Case Mix and managing health systems Dr Brian Ruff Discovery Health South Africa April 2011

1. Case Mix and managing health systems Dr Brian Ruff Discovery Health South Africa April 2011

2. AGENDA • How to measuring hospital efficiency: accounting for the mix and severity of cases • Solution: Case Mix and DRGs   • Case Mix in practice – some examples • Using Case Mix information: tracking and planning • The Key requirement: patient level clinical data

3. Measuring the hospital systems production: N

4. Measuring the hospital systems production: = expected average Production cost i.e. the mix and severity of admissions

5. Measuring the hospital systems production: No longer a problem Not as good No change Now problem Now problem Not as good N N N Different picture emerges

6. Case Mix solves: • How to compare relative efficiency of different hospitals ~ are we getting value for money? • Simple average cost per admission is misleading – because of the different complexity of cases • Solution – adjust for “case mix” • DRGs are the tool of Case Mix – they provide a mechanism of deriving meaningful benchmark cost for types of cases; in composite at a facility level they provide a measure of its ‘case mix’ i.e. Its load

7. AGENDA • How to measuring hospital efficiency: accounting for the mix and severity of cases • Solution: Case Mix and DRGs • Case Mix in practice – some examples • Using Case Mix information: tracking and planning • The Key requirement: patient level clinical data

8. Introduction to Hospital ‘Case Mix’ • Case Mix information about patient care makes hospital management possible: • The mixture of patients treated in two hospitals may differ significantly. E.g. district hospital vs. a tertiary academic hospital • The severity of patients at two hospitals may also differ. E.g. one treating pensioners with multiple co morbidities while the other treating young and otherwise healthy patients • Mix and Severity = the case mix of a hospital: • “Why” patient is in hospital – Demand side: characterise need for care from underlying disease profile - i.e. ICD 10 coded diagnoses • “How” are they being treated – Supply side resources consumed – facilities; pharmaceuticals; clinical effort i.e. Procedures, Drugs, Wards • Allows benchmarking ~ fair, ‘like-with-like’ comparisons: • Cost and Quality of care (complications; death etc)

9. With minor C.C.* Without C.C.* With major C.C.* Diagnosis Related Groups (DRG) logic: basic diagnosis with splits by co-morbidities and complications Condition x *Co-morbidities or complications

10. DRG algorithm ICD 10 diagnosis codes Diagnosis code MDC Major Disease Category 04 - Respiratory CPT 4 or ICD 9 CM procedure codes No Procedure Procedure Base DRG Medical Base DRG Surgical Base DRG 0438 - Asthma ICD 10 diagnosis codes Full DRG Co-morbidity and Complication code 04381 – Asthma without CCs or e.g. Diabetes; Epilepsy Full DRG with Severity level 04382 – Asthma with CCs or e.g. Cardiac /Resp. failure 04383 – Asthma with MCCs The DRG Grouper groups data into DRGs using diagnosis and procedure codes and age

11. Case weights are just averages Average expenditure per DRG calculated Case weight = DRG ave resource / sample average DRG 1 DRG 5 DRG 11 SAMPLE AVERAGE Dummy data used

12. Average Cost and LOS by Severity Cost and LOS by Severity 7.00 25,000 6.00 20,000 5.00 15,000 4.00 3.00 10,000 Cost 2.00 LOS 5,000 1.00 0.00 0 No CC W CC W M CC

14. Case Mix Index - definition Example hospital ‘a’: CMI = 404.85 / 365 = 1.11; i.e. hospital ‘a’: case mix is 11% higher than the average hospital. We thus expect it to thus cost 11% more than average, so if the hospital cost is 20% higher than average, the difference is a measure of its inefficiency; or if its less than 11% it reflects relative efficiency.

