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

2. Solution: Case Mix and DRGs Case Mix in practice – some examples
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:

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
No change
Not as good
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. Solution: Case Mix and DRGs Case Mix in practice – some examples
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. Diagnosis Related Groups (DRG) logic: basic diagnosis with splits by co-morbidities and complications
Condition x
With minor C.C.*
With major C.C.*
Without C.C.*
*Co-morbidities or complications

10. e.g. Cardiac /Resp. failure
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
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
04383 – Asthma with MCCs
e.g. Cardiac /Resp. failure
The DRG Grouper groups data into DRGs using
diagnosis and procedure codes and age

11. Case weights are just averages
DRG average expenditure
22.80
98.80
15.20
38.00
Case weight
0.60
2.60
0.40
1.00
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
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
No CC
W CC
W M CC

13. When we look graphically at the components that make up an events.
We see that a drg w cc has a higher LOS , more nurse intensity and more consumbales and related resources.

14. Case Mix Index - definition
Example hospital ‘a’:
CMI = / 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. Solution: Case Mix and DRGs Case Mix in practice – some examples
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. Solution: Case Mix and DRGs Case Mix in practice – some examples
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. DRG application: Alternative Hospital Reimbursement
Gain to population from reduced expenditure
105
100 95
Gain to hospitals on increased margin 90
Costs - no intervention 85
Price: Current 80
Costs - Alternative Reimbursement
Price: Unchanged Margin 75
Price: hosp 50% share of margin 70
Also used for Budgeting and ‘Purchasing’
Year 0
Year 1
Year 2
Year 3
Year 4
Year 5
Year 6
Year 7

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

25. Human Resource Planning Problem Statement:
Current model:
Based on SUPPLY:
Levels of care
based on
Available services
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
Case Mix
Hospital beds
Clinical staff
Iterative management
Case Mix load
Beds:
general; specialised; step down
Staff: medical; nursing; other
Production: throughput (numbers, case type) and outcomes
Measure:
Actual vs. expected
Planning

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

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

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. Solution: Case Mix and DRGs Case Mix in practice – some examples
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; disposition Resources 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. Disposition of patients:
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. Brian Ruff ~ brianru@discovery.co.za
Thank You
Brian Ruff ~