Managed care reporting Is managed care adding value? Dr Andrew good - prognosys

1. Managed care reportingIs managed care adding value?Dr Andrew good - prognosys

2. Outline of presentation • Overview of South African health systems and trends • The importance of measuring value – How do we define value? • Managed care financial reporting – Is information readily available to trustees to compare the performance of managed care programmes? • Results of a Prognosys research exercise to analyse the financial performance of a managed care company using publically available data.

3. State of South African healthcare We have presented previous research that showed that South African health systems are failing State sector Private sector Policies good Lack of focus on primary care Implementation poor Hospital / specialist focus Resources very limited Fragmentation of care Affordability under pressure The WHO 2008 report: Primary Health Care (Now More Than Ever) details three trends that undermine the delivery of health outcomes: • Hospital centrism • Fragmentation in approach • Commercialisation in unregulated systems Presenter logo to come here

4. Private healthcare trends Presenter logo to come here

5. State sector – voting with their feet Presenter logo to come here

6. How is value defined? – The Value Agenda • Should the goal be cost management? • Should the goal be improved access? • Should the goal be maximising profits? • Should the goal be quality at any price? The goal must be value Presenter logo to come here

7. Managed care in South Africa • Who is South Africa’s best HIV manager? • Who is South Africa’s best Diabetes Mellitus manager? • Who is South Africa’s best hospital risk manager? • Who is South Africa’s best medicine risk manager? • Who is the best provider of primary health care networks? Presenter logo to come here

8. How do we measure who is best? • Productivity – meeting SLAs • Financial outcomes – effective cost management • Clinical outcomes – showing value Presenter logo to come here

9. Some thoughts • Productivity – general productivity: Limpopo school text book analogy • Financial outcomes – low level of information: is enough information available • Clinical outcomes – dealt with by another speaker Presenter logo to come here

10. Research – CMS data • Background to research • Challenge with research • Process • Methodology • Results • Next steps Presenter logo to come here

11. Research – Background • Challenged MCO to do put their “money where their mouth is” • Project funded • CMS data used Presenter logo to come here

12. Research – Challenges • Limited data • Actuarial oversight – risk adjustment / benefit adjustment • Statistical oversight – is the methodology statically sound • Clinical oversight – does the research make sense Presenter logo to come here

13. Research – Methodology • Schemes joining and leaving • Clustering of schemes and options • Adjust for risk – avoid duplication implicit within option clustering • Run models • Result sign-off Presenter logo to come here

14. Research – Statistical Methodology • Linear Regression Analysis – Multiple specifications • Requires all variables relating to: • Attributes of MCO clients – Measurement problem • Hospital costs • Measurement problem: Benefit design unmeasurable • Solution: Cluster schemes based on proxies for “benefit richness” and “administrative richness” Presenter logo to come here

15. Research – Statistical Methodology • Variables Used in Regression: • Year indicators – control for hospital cost inflation • Restricted scheme indicator – controls for anti-selection • Demographics variables – Lives • Clinical risk variables – Beneficiaries admitted (hospital, high care, renal dialysis, ICU), Pregnancies • Cluster variables – proxy for benefit richness • MCO indicator – independent variable of interest • Cluster MCO indicator – test whether MCO has a significantly different impact on some clusters than on others Presenter logo to come here

16. Research – Results: context • Measuring the performance of managed care initiatives is key • These comparisons are complex and open to criticism • Progress in measuring the performance of managed care and debating how this is best to compare performance is not an option • The management team at the client believe that they add value to schemes • We have had additional input on our model specification from the Department of Economics at Stellenbosch University • We hope that this report opens up the debate around managed care • We welcome input, commentary and criticism that promotes the dialogue Presenter logo to come here

17. Research – Results: summary • Medical schemes may be grouped together (clustered) and the cluster used as a proxy for benefit design • 4 Clusters identified and named: • Cluster 1: Basic Benefits • Cluster 0: Extended Benefits • Cluster 3: Comprehensive Benefits • Cluster 2: Premium Benefits Presenter logo to come here

18. Research – Results: summary Presenter logo to come here

19. Research – Results: summary • Results reported robust to specification • There is a statistically significant probability that being a client of X reduces hospital costs compared to not being a client if the client is in cluster 0 (extended basic benefits) or cluster 3 (comprehensive benefits) • It is estimated that the average scheme that is an X client and offers extended basic benefits or comprehensive benefits will save about 20% on hospital costs per beneficiary per annum compared to when the same scheme is not be a client of X Presenter logo to come here

20. Research – results: graphically Presenter logo to come here

21. Next steps • We need debate • We need more research into this • We need agreed models • We need benchmarked financial measures to become standard in managed care reporting • We also need standard productivity measures and outcomes measures • Purchasing decisions should be linked to performance Presenter logo to come here

22. Questions? Dr Andrew Good agood@prognosys.co.za / 072 797 7279 THANK YOU