Cost Driver Analysis

1. Cost Driver Analysis Christoff Raath Health Monitor Co. 10 July 2006

2. National Health Monitor • Industry-wide scenario modeling tool • Annual statutory returns • Extended through detailed scheme data • All registered schemes and options • Database 2002 onwards

3. Medical Scheme Income Statement

4. MSA Risk Contri-bution NonHCExp Reserves

5. Claimed MSA Unused Risk Contri-bution NonHCExp Reserves

6. GP • Specialist • Medicine • Dental • Radiology • Pathology • Hospital • Other MSA Risk Contri-bution NonHCExp Reserves

7. MSA Risk Admin Contri-bution Broker fees NonHCExp Managed Care Other Reserves

8. MSA Risk Contri-bution NonHCExp Investment and other income Reserves

9. Contribution Levels Solvency Level Type of Scheme Contributions per member per month over 2002-2004

10. Scheme Distribution Number of members in different types of schemes

11. Composition of Contributions

12. Composition of Contributions Contributions per member per month

13. Gross Contribution Increases

14. Risk Contribution Increases

15. Contribution Increases Broken Down Increases per year 13.8% 10.0% 6.2%

16. Contribution Increases Broken Down Annualised increases 2002-2004 per type of scheme 10.8% 10.0% 9.4%

17. Contribution Increases Broken Down Annualised increases 2002-2004 per solvency level 14.7% 10.0% 10.1%

18. Contribution Increases • Benefits 6.2% • Reserve building 2.3% • Non healthcare exp 1.3% • MSA 1.3% • Investment & other income (-0.9%)

19. Real Contribution Increases Increases over CPI per year 6.7% 5.8% 4.9%

20. Real Contribution Increases • Benefits 3.1% • Reserve building 1.7% • Non healthcare exp 0.7% • MSA 0.8% • Investment & other income (-0.7%)

21. Expenses • Administration • Managed health care • Commission • Other

22. Expense Composition (Rands) Expenses per member per month, average over 2002-2004

23. Expenses Increases (%) Annualised increases in expenses over 2002-2004

24. Surpluses Generated Surplus per member per month over 2002-2004

25. Increase in Surpluses Annualised increase in pmpm surpluses generated 2002-2004

26. Risk Benefits Distribution of risk benefits, 2002-2004

27. Benefits (Rands) Average spent per member per month over 2002-2004

28. Benefits (%increase) Annualised increases in risk benefits over 2002-2004

29. Benefits (%increase) Annualised increases in risk benefits over 2002-2004

30. Conclusions • Risk benefits • Hospitalisation • Benefit design • Demographic changes insignificant • Surplus generation • Scheme behaviour influenced by • Solvency requirements • Prescribed minimum benefits

31. Benefits (weighted %increase) Weighted annualised increases in risk benefits over 2002-2004

32. Hospital cost analysis:2003-2005 Rajesh Patel BHF

33. Objectives • Presentation limited to results of: • Effect of Hospital Network on cost variability • Effect of alternate re-imbursement models

34. Data bias • 2006 BHF requested 2 data sets for analysis • Event cost • Aggregated data to evaluate population risk & utilisation • 1 administrator reponded • Part of 1 data set received • Results presented are therefore biased

35. Method • Dependent variable: Hospital cost 2003-5 • GLM1: Main effects • GLM2: with interaction

36. GLM1 Treatment year Hospital* Hospital network Physician practice type Basket of Procedures Payment type Age bands Region GLM2 Hospital* Physician practice type Basket of Procedures Payment type Age bands Region Treatment year X Hospital network Stratified by

37. Results • Model was strong (had power) • All variables used explained data variability • P < 0.0001

38. Y intercept = R12937 • Essential data for negotiation • Explain variance

39. Reason for higher cost of some networks • Lack of billing standardisation • Differences in interpretation • chargable vs non chargable • Problem perpetuated by competition commissioner ruling • Unregulated access to technology • Practitioner driven but clinic funded • E.g. disposable vs non disposable • Unregulated prices – non MCC items

40. Age has been adjusted

41. What is your experience/perception about re-imbursement (per diems) and FFS effect on hospital cost per admission? • FFS is more costly • Per Diem is more costly • Don’t know • No vested interest, prefer to abstain

42. Per Diems • Entrenched in US • With a number of funds it’s more costly than FFS • They cannot move away from it • Investers / Network Board of Directors not likely to approve a lower fee structure unless guarantees of volumes • For profit entities • With cost shifting, there is a premium to be paid • Per diem cost will therefore almost always be higher than FFS in the SA environment

43. 45% 55% • Good pricing and negotiation by network and funders • Effect of outlier threshold – study the contract • How is outlier threshold determined?

45. If “Yes” to last question • Are you willing to share data in support of your answer? • Yes • No • Don’t know need to consult • Would you like to see per diems in current code structure removed? • Yes • No

46. Conclusions • Urgent need for billing standardisation • Need to engage a willing HASA • No discussion of fees! – CC rules! • Effect of network on hospitalisation cost (for this data set) is consistant regardless of type/dimension of analysis • Tested recent claims made by private hospital industry • Is per diems the ideal alternate reimbursement method? • Recent contracts -not renewed or cancelled