15. AGENDA • How to measuring hospital efficiency: accounting for the mix and severity of cases • Solution: Case Mix and DRGs   • Case Mix in practice – some examples • Using Case Mix information: tracking and planning • The Key requirement: patient level clinical data

16. Illustration: Case Mix of orthopaedic units in 3 hospitals

17. Analytic ‘drill down’ example: Hysterectomies: e.g. haemorrhage e.g. cardiac failure

18. Hysterectomy analysis continued Identifying variation

19. ‘Drill down’ KZN: Hospital 4:

20. AGENDA • How to measuring hospital efficiency: accounting for the mix and severity of cases • Solution: Case Mix and DRGs   • Case Mix in practice – some examples • Using Case Mix information: tracking and planning • The Key requirement: patient level clinical data

21. Using Case Mix for Management:~ tracking and purchasing~ human resource planning~ measuring quality

22. Routine tracking reports

23. Gain to population from reduced expenditure Gain to hospitals on increased margin Costs - no intervention Costs - Alternative Reimbursement Price: Current Price: Unchanged Margin Price: hosp 50% share of margin DRG application: Alternative Hospital Reimbursement 105 100 95 90 85 80 75 70 Year 5 Year 6 Year 7 Also used for Budgeting and ‘Purchasing’ Year 0 Year 1 Year 2 Year 3 Year 4

24. Alternative Reimbursement Contracts in practice Network A Network A Experience Experience 100% 10,400 90% 10,350 80% 70% 10,300 60% 10,250 100% 50% 94% 95% 80% 10,200 40% 72% 30% 10,150 20% 10,100 10% Billed New Model 10% 10% 0% 10,050 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Q 1 Q2 Q3 Q4 Q1 2000 2001 2002 2003 2004 2005* 2006* Q1_2005 Q2_2005 Q3_2005 Q4_2005 Q1_2006 Fee For Service Per Diem DRG Demonstrates billed saving vs. predicted model

25. Human Resource PlanningProblem Statement: • Current model: • Based on SUPPLY: • Levels of care • based on • Available services • based on • Clinical expertise • determines • Capacity • trusts • Acuity • Alternative Model: Based on DEMAND • Burden of disease • leads to • Case Mix • assessed by • Severity and Volume • determines • Expertise & Staff Ratio • enables • Monitoring & resource planning Self justifying (supply side capacity is validated by supply side capacity) Case Mix (determines structure)

26. Human resource planning model Iterative management Planning

28. Relationship between case mix and need for beds and staff More Bigger same

29. 300 250 R = 85% 2 200 150 Expected 100 1 star 2 stars 3 stars 50 0 0 50 100 150 200 250 Actual Quality assessments: Actual vs. expected deaths and complications

30. Risk adjusted purchasing: • DRG implementation by country: • USA 1983 • Sweden 1985 • Finland 1987 • Portugal 1989 • Canada 1990 • UK 1992 • Australia; Ireland 1993 • Italy; Belgium 1995 • France 1997 • Denmark; Norway 1999 • Singapore early 2000’s • Netherlands; Germany; Japan 2003 • Others countries with pilots or investigations: • China; Russia; Brazil ; Malaysia; Thailand etc Analysing Changes in Health Financing Arrangements in High Income countries: Busse et al 2007 World bank HNP:

31. AGENDA • How to measuring hospital efficiency: accounting for the mix and severity of cases • Solution: Case Mix and DRGs   • Case Mix in practice – some examples • Using Case Mix information: tracking and planning • The Key requirement: patient level clinical data

32. Implementation of a system to measure & monitor • ‘Case Summaries’ with standard data elements is key: • On admission: • Symptom codes; admitting diagnosis; trauma and external causes; present on admission • On discharge: • Principal ‘resource driver diagnosis’; hospital complications; dispositionResources used – ward; ICU days, theatre time; costly radiology and drugs • Report dependent on: • quality of data, consistent data collecting over time, with feedback reports and consequences: • Improves the quality of data • Increase the value of data

33. Patient Discharge Summary Hospital to provide Discovery can code and capture Resource used: General ward; ICU; HC; theatre time; major radiology; etc

34. Associated data: • Origin of patients: • OPD; casualty; ambulance; other hospital • Disposition of patients: • home, tertiary hospital, step down, mortuary • Trauma burden: • assaults, MVA, falls etc • HIV and TB burden: • underlying respiratory and other diagnoses • Quality indicators: • Complication and Readmission and Mortality rates

35. Thank You Brian Ruff ~ brianru@discovery.co.za