Presentation at BHF Conference, Durban

1. Presentation at BHF Conference, Durban July 2006

2. Outline Introduction Methodology The data and evaluation criteria Some results What HQA can tell you

3. Introduction Not-for-profit company Founded by number of industry players With the aim of developing measures of health quality delivered within medical schemes Board includes representatives from CMS, BHF, Consumer Union, Medical Schemes and Administrators Note: the focus is on health quality delivered in medical schemes – not quality delivered by an individual service provider Funding for HQA: substantial portion from BHF, rest from membership fees and survey participation fees

4. Introduction What we attempt to establish in HQA is the relative health quality delivered by different options in different medical schemes HQA does not aim to establish absolute measures of quality Data was supplied by 5 medical schemes by the time this presentation was drafted Several others (8 – 10) indicated that data will be supplied later – we will probably aim to complete the data collection by the end of August Data in this presentation covered 20 options. By the end of August, we hope to have more than 60 options in sample

5. Introduction Results are only communicated to participating schemes and scheme management Results may not be used in marketing material, and each participant agrees that results are confidential HQA guarantees confidentiality of data of participants Impossible for one participant to tell how another participant scored The Board of HQA does not know the results of any single participant, but only overall results Each HQA participant has the right to use the HQA logo in its marketing material – indicating to its members that it took part in the quality survey and that the Board and Scheme Management evaluates quality indicators as part of an industry initiative

6. Information and data Schemes are requested to present detailed data in four categories: Ambulatory care: pneumonia/influenza, heart failure, paediatric hospitalisation for G/E, UTI, suicide rate, pathology, preventative health, preventative health utilisation and depression Chronic diseases: COPD, ischaemic heart disease, diabetes, depression, asthma, HIV and bipolar/schizophrenia Hospitalisation: spinal fusions, hysterectomies, hip replacements, knee replacements, stents, by-pass grafts, tonsillectomies, myringotomy, pneumonia/influenza, heart failure, chemical dependence, depression, D&C non obstetric, perforated appendix Maternity and new born: deliveries, unintended pregnancies, antenatal care, teenage pregnancies Data was requested separately for each option.

7. Sources of reference Sources of reference: HEDIS Healthy People 2010 AHQR SA DOH Detailed technical and clinical workshops with industry players in January this year

8. Broad methodology Separate evaluation criteria from tracking indicators and monitoring indicators Quality ranking based only on evaluation criteria Evaluation criteria are risk-adjusted in two ways: Evaluate outcomes for defined population – e.g. compare diabetics only against diabetics, or those with spinal fusions against others with spinal fusions Within indicators where it makes sense, adjust further for age and gender (i.e. compare young diabetics against young diabetics)

9. Criteria for evaluation indicators Criteria for an evaluation indicator: It must be an indicator or proxy of health quality. Risk adjustment must be possible for the indicator. Data must be available in medical scheme databases Indicator calculation must be reasonably easy.

10. Broad methodology Once evaluation criteria defined – collect statistics and evaluate Express rank of each option, relative to others, for criteria Combine factors in overall ranks for: ambulatory care, chronic care, hospitalisation and maternity Plot rank of each option against contribution rank Now analyse underlying characteristics of options, e.g. PMB focused / comprehensive? Restricted / open Large / small Savings or not? Industry specific or not? DSP or not? Type of DSP reimbursement? – etc…

11. Assumptions & methodologyMethodology Normal Distribution (ND) factors: This is where high values and low values are undesirable. High values indicate relative over-servicing and low values indicate a possibility of denial of care. This is evaluated using the normal distribution. Average: 187 per 1,000 beneficiaries Standard deviation: 98.74. (after standardising)

12. Assumptions & methodologyMethodology Descending Value (DV) factors: this is where high values are undesirable and low values desirable, e.g. multiple admission rates. This is evaluated on a straight line basis.

13. Assumptions & methodologyMethodology Ascending Value (AV) factors: this is where low values are undesirable and high values desirable, e.g. percentage single day admissions.

