1 / 70

Eran Bendavid

When Rationality Falters: Limitations and Extensions of Decision Analysis. Eran Bendavid. Experiment Part 1. Assume that the United States is preparing for the outbreak of an unusual Icelandic disease, which is expected to kill 600 people in the absence of intervention.

emmanuel-manning
Download Presentation

Eran Bendavid

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. When Rationality Falters: Limitations and Extensions of Decision Analysis Eran Bendavid Decision and Cost-Effectiveness Analysis

  2. Experiment Part 1 • Assume that the United States is preparing for the outbreak of an unusual Icelandic disease, which is expected to kill 600 people in the absence of intervention. • Two alternative programs to combat the disease have been proposed. Assume that the exact estimates of the programs are as follows: Decision and Cost-Effectiveness Analysis

  3. Experiment 1 • If program A is adopted, 200 people will be saved. • If program B is adopted, there is 1/3 chance that 600 people will be saved and 2/3 probability that no people will be saved. Decision and Cost-Effectiveness Analysis

  4. Experiment 1 – Switch Groups • If program A is adopted, 400 people will die. • If program B is adopted, there is a 1/3 chance that nobody will die, and 2/3 chance that 600 people will die. Decision and Cost-Effectiveness Analysis

  5. Experiment 2 – Everyone • Imagine yourself $3000 richer than you are right now. You have to choose between (a) a sure gain of $1000, (b) a 50% chance of gaining $2000 and 50% of gaining nothing. • Imagine yourself $5000 richer than you are right now. You have to choose between (a) a sure loss of $1000, (b) a 50% chance of losing nothing and 50% chance of losing $2000. Decision and Cost-Effectiveness Analysis

  6. Cartoon Decision and Cost-Effectiveness Analysis

  7. Three Topics • Frames • Equity • Economic epidemiology Decision and Cost-Effectiveness Analysis

  8. Normative Problem Formulation • Classical decision theory axioms • Ordering of preference • Transitivity of preference • Quantification of judgment • Comparison of alternatives • Substitution • Cost benefit rationale “Risky prospects arecharacterized by their possible outcomes and by the probabilities of these outcomes. The same option, however, can be framed or described in different ways.” -- Tversky & Kahneman, 1981 Decision and Cost-Effectiveness Analysis

  9. Formulation Effects • Positive formulation • Keep the status quo • Risk averse • Negative formulation • Gamble to achieve a better result • Risk seeking Decision and Cost-Effectiveness Analysis

  10. Mental Accounting • You set off to buy an iPod shuffle at what you believe to be the cheapest store in your neighborhood. When you arrive, you discover that the price of the Shuffle is $75, a price you believe is consistent with low estimates of the retail price. • A friend walks into the store and tells you a store 10 minutes away sells Shuffles for $55. • Do you go to the other store? • Now suppose you are buying a MacBook Pro for $1960, and a friend tells you it sells for $1940 in a store 10 minutes away. Do you go? Decision and Cost-Effectiveness Analysis

  11. Different Frames • Real versus Hypothetical • Experiment 1: What do you think? • Experiment 2: Framing with hypothetical payoffs • Experiment 3: Framing with real payoffs • Framing the choice to the civil jury can greatly affect the award • Framing the choice to the criminal jury • Can help decide guilt or innocence • Can affect the sentencing of the guilty Decision and Cost-Effectiveness Analysis

  12. Framing Effects in Medical Decision-Making: Treatments • When framed positively (i.e. survival vs. mortality): • Respondents 1.5 x more likely to choose surgery over other treatments (i.e. radiotherapy) • Respondents demonstrated increased preference for invasive/toxic treatments • No framing effect noted in hypothetical vs. real life treatment decisions • Medicine use intention higher when results presented as RRR vs. ARR or NNT Decision and Cost-Effectiveness Analysis

