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Cost-Effectiveness Analysis Life Years Analysis

Cost-Effectiveness Analysis Life Years Analysis. Scott Matthews Courses: 12-706 / 19-702. Admin. HW 5 Due Wednesday Project 2 Coming soon. Due Monday Nov 24 (2 weeks). Specifics on Saving Lives. Cost-Utility Analysis Quantity and quality of lives important

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Cost-Effectiveness Analysis Life Years Analysis

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  1. Cost-Effectiveness AnalysisLife Years Analysis Scott Matthews Courses: 12-706 / 19-702

  2. Admin • HW 5 Due Wednesday • Project 2 Coming soon. • Due Monday Nov 24 (2 weeks)

  3. Specifics on Saving Lives • Cost-Utility Analysis • Quantity and quality of lives important • Just like discounting, lives are not equal • Back to the developing/developed example • But also: YEARS are not equal • Young lives “more important” than old • Cutting short a year of life for us vs • Cutting short a year of life for 85-year-old • Often look at ‘life years’ rather than ‘lives’ saved.. These values also get discounted

  4. Simple Example

  5. Cost-Effectiveness Testing • Generally, use when: • Considering externality effects or damages • Could be environmental, safety, etc. • Benefits able to be reduced to one dimension • Alternatives give same result - e.g. ‘reduced x’ • Benefit-Cost Analysis otherwise difficult/impossible • Instead of finding NB, find “cheapest” • Want greatest bang for the buck • Find cost “per unit benefit” (e.g. lives saved) • Allows us to NOT include ‘social costs’

  6. The CEA ratios • CE = C/E • Equals cost “per unit of effectiveness” • e.g. $ per lives saved, tons CO2 reduced • Want to minimize CE (cheapest is best) • EC = E/C • Effectiveness per unit cost • e.g. Lives saved per dollar • Want to maximize EC • No practical difference between 2 ratios

  7. Interesting Example

  8. Lessons Learned • Ratios still tend to hide results • Do not take into account scale issues • CBA might have shown Option B to be better (more lives saved) • Tend to only consider budgetary costs • CEA used with constraints? • Minimize C s.t. E > E* • Min. effectiveness level (prev slide) • Find least costly way to achieve it • Minimize CE s.t. E > E* • Generally -> higher levels of C and E! • Can have similar rules to constrain cost

  9. Sample Applications • Cost-effectiveness of: • New drug/medical therapies* very popular • Pollution prevention • Safety regulations

  10. Definitions • Overall cost-effectiveness is the ratio of the annualized cost to the quantity of effectiveness benefit. • Incremental cost-effectiveness is the difference in costs divided by the difference in effectiveness that results from comparing one option to another, or to a benchmark measure.

  11. Incremental CE • To find incremental cost-effectiveness : • Sort alternatives by ‘increasing effectiveness’ • TAC = total annualized cost of compliance • PE = effectiveness (e.g. benefit measure) • CE = (TACk – TACk-1) / ( PEk – PEk-1) • CE = incremental cost-effectiveness of Option k • Use zero values (if applicable) for base case

  12. Incremental CE Example • Inc CE here only relevant within control categories (metals v. oils v. org’s) • ** Negative CE means option has more removals at lower cost • Source: US EPA Office of Water EPA 821-R-98-018, “Cost Effectiveness Analysis of Effluent Limitations Guidelines and Standards for the Centralized Waste Treatment Industry”

  13. Definitions (2) • Marginal cost-effectiveness refers to the change in costs and benefits from a one-unit expansion or contraction of service from a particular intervention (e.g. an extra pound of emissions, an extra fatality avoided).

  14. Why is CEA so relevant for public policy analysis? • Limited resources! • Opportunity cost of public spending • i.e. if we spend $100 M with agency A, its $100 M we cannot spend elsewhere • There is no federal rule saying ‘each million dollars spent must save x lives’

  15. Gray Areas • How to measure cost-effectiveness when there is a single project cost but multiple effectiveness categories • E.g. fatalities and injuries, CO2 and SO2 • Alternatives: • Keep same cost, divide by each benefit • Overstates costs for each • Keep same cost, divide by ‘sum of benefits’ • Allocate cost, divide by each benefit separately • Weight the costs and/or benefits • Will see this more in next lecture

  16. Another CEA Example • Automated defribillators in community • http://www.early-defib.org/03_06_09.html • What would costs be? • What is effectiveness?

  17. Value of Life Analysis Scott Matthews Courses: 12-706 / 73-359 / 19-702

  18. “Value of Life” • Economists don’t like to say they put a value on life • They say they “Study peoples’ willingness to pay to prevent premature mortality” • Translation: “how much is your life worth”? 12-706 and 73-359

  19. WTP versus WTA • Economics implies that WTP should be equal to ‘willingness to accept’ loss • Turns out people want MUCH MORE in compensation for losing something • WTA is factor of 4-15 higher than WTP! • Also see discrepancy shrink with experience • WTP formats should be used in CVs • Only can compare amongst individuals

  20. Economic valuations of life • Miller (n=29) $3 M in 1999 USD, surveyed • Wage risk premium method • WTP for safety measures • Behavioral decisions (e.g. seat belt use) • Foregone future earnings • Contingent valuation • Note that we are not finding value of a specific life, but instead of a statistical life 12-706 and 73-359

