1. Outcomes in Decision Analysis: Utilities, QALYs & DALYs, and Discounting DCEA 24 January 2013 James G. Kahn

2. Overview  Back to the aneurysm example:  To Clip Or Not To Clip?  Clinical Outcomes  Utilities and utility measurement  Direct  Indirect  QALYs (& DALYs)  Discounting

3. Review—Last Lecture Formulated an explicit question Formulated an explicit question “to clip or not to clip” (incidental aneurysm) “to clip or not to clip” (incidental aneurysm) Made a simple decision tree Made a simple decision tree Conducted an expected value calculation to determine which course of action would likely yield the highest life expectancy Conducted an expected value calculation to determine which course of action would likely yield the highest life expectancy

4. To Clip or Not To Clip.865 vs.977 =1.0 =.55 =.9921 =.977 Diff = -0.0151 =0

5. To Clip or not to Clip? Has an impact on life expectancy Has an impact on life expectancy Also actual clinical outcomes: Also actual clinical outcomes: Surgical death Surgical death Aneurysm rupture Aneurysm rupture Death from aneurysm rupture Death from aneurysm rupture Neurologic Injury Neurologic Injury Major Major Minor Minor Fear of aneurysm rupture Fear of aneurysm rupture

6. Quantifying Health Outcomes Mortality Life Years number of expected years of life Significant Morbidity Paralysis, loss of sight Quality Adjusted Life Years Life years adjusted for value of health state Disability Adjusted Life Years Disease burden – lost years + disability Financial Valuation of Outcomes Costs to patient, payer, or society Willingness to pay to avoid outcomes

7. Health Outcomes – Mortality Mortality Mortality Death from disease/accident/procedure e.g. If Ms. Brooks undergoes surgery, one of the possible outcomes is mortality Life Years Life Years Calculate an expected value of life years using a probabilistically weighted average of expected life e.g. If Ms. Brooks does not undergo surgery, her life expectancy is less than if she did not have aneurysm, these outcomes are measured in expected life years

8. Health Outcomes – Morbidity Morbidity Morbidity Some health state that is less than perfect e.g. disability from stroke, chronic pain Comparison of morbidities Comparison of morbidities Difficult – apples and oranges problem e.g. which is worse: Blind v. Deaf Deaf v. Paraplegia Paraplegia v. Blind

9. To Clip or not to Clip? Clinical outcomes for clinician readers Clinical outcomes for clinician readers Outcomes may affect health-related quality of life: how do we compare? Outcomes may affect health-related quality of life: how do we compare? Neurologic injury can cause mild/moderate disability Neurologic injury can cause mild/moderate disability Not clipping can cause anxiety associated with being at risk of aneurysm rupture Not clipping can cause anxiety associated with being at risk of aneurysm rupture Outcomes may occur at different times Outcomes may occur at different times

10. How do we incorporate quality-of-life effects into decision analysis? Measure/estimate and apply health state utilities Measure/estimate and apply health state utilities Use utilities to quality-adjust life expectancy for decision and cost-effectiveness analysis Use utilities to quality-adjust life expectancy for decision and cost-effectiveness analysis

11. Preview—Where We Are Going with this Analysis? Recall Ms. Brooks and her incidental aneurysm -- to clip or not to clip? We want to: Determine her utilities Determine her utilities Use them to generate QALYs Use them to generate QALYs Evaluate incremental QALYs and cost (CEA/CUA) Evaluate incremental QALYs and cost (CEA/CUA) Compare incremental cost effectiveness ratios (ICER) to other currently accepted medical interventions Compare incremental cost effectiveness ratios (ICER) to other currently accepted medical interventions

12. What is a Utility? Utility - Quantitative measure of the strength of an individual’s preference for a particular health state or outcome. Utilities can be obtained for: * Disease states (diabetes, depression) * Treatment effects (cure, symptom management) * Side effects (impotence, dry mouth) * Process (undergoing surgery, prenatal diagnostic procedure)

13. Utilities Utilities are the currency we use to assign values to outcomes Scaled from 0 to 1 1 = perfect or ideal health or health in the absence of the condition being studied 0 = death

14. How are utilities measured? Direct – compare with 0 / 1 anchors Direct – compare with 0 / 1 anchors - Visual Analog Scale - Visual Analog Scale - Standard Gamble - Standard Gamble - Time Trade-off - Time Trade-off Indirect Indirect Assess standard health domains (e.g., physical functioning, pain, and cognition) and calculate 0-1 utility with an equation. Assess standard health domains (e.g., physical functioning, pain, and cognition) and calculate 0-1 utility with an equation.