  13. RRR, ARR, and NNT • RRR = Relative Risk Reduction • ARR = Absolute Risk Reduction • NNT = Numbers Needed to Treat Dead Alive Meds 404 921 CABG 350 974 Risk of death (from having CABG) = 350/1324 = 0.264 Relative risk of death = 0.264/0.305 = 0.87 = 87% RRR = Amt of risk of death is reduced by surgery: 100% - 87% = 13% ARR = Absolute amt of risk surgery reduces death: 30.5% - 25.4% = 4.1% NNT = # pts needing surgery to prevent 1 death: 1/ARR = 24 Source: http://www.ebm.worcestervts.co.uk/trial_results.htm Decision and Cost-Effectiveness Analysis

  14. Conclusions on Frames • Humans are inconsistent. • Framing is effective • Framing can be manipulated to achieve desired outcomes • Awareness of framing effects can make you a better decision maker • Crucial in understanding discrepancies and inconsistencies in individual preferences. Decision and Cost-Effectiveness Analysis

  15. Implications for Cost-Effectiveness Analysis • Important when considering perspective for analysis. • Preferences are dependent on framing and point of reference. • Individual preferences vs. community preferences • Preferences at time of illness or during recovery • Availability of alternative treatments Decision and Cost-Effectiveness Analysis

  16. Three Topics • Frames • Equity • Economic epidemiology Decision and Cost-Effectiveness Analysis

  17. Equity • Efficiency and Equity • Both important for health care resource allocation decisions • Few guidelines for measuring or incorporating equity • Equity ~ Values • How can equity concerns be incorporated in cost-effectiveness analyses? Decision and Cost-Effectiveness Analysis

  18. What is equity? • An equal and fair distribution • Are treatments fairly allocated? Or Are benefits fairly distributed? • Canadian Common Drug Review Pharmacoeconomic Review Template: • “What equity assumptions were made in the analysis?” • No guidance on how to assess Decision and Cost-Effectiveness Analysis

  19. Vertical Equity • Principle of vertical equity = allocation linked to “need” • Greater care is given to people with greater health needs • Sicker patients  first priority for funding • Goal is to create equity in eventual health status Decision and Cost-Effectiveness Analysis

  20. Neglecting Vertical Equity • Implies all health outcomes are valued equally • Regardless of to whom they accrue • Conversely, paying attention to equity: • Could make some relatively inefficient technologies more attractive • If benefits groups with greater claim to treatment • Or could make efficient options less attractive Decision and Cost-Effectiveness Analysis

  21. NICE (UK) Decisions, 1999 to 2002 Sculpher, M.The use of quality-adjusted life-years in cost-effectiveness studies.Allergy61 (5), 527-530. Decision and Cost-Effectiveness Analysis

  22. Controversy • Vertical equity may be controversial • If your definition of “need” is different than mine • Assume we accept vertical equity • What characterizes equity? • How should it measured? Decision and Cost-Effectiveness Analysis

  23. Review of Efficiency • The Incremental Cost-Effectiveness Ratio • Comparing treatments A and B: • The cost of obtaining one extra unit of health effect • Cost-effectiveness analysis • A measure of efficiency • Tradeoff between made explicit between • scarce resources • potential changes in health Decision and Cost-Effectiveness Analysis

  24. 0.8 0.8 0.8 0.8 0.9 0.75 0.75 0.8 0.7 0.5 0.5 0.5 0.6 0.5 Quality of LifeWeight 0.4 0.25 0.3 0.2 0.1 0 1 2 3 4 5 6 7 8 9 10 Years QALYs as a Measure of Health • Quality Adjusted Life Year • Life expectancy = 10 years • Quality adjusted LE = 6.45 QALYs MS&E 292 - Health Policy Modeling

  25. Are All QALYs Gains Equivalent? 25 Each associated with a gain of 3 QALYs! E ′ 20 E B ′ B 15 A’ Life Expectancy C ′ 10 D ′ 7 QALYs A 5 4 QALYs C D 1 QALY 0 0 0.2 0.4 0.6 0.8 1 Quality of Life Decision and Cost-Effectiveness Analysis