  21. DALY/QALY measures • Disability adjusted life years or quality-adjusted life years • These are measures used to normalize the quality-quantity tradeoff discussed last time. • E.g., product of life expectancy (in years) and the quality of life available in those years. 12-706 and 73-359

  22. Risk Analysis • Study of the interactions between decision making, judgment, and nature • Evidence : cost-effectiveness of risk reduction opportunities varied widely - orders of magnitude • Economic efficiency problems 12-706 and 73-359

  23. Example - MAIS scale • Abbreviated Injury Scale (AIS) is an anatomically based system that classifies individual injuries by body region on a six point ordinal scale of risk to life.   • AIS does not assess the combined effects of multiple injuries.  • The maximum AIS (MAIS) is the highest single AIS code for an occupant with multiple injuries.  12-706 and 73-359

  24. MAIS Table - Used for QALY Conversions 12-706 and 73-359

  25. Sample QALY comparison • A: 4 years in a health state of 0.5 • B: 2 years in a health state of 0.75 • QALYs: A=2 QALY; B=1.5 QALY • So A would be preferred to B. 12-706 and 73-359

  26. Cost-Effectiveness of Life-Saving Interventions • From “500 Life-saving Interventions and Their Cost-Effectiveness”, Risk Analysis, Vol. 15, No. 3, 1995. • ‘References’ (eg #1127) are all other studies • Model: • Estimate costs of intervention vs. a baseline • Discount all costs • Estimate lives and life-years saved • Discount life years saved • CE = CI-CB/EI-EB 12-706 and 73-359

  27. Specific (Sample) Example • From p.373 - Ref no. 1127 • Intervention: Rear outboard lap/shoulder belts in all (100%) of cars • Baseline: 95.8% of cars already in compliance • Intervention: require all cars made after 9/1/90 to have belts • Thus costs only apply to remaining 4.2% (65,900) cars • Target population: occupants over age 4 • Others would be in child safety seats • What would costs be? 12-706 and 73-359

  28. Example (cont) • 1986 Costs (from study): $6 cost per seat • Plus added fuel costs (due to increased weight) = total $791,000 over life of all cars produced • Effectiveness: expect 23 lives saved during 8.4 year lifetime of fleet of cars • But 95.8% already exist, thus only 0.966 lives saved • Or 0.115 lives per year (of use of car) • But these lives saved do not occur all in year 0 - they are spread out over 8.4 years. • Thus discount the effectiveness of lives saved per year into ‘year 0’ lives.. 12-706 and 73-359

  29. Cost per life saved • With a 5% discount rate, the ‘present value’ of 0.115 lives for 9 years = 0.817 (less than 0.966) • Discounted lives saved = • This is basically an annuity factor • So cost/life saved = $791,000/0.817 • Or $967,700 per life (in “$1986/1986 lives”) • Using CPI: 145.8/109.6 -> $1,287,326 in $1993 • But this tells us only the cost per life saved • We realistically care more about quality of life, which suggests using a quality index, e.g. life-years saved. 12-706 and 73-359

  30. Sample Life Expectancy Table 35-year old American expected to live 43.6 more years (newer data than our study) Source: National Center for Health Statistics, http://www.cdc.gov/nchs/fastats/lifexpec.htm 12-706 and 73-359

  31. Cost per life-year saved • Assume average age of fatality in car accident was 35 years • Life expectancy tables suggested a 35 year old person would on average live to age 77 • Thus ‘42’ life years saved per fatality avoided • 1 life-year for 42 yrs @5%= 17.42 years (ann. factor) • $1993 cost/life-year = $1,287,326/17.42 • With 2 sig. figures: ~$74,000 as in paper • Note $1,287,326 is already in cost/life units -> just need to further scale for life-years by 17.42 12-706 and 73-359

  32. Example 2 - Incremental CE • Intervention: center (middle) lap/shoulder belts • Baseline: outboard only - (done above) • Same target population, etc. • Cost: $96,771,000 • Incremental cost : $96,771,000 - $791,000 • Effectiveness: 3 lives/yr, 21.32 discounted • Incremental Effectiveness: 21.32 - 0.817= 20.51 • Cost/life saved = $95.98 million/20.51 = $4.7 million ($1986) => $6.22 million in $1993 • Cost/life-year = $6.22 million/17.42 = $360,000 12-706 and 73-359

  33. Overall Results in Paper • Some had < $0 cost, some cost > $10B • Median $42k per life year saved • Some policies implemented, some only studied • Variation of 11 orders of magnitude! • Some maximums - $20 billion for benzene emissions control at tire factories • $100 billion for chloroform standards at paper mills 12-706 and 73-359

  34. Comparisons 12-706 and 73-359

  35. Agency Comparisons • $1993 Costs per life year saved for agencies: • FAA (Aviation): $23,000 • CPSC (Consumer Products): $68,000 • NHTSA (Highways): $78,000 • OSHA (Worker Safety): $88,000 • EPA (Environment): $7,600,000! • Are there underlying causes for range? Hint: are we comparing apples and oranges? 12-706 and 73-359

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