14. Tracking / monitoring Indicators Tracking indicators: Ischaemic heart disease:Incidence per 1000 lives, prevalence per 1000 lives COPD :Incidence per 1000 lives GP visits per beneficiary for diabetics Etc. Health Status Lifestyle disease incidence per 1,000 lives CDL conditions proxy drug compliance Death rates Etc. These are not used in the quality rankings, but to monitor status of health over time – no need for risk adjustment

15. Evaluation Indicators Ambulatory care

16. Evaluation Indicators Ambulatory care

17. Evaluation Indicators Chronic diseases

18. Evaluation Indicators Chronic diseases

19. Evaluation Indicators Chronic diseases

20. Evaluation Indicators Hospitalisation

21. Evaluation Indicators Hospitalisation

22. Evaluation Indicators Hospitalisation

23. Evaluation Indicators Maternity and New born

24. Tracking Indicators Ambulatory care

25. Tracking Indicators Chronic diseases

26. Tracking Indicators Chronic diseases

27. Tracking Indicators Hospitalisation

28. Tracking Indicators Hospitalisation

29. Tracking Indicators Maternity and New Born

30. Health Status Indicators

31. Results – Ambulatory Preventative health (coverage)

32. Results – Ambulatory Preventative health

33. Results – Chronic diseases IHD (coverage)

34. Results – Chronic diseases Diabetes (coverage)

35. Results – Chronic diseases Asthma

36. Results – Hospitalisation Hip and knee replacement (average length of stay)

37. Results – Hospitalisation Stents and by-pass grafts (average length of stay)

38. Results – Maternity and new born Deliveries (average length of stay)

39. Results Observations: The plotted diamond shapes indicate a health quality and contribution rank pair for a particular option. The better the quality of health provided in an option, the higher the health quality rank. The higher the contribution, the higher the average contribution rank. In other words, more expensive options are reflected towards the upper part of the graph. The observed values with blue circles in indicate options with designated service provider networks. With more data, and more cleaned data, we can perhaps make more definitive statements about Relative quality of care with DSPs The influence of other product features on quality of care The relationship between cost and quality

40. Illustrative Results – Ambulatory care

41. Illustrative Results – Chronic Diseases

42. Illustrative Results – Hospitalisation

43. Illustrative Results – Maternity and new born

44. What can HQA tell you? How your scheme’s health outcomes compare to other schemes with similar underlying age structures And for the same population of chronic disease sufferers, or those hospitalised for a particular condition / treatment etc. And how this differs for those schemes with different benefit structures or different DSP arrangements or different target markets And how all of this compares given the contribution levied by your scheme

45. What HQA cannot tell you… Whether the quality of care provided under any one indicator is high or low by international / national standards: this is only a comparison against local schemes / options participating in the survey – it makes no value judgements about absolute levels of care But the more participants – the more reliable and representative the analysis Whether your scheme is a “better” scheme than another – many other issues to consider Whether your competitor X performed “better” or “worse” than you – impossible to tell from information provided

46. Where HQA might give you pointers in the right direction… The reason behind a low relative score on a particular indicator: May be unique to a specific population with e.g. occupation-related illness – some evidence of this in data submitted so far May be due to a product feature – e.g. high member co-payments or low limits or no cover May be due to treatment provided in a specific network arrangement The consequences of certain rationing decisions E.g. what is the relationship between LDL coverage, aspirin coverage, B-Blocker coverage and: admission rate and re-admission rate of IHD registered beneficiaries

47. Where HQA might give you pointers in the right direction… The REF!! Do some of the outcomes point to areas where you should manage certain conditions more actively / change your benefit structure / talk to your DSP Because your actual cost will be higher than what you are “compensated for” by the REF? Remember REF does not compensate for the cost in your scheme, but rather for the industry cost in a scheme with your demographic profile, given assumptions and policy decisions included in REF rate

48. Where HQA might give you pointers in the right direction… What drives your medical inflation rate: You will have tracking indicators & monitoring indicators, relative to all other participants All standardised for age & gender Giving some indication of where you might experience higher or lower costs And hence better understanding of why your medical inflation rate is where it is given increase in tariffs This could inform benefit structure and managed care decisions

49. The way forward Our biggest challenge so far has been data We are expecting data from a number of additional schemes We expect data to arrive up until the end of August We will then draft final reports for participants The data request is onerous, but once it is set up at an administrator, it becomes much easier to do subsequent extractions, or to do so for other schemes The data request itself will change marginally from year to year, but there hopefully won’t be further major structural changes Please contact us if you would still like to participate!

50. Questions Emile Stipp Tel 011 209 8102 E-mail estipp@deloitte.co.za Ashleigh Theophanides Tel 011 209 8112 E-mail atheophanides@deloitte.co.za