  26. Steps in Applying Equity to CEA • Define groups which should receive priority to advance equity • Derive equity weights • Determine how equity weights can be applied to results of cost-effectiveness analyses (CEA) • Apply equity weighting to CEA results as a form of sensitivity analysis Decision and Cost-Effectiveness Analysis

  27. Some Possible Equity Factors Decision and Cost-Effectiveness Analysis

  28. Steps in Applying Equity to CEA • Define groups which should receive priority to advance equity • Derive equity weights • Determine how equity weights can be applied to results of cost-effectiveness analyses (CEA) • Apply equity weighting to CEA results as a form of sensitivity analysis Decision and Cost-Effectiveness Analysis

  29. Decision and Cost-Effectiveness Analysis

  30. Survey to Understand Equity • Pilot in elected officials, municipal and provincial public clerks. • Participants recruited from waiting rooms at major Toronto downtown teaching hospital. • Asked to imagine they were voting in a referendum between 2 programs. MS&E 292 - Health Policy Modeling

  31. An Example Decision and Cost-Effectiveness Analysis

  32. Solve the problem of equity? • Personal circumstances made such decision making challenging. • Several disliked the conceptual basis of the study, • Fairness factors “aren’t measurable” • Trade-offs between attributes too complex • Individual or group values should dominate over centralized decision making Decision and Cost-Effectiveness Analysis

  33. More Comments • 7: interesting and thought-provoking • 14: challenging (3 both interesting and challenging) • 5 wanted “equal” option to indicate that they considered some scenarios equivalent • Some felt that any rationing was objectionable • “Everyone should have a chance to be treated. It is up to the patient and his doctor to decide whether it is worthwhile”. • Choices are best left in the hands of God Decision and Cost-Effectiveness Analysis

  34. Significant factors in equity… • Consistent with prioritization for those with poorer health • Less prior resource allocation viewed as having priority • Equal priority two groups alike except: • 1st had a quality of life that was 50 points worse • 2nd had an expected 10 year increase in life expectancy • Equal priority two groups alike except: • 1st 10 years younger • 2nd had received about $13,000 less in prior resources Decision and Cost-Effectiveness Analysis

  35. Some Factors Not Significant • Number of people expected to benefit • Potential improvement in quality of life • Could have important implications for resource allocation models • Distributional aspects (“how many benefit?”) may be less important than the characteristics of individuals (“who benefits?”) Decision and Cost-Effectiveness Analysis

  36. Steps in Applying Equity to CEA • Define groups which should receive priority to advance equity • Derive equity weights • Determine how equity weights can be applied to results of cost-effectiveness analyses (CEA) • Apply equity weighting to CEA results as a form of sensitivity analysis Decision and Cost-Effectiveness Analysis

  37. Equity-Weighted QALYs • Vertical equity • Implies society values some health gains more than others • For example • A QALY gain a sick person more valuable than a QALY gain for a well person • Cancer drug vs. lifestyle drug • One often proposed solution is to adjust QALYs • QALYs transformed into “eQALYs”= equity-weighted QALYs Decision and Cost-Effectiveness Analysis

  38. An alternative to focusing on QALYs • Rather than focusing on health outcome • Focus on resource allocation decision • Reframe vertical equity as “more willing to pay for some health outcomes than others” • i.e., a higher (or lower) willingness to pay threshold • Advantage: • Policy implications more transparent • Accommodated by current CEA methods • Disadvantage • Measurement more difficult • “Knee-jerk” rejections more common? Decision and Cost-Effectiveness Analysis

  39. Limitations of eQALYs • QALYs already controversial • Construct is artificial, somewhat foreign • Measurement issues • Already conflate survival, quality of life • Putting equity in might confuse more than it illuminates • And exacerbate concerns about subjectivity, values • i.e. eQALY components: • Survival Objective • Quality of life (preference) Subjective • Equity weight Subjective and value-laden Decision and Cost-Effectiveness Analysis

