1. A METHODOLOGY FOR MEASURING THE COST- UTILITY OF EARLY CHILDHOOD DEVELOPMENTAL INTERVENTIONS Quality of improved life opportunities (QILO)

2. Why Do We Need Economic Analysis?  Evaluate political policies (economic perspective)  Realisation of benefits for participants, their families, and the community  Attract further investment (private and public)  To evaluate the efficiency of programs (prioritisation of resources)  Effectiveness = $ Savings and Benefits

3. Benefits and Savings

4. Current methods  Cost Analysis  Cost-Effectiveness Analysis  Cost-Savings Analysis  Cost-Benefit Analysis

5. Governmental Perspective  Governmental Perspective  Short and long term benefits or savings to government “Might government funds invested early in the lives of children yield compensating decreases in government expenditures”?

6. Problems with this approach –Unable to measure disparate programs –Frames the case for developmental prevention too narrowly –Disjuncture between program objectives and program evaluation criteria –Neglects potential benefits with important consequences for society at large  Improved public safety  Living an effective an productive life

7. The societal perspective  Identifying a common metric outcome  A holistic approach to valuing benefits on an individual level.  Measures benefits across multiple domains, at different times, but still on an individual level.  Possibility of valuing alternative life courses.

8. Adaptation of QALYs  Help us make better resource allocation decisions  Choices between groups (clientele/patient) competing for specific forms of care are made explicit  Prioritisation of resources  Provides another piece in the complex jigsaw puzzle.

9. Concept behind QALYs  Common metric for assessing the extent of benefits gained from a variety of interventions  Quantity and quality of life gains

10. Quantity and quality of life  A QALY places a weight on time in different health states  Quantity of life is expresses in terms of survival or life expectancy  Quality of life embraces not only health status but also a range of other health states e.g. physical and mental capacity

11. Measuring Quality of life  Standard gamble  Time trade-off  Rating scales  Mulitattribute utility functions

12. Utilities  Utilities produced represent valuations attached to each health state  Continuum between 0 &1

13. Instruments that produce utilities  EQ-5D  SF-36  Health Utilities Index (HUI1)(HUi2)(HUI3) (HUI1)(HUi2)(HUI3)  EuroQol-5D

14. Instruments that produce utilities

15. Arriving at QALY Benefits (QALYs)= Number of QALYs saved through preventing or delaying premature death + number of QALYs gained through illness avoided or delayed - number of QALYs lost from side effects - loss of benefits from substitution for other drugs or treatment regimes

16. Arriving at QALY

17.   Amount of time spent in health state is weighted by the utility score given to that state

18. Arriving at QALY   Data relating to Health Related Quality of Life = Impact of intervention on an individual patient (with and without intervention)

19. Arriving at QALY

25. Cost utility ratio  Difference between the costs of two interventions divided by the difference in the QALYs they produce

26. Cost utility ratio 2  E.g. Treatments for a disease T1 & T2 T1 generates 0.5111 QALYs T2 generates 0.6016 QALYs  T1 QALY – T2 QALY = 0.0905 QALYs  33 days of perfect health (0.0905 x 365)  Addition cost of T2 = $220/patient  Therefore it costs $2,431 (220/0.0905) to generate an additional QALY by using T2

27. Where to? –Adapting the methodology (QILO) –Framing and designing the study –Estimating costs (using methodology developed by Manning, 2004) –Discounting costs –Identifying relevant outcomes –Describing the element states and their possible course over time for individuals who receive the intervention and for those who receive each alternative. –Attain weights for various states (survey) –Combining the elements of each state (measures of effectiveness) into a single number reflecting the value assigned to that state (Multi-attribute utility) –Integrating the values assigned to the states –Estimating the probabilities of each outcome –computing a numerical average outcome for each of the alternatives being compared.