15. Direct utility measurement

16. BKA vs. AKA Example Patient in hospital has infection of the leg Two options: 1) BKA – below knee amputation BKA –1% mortality risk BKA –1% mortality risk 2)Medical management – 20% chance of infection worsening and needing AKA (above the knee amputation), 10% mortality risk 2)Medical management – 20% chance of infection worsening and needing AKA (above the knee amputation), 10% mortality risk

17. For which outcomes do we need to measure utilities? Living without part of a leg (below the knee) Living without part of a leg (below the knee) Living without a bigger part of a leg (above the knee) Living without a bigger part of a leg (above the knee) Pain Pain Worry Worry Other Other

18. Visual Analog Scale 100 98 2 0 99 65 55 1 Full health: intact leg Dead BKA Outcomes rated on a 0-to-100 “feeling thermometer.” AKA

19. Standard Gamble What chance of immediate death would you be willing to incur to avoid living with the outcome being assessed? Method relies on respondents choosing between: 1) a certain outcome (BKA) 1) a certain outcome (BKA) 2) a gamble between an ideal outcome (intact leg) and the worst outcome (dead) 2) a gamble between an ideal outcome (intact leg) and the worst outcome (dead)

20. Standard Gamble Question Death Perfect Health

21. xercise Standard Gamble Exercise Spend the rest of your life with BKA ] immediate death [p]% chance of immediate death 1-[p]% chance of spending the rest of your life with an intact leg Which do you prefer? Choice AChoice B

22. Standard Gamble Standard gamble measurement involves questioning patients to determine the p at which the two outcomes are equivalent Using expected utilities, the value of p implies the utility Utility (BKA) x Prob (BKA) = Utility(cure) x (1-p) + Utility(death) x (p) Thus, if utility of cure = 1 and of death = 0, the utility of BKA = 1-p.

23. Time Tradeoff How many years of your life would you be willing to give up to spend your remaining life without the condition/health state being assessed? Method relies on respondents choosing between: 1) Full life expectancy with the condition/outcome being assessed (BKA) 1) Full life expectancy with the condition/outcome being assessed (BKA) 2) A reduced life expectancy with the ideal outcome (intact leg) 2) A reduced life expectancy with the ideal outcome (intact leg)

24. Time Tradeoff Preference Elicitation Spend the remaining 40 years of your life with BKA Live 40 more years of life with an intact leg (give up 0 years of life) Which do you prefer? Choice AChoice B

25. Time Tradeoff Preference Elicitation Spend the remaining 40 years of your life with BKA Live 30 more years of life with an intact leg (give up 10 years of life) Which do you prefer? Choice AChoice B

26. Utility Measurement – Time Trade-off Find years of life at which patient is indifferent between Choice A (with health problem) & Choice B (shorter life). We assume that: Time A * Utility A = Time B * Utility B And thus Utility A = [Time B * Utility B] / Time A If willing to give up 4 years to avoid BKA: Utility of BKA = [(40-4) * 1] / 40 = 36/40 = 0.9

27. Pros and Cons - VAS Advantage: Easy to understand Disadvantages: Doesn’t require the respondent to: - Think about what they’d be willing to give up - Think about what they’d be willing to give up - Explore risk preference - Explore risk preference Values spread over the range

28. Pros and Cons – SG Advantages: Requires assessor to give something up, incorporates risk attitude Disadvantages: Choices may be difficult to make Most confusion-prone method Lack of engagement or willingness to participate in exercise Utility values tend to cluster near 1

29. Pros and Cons – TTO Advantages: Still asking assessor to give something up Easier choices than SG. Values not so clustered near 1 Disadvantages: Fails to incorporate risk Lack of clarity of when time traded occurs Isn’t something that one can choose to give up. (One can take on a risk of death, but not “pay with life years.”)