  40. The Net Benefit Approach • Consider an ICER • Δ C / Δ E • Decision favorable if: • ICER < society’s willingness to pay for an extra unit of E (λ) • Δ C / Δ E < λ • Define Net Monetary Benefit (NMB) as • NMB = λ∙ Δ E- Δ C • Decision favorable if NMB>0 Decision and Cost-Effectiveness Analysis

  41. Equity-weighted NMB • Assume an intervention • We want to assign an equity weight to the health effect • Call the equity weighting function f(∙) • Equity-weighted health effect is f(Δ E,q) • Where q is a vector of equity factors • So equity-weighted NMB is • NMB = λ∙ f(Δ E,q)- Δ C Decision and Cost-Effectiveness Analysis

  42. Steps in Applying Equity to CEA • Define groups which should receive priority to advance equity • Derive equity weights • Determine how equity weights can be applied to results of cost-effectiveness analyses (CEA) • Apply equity weighting to CEA results as a form of sensitivity analysis Decision and Cost-Effectiveness Analysis

  43. Conclusions • Equity weighting the willingness to pay threshold is algebraically equivalent to equity adjusting QALYs • A form of sensitivity analysis, offers transparency, reproducibility • Focus on methods to estimate the relative attractiveness of allocating to different groups • Doesn’t obviate need for determining societal willingness to pay threshold Decision and Cost-Effectiveness Analysis

  44. Equity Considerations • Fairness in process • Accountability for reasonableness • Fairness in outcomes • A decision that is: • Transparent • Principled • Defensible Decision and Cost-Effectiveness Analysis

  45. Three Topics • Frames • Equity • Economic epidemiology Decision and Cost-Effectiveness Analysis

  46. Traditional View of Epidemics • How is an epidemic started? • Index case • The first case to start an epidemic • Not necessarily the first case of the disease • Epidemic is an interaction of the disease, the host, and the susceptible population Decision and Cost-Effectiveness Analysis

  47. Finding the Index Case • Detective work to find “Patient Zero” • Gaëtan Dugas • the French-Canadian gay flight attendant reputed to introduce HIV to the US. • Made famous by the book “And the Band Played On” • The research used for that study was later repudiated • Introduction probably through Haiti rather than Africa • Typhoid Mary • The SARS outbreak • On Feb 21, 2003, a 65-year-old medical doctor from Guangdong checks into the 9th floor of the Metropole hotel in Hong Kong Decision and Cost-Effectiveness Analysis

  48. The importance of a susceptible population and hosts Index case from Guangdong Hospital 2 Hong Kong 4 HCW + 2 Canada 12 HCW + 4 Hospital 3 Hong Kong 3 HCW F Ireland G 156 close contacts of HCW and patients A Hotel M Hong Kong K H I Hospital 1 Hong Kong 99 HCW E USA D J C B Viet Nam 37 HCW + ? Hospital 4 Hong Kong Germany HCW + 2 Singapore 34 HCW + 37 New York Bangkok HCW 4 other Hong Kong hospitals 28 HCW Decision and Cost-Effectiveness Analysis

  49. SARS: 8,445 probable cases, 790 deaths Europe: 10 countries (38) Russian Fed. (1) Canada (238) Mongolia (9) Mongolia (9) China (5328) USA (70) Kuwait (1) Hong Kong (1755) India (3) Colombia (1) Viet Nam (63) Singapore (206) Brazil (3) South Africa (1) South Africa (1) Australia (5) New Zealand (1) Decision and Cost-Effectiveness Analysis

  50. Epidemic Models • S-I-R Models POPULATION Susceptible Infected Removed • Have no immunity • Never had the disease • Have not been immunized • Recovered and immune • Dead Decision and Cost-Effectiveness Analysis

More Related