1. The Future of Disease Management May 2008

2. 1 Agenda History of disease management Don’t drink the Kool-Aid: Why the “let’s do DM” model has not lived up to expectations (but no one’s noticed) –Actuarial pre-post savings calculations are provably invalid Success is in sight: How to make your health plan work…with an example Lessons for you, as a health plan

3. History of Disease Management: Milestones Invention of the automated cigarette roller by John Duke (1896)

4. History of Disease Management: Milestones Introduction of Twinkies by Hostess (1953)

5. History of Disease Management: Milestones Ray Kroc franchises the McDonald Brothers (1955)

6. 5 History of Disease Management “We want to make the world safe for DM-ocracy” Woodrow Wilson

7. 6 -- “Engine Charlie” Wilson “What’s good for DM is good for the country.”

8. History of Disease Management: Milestones Cap’n Crunch sets record for sugar content in a cereal (1972—59%)

9. History of Disease Management: Milestones 2003 – “Small” Soda now bigger than a 1972 Large Soda

10. 9 Agenda History of disease management Don’t drink the Kool-Aid: Why the classic model has failed (but no one’s noticed) –Actuarial pre-post savings calculation methodology is provably invalid Success is in sight: New models which really do work Lessons for you, as a health plan

11. 10 In this example Assume that “trend” is already taken into account correctly Focus on the baseline and contract period comparison

12. 11 Base Case: Example from Asthma First asthmatic has a $1000 IP claim in 2005 2005 (baseline) 2006 (contract) Asthmatic #11000 Asthmatic #2 Cost/asthmatic

13. 12 Example from Asthma Second asthmatic has an IP claim in 2006 while first asthmatic goes on drugs (common post-event) 2005 (baseline) 2006 (contract) Asthmatic #11000100 Asthmatic #201000 Cost/asthmatic What is the Cost/asthmatic In the baseline?

14. 13 Cost/asthmatic in baseline? 2005 (baseline) 2006 (contract) Asthmatic #11000100 Asthmatic #201000 Cost/asthmatic$1000 Vendors don’t count #2 in 2005 bec. he can’t be found

15. 14 Cost/asthmatic in contract period? 2005 (baseline) 2006 (contract) Asthmatic #11000100 Asthmatic #201000 Cost/asthmatic$1000$550

16. 15 Why Pre-Post Overstates Savings 2005 (baseline) 2006 (contract) Asthmatic #11000100 Asthmatic #201000 Cost/asthmatic$1000$550 In this case, a “dummy population” falls 45% on its own without DM due to #2 being a “plane on the ground”

17. 16 The Valid Way to Check Pre-Post Savings Claims –You look at the event rates overall in the plan (or in your own organization if large enough) over time As though you were measuring a birth rate. Very simple As in this example, count total IP (and ER) events, divide by 1000

18. 17 Asthma events in the payor as a whole – the plausibility check 2005 (baseline) 2006 (contract) Asthmatic #11000100 Asthmatic #201000 Inpatient events/year 11

19. 18 This is called a “plausibility check” You use plausibility checks all the time in your everyday life and don’t think twice about them –But for some reason in DM people rely on faith instead Here is one of many real-world examples of actuarial “pre-post” results bearing no relation to reality

20. 19 Program Year One – Clinical Indicators Clinical Outcomes:

21. 20 Note the pink line in this Northeast health plan – CAD events did not fall 48%. They rose

22. 21 Agenda History of disease management Don’t drink the Kool-Aid: Why the “let’s do DM” model has not lived up to expectations (but no one’s noticed) –Actuarial pre-post savings calculations are provably invalid Success is in sight: How to make your health plan work…with an example Lessons for you, as a health plan

23. 22 Let’s look at an example of a model of the future which works This model is a tight care coordination/DM model in which all “data” coming into the organization is used, not wasted This company is not a health plan. They do not pay claims. But they do all the member services services and UM/CM/DM interventions As the next slide shows, they are claiming substantial reductions from trend across their population

24. 23 4.51% medical/Rx claim trend over past 5 years 61% of companies had a reduction in claims/employee in first year None of accounts had reduction in benefits (no cost shifting to employees) or network changes 92% patient satisfaction ©2007 Quantum Health, Inc. All rights reserved. This looks promising…is it real?

