Sample included Top 25 TPAs on basis of Administration Claims Paid for the year 2002 • Did not categorize by tier due to small sample • 9 responses received for overall = 36% Response Rate • 6 responses received from top-ten = 60 % Response Rate • Confidence Intervals not applicable

10. BUYER RESPONSE CREDIBILITY • 5 Tier Categories based on Annual Revenues • Tier 1: Revenues = $15,000,000,000 to $30,000,000,000 • Included 40 entities; 9 Respondents for 22.5% Response Rate • Tier 2: Revenues = $5,000,000,000 to $14,000,000,000 • Included 40 entities; 9 Respondents for 22.5% Response Rate • Tier 3: Revenues = $2,500,000,000 to $4,999,000,000 • Included 40 entities; 10 Respondents for 25.0% Response Rate • Tier 4: Revenues = $1,500,000,000 to $2,499,000,000 • Included 40 entities; 9 Respondents for 22.5% Response Rate • Tier 5: Revenues = Under $1,500,000,000 • Included 40 entities; 10 Respondents for 25.0% Response Rate • High Representation and Statistical Confidence • Points of Pain: 95% CI +/- .55 • Usefulness of Technology: 95% CI +/- .90 • Utilization of Technology: 95% CI +/-1.10 • Benefits from Technology: 95% CI +/- .60 • Obstacles to Implementation: 95% CI +/- .70

11. Key Findings • Respondent perceptions vary according to respondent type and size. • Automation can mitigate points of pain and enable significant improvements. • There is a gap between perceived usefulness and current level of utilization. • The gap is less for mature technologies and significantly larger for emerging technologies.

12. Key Findings • Rising medical costs have achieved “critical status” – outdistancing any other issue. • Interestingly, the technology that specifically targets this cost driver, medical bill automation, is not only the most “used” technology, it is also perceived as the most “useful”. • Given that the critical status of this issue, the implications is that existing solutions must be augmented with new solutions to resolve the issue in its current form.

13. Key Findings • Technologically sophisticated respondents are not perceiving the same levels of benefit/value as the less technologically sophisticated. • Strong correlation between perceived benefit and emerging technologies. • The obstacles to implementation of technology may not be as burdensome as once thought.

14. Identifying the Key Points of Pain

15. Reaching “critical” status – for every type and size of respondent Rising medical costs scored significantly higher than all other “points of pain” Points of Pain

16. Usefulness Scoring Utilization Scoring Technology Assessment

17. Thirty different technologies were assessed. These technologies had been identified and validated in the qualitative research. Technology Assessment

18. Substantial Variation in Both Usefulness and Utilization

19. Perceived Usefulness of Technology The Top 10

20. Utilization of Technologies The Top 10

21. Mature Technologies Emerging Technologies Gap Between Usefulness and Utilization

22. The increasing gap indicates increasing potential of achieving value and benefit. Emerging Technologies The largest tier of carriers showed a much higher utilization of the emerging technologies than did any other group. Gap Between Usefulness and Utilization

23. Difference in Perceived Usefulness and Actual Utilization (By Largest Differences)

24. Claims Technology – Outcomes & Benefits Assessment

25. Desired Outcomes • Increase in Productivity of Claims Reviews and Audits • Reduced Loss Costs • Improved Return-to-Work • Reduced Administrative Expenses • Reduced Frequency and Severity of Losses • Reduction in Claim Settlement Times

26. Increase in Productivity of Claims Reviews and Audits Due to Technology

27. Reduced Loss Costs Due to Technology

28. Improved R-T-W Due to Technology

29. ReducedAdministrative Expenses

30. ReducedFrequency and Severity of Losses

31. Reduction in Claim Settlement

32. Importance of Improvements Required to Address Points of Pain

33. Return-to-work Loss forecasting accuracy, Settlement time Timeliness in payments to providers Measurement is affected by what the system can measure, which is often a function of the size of the organization What’s Not Getting Measured

34. Barriers and Obstacles

35. Obstacles in Implementing Technology • Level of investment to immediate payback (5.35) • Lack of information on resulting benefits (5.11) • Legacy systems and processes (5.07) • Turnover in claims personnel (4.76) • Lack of data standardization (4.66)

36. Relationship Between Technology and Outcomes(More Technology Doesn’t Necessarily Mean Better Results) MODEL ONE MODEL TWO 40 40 30 30 20 Claim review productivity Claim review productivity 20 10 Observed 10 Linear 0 Logarithmic 0 0 100 200 300 0 20 40 60 80 100 120 140 TECHNOLOGICAL SOPHISTICATION TECHNOLOGICAL SOPHISTICATION LEGEND Observed Values Linear Relationship Curvilinear Relationship

37. Positive Relationship Between New Technology and Outcomes

38. Conclusions • There is significant potential for improved results based on leveraging underutilized technologies. • The potential ranges from 5% to 40% increase in productivity and from 2% to 20% in loss cost reductions. • It is critical to benchmark and measure practices that will contribute to improving results. • Effective implementation and system integration of systems will help reduce the gaps.