30. Indirect measures of utility First assess features of health using standard domains (attributes) respondents complete a questionnaire Then calculate utility (0 - 1) with equation score using a “multi-attribute scoring function” derived from community preferences for health states defined by these attributes

31. http://www.healthutilities.com/hui3.htm

32. Source: Arnold 2009 BMJ

33. Utilities in decision analysis Utilities are used to add morbidity effects to life expectancy. Utilities are used to add morbidity effects to life expectancy. Quality Adjusted Life-Years (QALYs) (we’ll return to DALYs later) Quality Adjusted Life-Years (QALYs) (we’ll return to DALYs later)

34. QALYs QALYs are usually considered the standard unit of comparison for outcomes for CEAs in OECD QALYs are usually considered the standard unit of comparison for outcomes for CEAs in OECD QALYs = time (years) x quality (utility) QALYs = time (years) x quality (utility) e.g. 40 years life expectancy after AKA, e.g. 40 years life expectancy after AKA, utility (AKA) = 0.9 utility (AKA) = 0.9 = 40 x 0.9 = 36 QALYs (undiscounted) = 40 x 0.9 = 36 QALYs (undiscounted) Mortality lowers LY, morbidity lowers QA Mortality lowers LY, morbidity lowers QA

35. Back to aneurysm

36. Now we want to add utilities for intermediate outcomes Normal survival 1.0 Worry about possibility of aneurysm rupture 0.95 Stroke utility (clipping compli- cation or aneurysm rupture) (0.76+.25)/2=0.5 Survival adjmt due to stroke 0.33 Immediate death 0.0

37. Including utility for early death and disability due to stroke

38. Adding utility for worry =.95 (in No surgery arm)

39. Outcomes - Discounting Aneurysm Example Aneurysm Example We said since life expectancy is reduced by 2/3, so instead of 35, it is = 35 *.333 = 11.67 We said since life expectancy is reduced by 2/3, so instead of 35, it is = 35 *.333 = 11.67 However, are all years considered equal? However, are all years considered equal? Consider: Favorite Meal Consider: Favorite Meal Extreme Pain Lifetime Income

40. Outcomes - Discounting Generally, present value more than future Generally, present value more than future One way to value the different times is discounting One way to value the different times is discounting Essentially this year is worth D more than next year Essentially this year is worth D more than next year D (annual discount rate) usually set at 3% D (annual discount rate) usually set at 3% To compare values of all future times, a calculation, net present value, is often used To compare values of all future times, a calculation, net present value, is often used NPV = 1 / (1 + D) t Where t is number of years in the future NPV = 1 / (1 + D) t Where t is number of years in the future

41. Outcomes - Discounting Aneurysm Example Aneurysm Example If utility is 0.6 and life expectancy is 3 years If utility is 0.6 and life expectancy is 3 years NPV would be:  Utility / (1 + D) t or NPV would be:  Utility / (1 + D) t or NPV = 0.6 / 1 + 0.6 / (1.03) 1 + 0.6 / (1.03) 2 However, since events in year 1 occur on average half way through, we can use 0.5 for year 1: However, since events in year 1 occur on average half way through, we can use 0.5 for year 1: NPV = 0.6 / (1.03) 0.5 + 0.6 / (1.03) 1.5 + 0.6 / (1.03) 2.5

42. Outcomes - Discounting

43. QALYs vs. DALYs “Quality Adjusted Life Years” (QALYs) came first; still used for CEAs in OECD measure of health. An illness which shortens life by 2 years and lowers “health status utility” by 20% for 5 years decreases QALYs by -2 - 0.2 * 5 = -3 Interventions are designed to increase QALYs “Disability Adjust Life Years” (DALYs) most common health metric in global health. measure of disease burden – i.e., the negative of QALYs. An illness which shortens life by 2 years and raises “disability” by 20% for 5 years increases DALYs by 2 + 0.2 * 5 = 3 Interventions are supposed to avert DALYs.

44. Geographic setting MeasuresComponentsGoal is to: Quality-Adjusted Life Years (QALYs) U.S., Europe, and other OECD countries Health status “LY” is gain in life years due to intervention. “QA” is gain in health status utility* due to better health. Gain Disability- Adjusted Life Years (DALYs) Global, and developing world Disease burden “LY” is life years lost due to premature death. “DA” is disability* due to morbidity. Avert * In practice, methods to estimate disability weight and health status utility often overlap, relying on similar elicitation of expert or patient or population opinion.

45. Excel workbook

46. Exponential Discounting Exponential discounting first described in 1937* Mathematically easy to manipulate Assumed discounting in “simple regular fashion” Does not differentiate difference between: Today vs. tomorrow Ten years vs. ten years plus one day *Samuelson PA. A Note on Measurement of Utility. Rev Econ Stud 1937;4:155-61

47. Overall Review Outcomes - Clinical Outcomes - Clinical Mortality - timing Morbidity – severity, duration, timing Measuring Utilities Measuring Utilities Direct – TTO most often Indirect – may underestimate utility QALYs - health, DALYs – disease burden QALYs - health, DALYs – disease burden Discounting Discounting NPV =  Utility / (1 + D) t