25. 24 Use a “plausibility test” before deciding it’s best practice How would you check the plausibility of this? Remember, if everything produced its claimed ROI/savings, you’d have negative medical spending

26. 25 Plausibility test: Is this performance due to good management, luck, or invalidity? If it’s “real,” you’d expect –Utilization of the ER and hospital would decline Let’s check the actuals against the expectations

27. 26 Is it luck or is it real: Plausibility Test ER Use-15% Hospital Use-27% (-13% Admissions, - 16% ALOS)

28. 27 Plausibility test: Is this performance due to good management, luck, or invalidity? If it’s “real,” you’d expect –Utilization of the ER and hospital would decline (but mostly not be replaced with OP procedures) Let’s check the actuals against the expectations

29. 28 Is it luck or is it real: Plausibility Test ER Use-15% Hospital Use-27% (-13% Admissions, - 16% ALOS) Outpatient Procedures-9%

30. 29 Plausibility test: Is this performance due to good management, luck, or invalidity? If it’s “real,” you’d expect –Utilization of the ER and hospital would decline (but mostly not be replaced with OP procedures) –Specialist visits would decline Let’s check the actuals against the expectations

31. 30 Is it luck or is it real: Plausibility Test ER Use-15% Hospital Use-27% (-13% Admissions, - 16% ALOS) Outpatient Procedures-9% Specialist Visits-9%

32. 31 What other explanation could there be?

33. 32 OK, so maybe all these things happened because demographics improved? Then you would expect everything to decline, not just the expensive things But if it’s truly through better prevention, DM, and care coordination, you’d expect to see increases in PCP visits, drugs etc.

34. 33 Plausibility test: Is this performance due to good management, luck, or invalidity? If it’s “real,” you’d expect –Utilization of the ER and hospital would decline (but mostly not be replaced with OP procedures) –Specialist visits would decline –PCP visits and drug use would increase –Use of preventive care resources would be way up Let’s check the actuals against the expectations

35. 34 Is it luck or is it real: Plausibility Test ER Use-15% Hospital Use-27% (-13% Admissions, - 16% ALOS) Outpatient Procedures-9% Specialist Visits-9% PCP Visits/Drug Use+7%/+4% Preventive Care/Diagnostics+32%

36. 35 The secret to future success Total comprehensive services from a single vendor –“Plausibility-tested” results, not pre-post –One phone number (see example, next page) –Closely coordinated –Many “touch points” Example: A request for an endocrinologist referral triggers a diabetes DM program if Dx already given

37. 36 Is your health plan reducing fragmentation or causing it? Integrated Customer Service: Eliminate Plan Fragmentation Network 2 Network 3 Network 4 Directory PreCert 1 PreCert 3 PreCert 2 Out of State: not sure what to do ??? Rx Which one is “Customer Inquiry?” ©Quantum Health, Inc., 2007. All rights reserved.

38. 37 The secret to future success Total comprehensive services from a single vendor –“Plausibility-tested” results, not just pre-post –One phone number –Closely coordinated –Reduced “time to contact” from months to days via many “touch points,” all linked so that if someone calls in for one thing they might be sent somewher else as well (examples to follow)

39. 38 “Time to contact” for this organization (source: Managed Healthcare Executive)

40. 39 Examples Reducing Time to Contact through data you already receive through “touch points” you already have –“Are diabetic shoes covered?” –“I need a referral to a cardiologist”

41. 40 Lessons for you as a health plan about the future: The future is in using the data you already get, to coordinate care The future is not in fancy web-enabled consumer tools or other ways of hoping the consumer looks to the health plan for a role in care –Ain’t gonna happen The future is in transforming the huge amounts of your incoming data into light rather than losing it in heat The future is in optimzing performance of the whole, rather than of individual silos –That’s what a health plan is. Otherwise, it’s just claims-paying and contracting

42. 41 Lessons Use your data Don’t be running around inventing new things when there is plenty of opportunity in what’s already coming in the door

43. 42 Impact of New Model Size of ROI from DM: lower Size of Savings from program: Higher Note: I don’t want to get into the math but a lower ROI can result In higher net savings

44. 43 Impact Size of ROI from DM Size of Savings from program: Higher Credibility of program: Priceless