Economic evaluation of health programmes

1. Economic evaluation of health programmes Department of Epidemiology, Biostatistics and Occupational Health Class no. 11: Cost-utility analysis – Part 4 Oct 8, 2008

2. Plan of class • Finish material from last class • Preference-based generic instruments • Construction of QALYs • Limitations of QALYs • QALYs vs DALYs

3. Preference-based generic instruments: Purpose • SG, TTO difficult and costly to use • One would prefer a simpler instrument • Administer to subjects in a study to evaluate their health-related quality of life as rated by a community sample

4. Preference-based generic instruments: 2 steps in use QUESTIONNAIRE THAT ASKS AT WHICH OF 3 TO 6 LEVELS RESPONDENT IS ON 5 TO 15 DIMENSIONS FORMULA FOR CONVERTING RESPONSES INTO A HEALTH RELATED QUALITY OF LIFE WEIGHT FROM 0 TO 1 (VALUE OR UTILITY DEPENDING ON QUESTIONNAIRE)

5. Questionnaire design • Obvious differences: • Number and choice of dimensions • Number of levels for each dimension

6. Note: At least two other questionnaires exist: Australian Quality of Life (AQoL) and the Finnish 15D. Not as widely used as EQ-5D, SF-6D or HUI2 or HUI3. Not discussed in class.

7. Health as a spectrum Disease or disorder Impairment Ability Participation Role, social and usual activities Pain/ Dexterity Limits Walking Rheumatism Macular degene- ration Role, social and usual activities Limits ability to read Vision WHO international classification of health into disease or disorder, impairment, ability and participation (with examples). (Taken from Brazier et al., Measuring and valuing health benefits for economic evaluation, Oxford, 2007, Fig 4.1 )

8. SF-6D, EQ-5D, HUI2 HUI3 Disease or disorder Impairment Ability Participation Role, social and usual activities Pain/ Dexterity Limits Walking Rheumatism Macular degene- ration Role, social and usual activities Limits ability to read Vision

9. Include dimensions relating to social participation? • “Within skin” aspects of health: avoid measuring peoples’ choices/preferences • “purer” measure of health • No influence of adaptation • But general population values will underestimate adaptation • Health is a means, social participation part of its end – this is what matters to patients

11. Scoring the questionnaires • In each case, use a method such as SG, TTO, VAS to value some states, and interpolate statistically • Too many states to value them all individually! • Two approaches to developing scoring methods: • Multi-attribute utility theory (MAUT): HUI2, HUI3 • Statistical estimation without restrictive assumptions of MAUT: QWB, SF-6D, EQ-5D

12. Multi-attribute utility theory: The problem • What happens when lottery outcome yields something that has several attributes, such as mobility, emotional state, etc? • How to combine the utilities of separate dimensions of outcome to generate an overall utility of the outcome?

13. Example • How would you combine utilities derived from an apartment that you might rent? Attributes include: (a) price; (b) location; (c) size; (d) quietness; (e) attractiveness; (f) other factors.

14. 3 most common methods based on MAUT • In all cases, need to calculate utility associated with each dimension • Additive, multiplicative, multilinear (see formulas in book, p. 157) • The simpler the method, the more restrictive the assumptions • e.g., additive implies no interactions • HUI2 and HUI3 use multiplicative formula

15. Exercises • On the EQ-5D, considering Table 6.4, what does score 11212 mean? What health-related quality of life weight does this represent? • On the HUI3, same questions for 22111223.

16. Choice of instrument matters • Different instruments yield different results • Different ranges: -0.4 to 1.0 for EQ-5D, vs. 0.3 to 1.0 for SF-6D • EQ-5D scores of 11111 can translate to SF-6D scores as low as 0.56 • Studies comparing scores across instruments for same patients find significant differences • Patient group appears to be a factor • Differences as small as 0.03 should be considered significant

17. Reasons for differences • Differences in coverage • Capacity vs functioning • Symptoms, social health, mental health covered differently • Sensitivity of dimensions • Floor effect for physical and social functioning, role limitations for SF-6D • Ceiling effect with EQ-5D • Valuation methods • Systematic differences depending on method

18. Choosing a method: Practicality

19. Choosing a method: Reliability • All have acceptable test-retest reliability • Different responses depending on whether patients or health professionals fill out – need to standardize to whom instrument administered

20. Choosing a method: Validity • QWB based on VAS • HUI2 and HUI3 based on SG but as transformation of VAS; not clear this is better than TTO used in EQ-5D • Populations from which data for scoring formulas derived are more or less comprehensive – more limited for HUIs, very broad for EQ-5D • Unclear how important this is

21. Choosing a method: Conclusions • Differences in dimensions covered, number of levels, floor and ceiling effects may make one of the instruments more suitable for a particular patient group • Which would you use for assessing cataract surgery? Antidepressants? • Use HUI3 rather than HUI2 • Don’t use QWB

22. A QALY exercise • With new cancer protocol: 6 months at HRQOL 0.3, followed by 15 years at 0.95 • With standard treatment: 1 year at 0.5, followed by 7 years at 0.90, then 1 year at 0.8, 1 year at 0.5, then death • How many QALYs does the new protocol produce?

23. Limitations of QALYs (partial list) • Ignore priority often given to helping people at low initial state • Many small improvements to people at high initial state can be preferred to saving a life • Imperfectly measured • Use anyway?

24. QALYs vs DALYs (Disability-adjusted life years) DALYs developed to do estimate potential impacts of possible health interventions in developing countries