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2. Lecture 11: Pricing Pharmaceuticals AEM 4160: Strategic Pricing Prof. Jura Liaukonyte 2

3. Lecture Plan  QALY  Value of Statistical Life  HBS Case on Gardasil

4. Value of Statistical Life  An economic value assigned to life in general.  Marginal cost of death prevention in a certain class of circumstances.  As such, it is a statistical term, the cost of reducing the (average) number of deaths by one.

5. Viscusi. “The Value of a Statistical Life: A Critical Review of Market Estimates Throughout the World.” Journal of Risk and Uncertainty, v. 27 issue 1, 2003, p. 5.

7. Value of Life and Compensating Differences  Calculating VSL may sound callous or morbid, but it can lead to stronger safety and environmental regulations  For example, auto safety rules that would cost $100 million to implement but might protect $500 million worth of lives (say, 100 people at $5 million of VSL) are seen as a good deal, cost-benefit-wise.  VSLs can vary widely, depending on the agency and the administration in office, usually $5- $9 million.

8. Controversial?  Some economists have suggested that to be clearer about the fact that we’re not talking about Fred’s life but a change in population mortality risk, we should use a different word, like “micromort” (as argued in Cameron, 2010).  There’s a mathematical sense in which the two ideas are identical—if we’re increasing deaths by one, why should it matter whether the person who dies is identifiable or not?  However, while people seem willing to trade off population mortality risk against other things, people have a visceral ethical reaction to valuing Fred’s life.

9. VSL  VSL is very important in policy.  Many government agencies have a VSL estimate that drives their cost-benefit analyses or policy studies.  US Environmental Protection Agency uses a value of $8.5 million in 2012 dollars  The US Department of Transportation uses a value of $6.4 million  When these agencies analyze policies that have been or may be enacted, they use these numbers to value changes in risks to lives.  For example, the EPA’s assessment of a revised air pollution rule (the Cross State Air Pollution Rule) found that the rule provides much larger benefits than costs, and this conclusion is largely driven by reductions in mortality risks

11. Value of a Statistical Life and Compensating Differences

12. VSL  The idea is that if we can find out the exact amount a person is willing to pay (or accept) to avoid (or allow) an increase in risk of death of ∆p, then we can extrapolate to figure out how much you’d pay (or accept) to avoid (allow) certain death.  Therefore if the WTP or WTA amount is ∆X, then we can say that:

13. VSL  Safety devices: E.g., fire alarms have an annualized cost of $20 they reduce risk of death by 1 in 100,000 per year. By buying the smoke alarms, people are demonstrating that they value their lives enough to make that tradeoff. So these people must value their lives at least as much as:  Sprinkler systems: E.g. people are generally unwilling to buy sprinkler systems. These people might not value their lives enough to make that tradeoff. If a sprinkler system has a cost of $1000 but it reduces the risk of death by 1 in 10,000, then:

14. Value of a Statistical Life and Compensating Differences  Qa, Qb =probability of fatal injury on job a, b respectively in a given year  Wa, Wb = earnings on job a, b in a given year  Assume Qa<Qb so that Wa<Wb  Compensating difference=Wb-Wa  Value of a “statistical” life = (Wb-Wa)/(Qb-Qa)  Example: If a person is faced with.001 higher risk of death per year and is paid $5000 per year extra for that risk, the value of a statistical life is 5000/.001 - $5,000,000

15. Value of Life and Compensating Differences  Four biases in estimates of statistical value of life  Valuation is correct only for “marginal” worker. Estimate is too high for infra-marginal worker, and too low for workers that didn’t accept job with risk.  Ex post versus ex ante rewards for risk (compensating difference vs. law suits, insurance, etc.)  Failure to control for other risks correlated with fatality risk  Fatality risk measured with error

16. Question  Is Gardasil a Good Product?

17. Pricing in the Biomedical Industry  What factors should Merck consider when setting the price?

18. Factors:  Important or not important?  Product cost  R&D Investment?  Other Vaccines?  Public Relations?  Value to the Customer/Benefit?  Economic Modeling?  Competition?

19. Pharmaceutical Market  Prescription medicines are subject to derived demand.  Products demanded and sold in response to medical need.  Their use is affected by recognized standards of care  Essential decision maker is the physician who neither consumes nor pays for the product  Prescriptions are considered “negative goods”, in that those who purchase or consume them would prefer not to do so.  Prescriptions are experience goods.  Their actual utility cannot be determined until they have been used.

20. QALY  The quality-adjusted life year (QALY) is a measure of disease burden, including both the quality and the quantity of life lived.  It is used in assessing the value for money of a medical treatment.  The QALY is based on the number of years of life that would be added by the treatment.  Each year in perfect health is assigned the value of 1.0 down to a value of 0.0 for death.

21. QALY  Used in cost-utility analysis to calculate the ratio of cost to QALYs saved for a particular health care treatment.  Helpful in allocating healthcare resources  Treatment with a lower cost to QALY saved ratio being preferred over an intervention with a higher ratio  Controversial: some people will not receive treatment because it is too costly  Cost per QALY under $50,000 is acceptable

22. Calculating Cost per QALY  Cost Per QALY = Cost of a quality life year  Step 1: Consider the costs per person:  Cost per dose: ___________________  Cost per administration:_____________  Number of doses: _____________________  Total cost per patient: __________________

23. Step 2  Additional QALYs per person  At age 50, further life expectancy without cervical cancer:______  QALY per year: __________________________________________  Total QALYs: ____________________________________________  At age 50, further life expectancy with cervical cancer: ________  QALY per year: ___________________________________________  Total QALYs: _____________________________________

24. Step 2  Reduction in QALYs with cervical cancer:_________________  Gardasil prevents:______________________________  Gardasil incremental QALYs: ________________  Chance of Getting cervical cancer without Gardasil: _________  Incremental QALYs per person: _______________________  Cost per QALY:  Vaccination: _____________________________________  QALY: ____________________________________  Cost per QALY:___________________________

25. Step 2a  This was a rough calculation because it left out an important piece of a puzzle:  COST SAVINGS  Fewer Pap tests  Fewer LLETZ procedures  Fewer cervical cancers to treat

26. Step 2a  Calculate COST savings  Chance that a woman will have CIN 1: ______________  Chance that a woman will have CIN 2/3:______________  Chance that a woman will have cervical cancer: ___________  Cost to treat CIN 1: ________$55______________  Cost to treat CIN2/3: _____________________  Cost to treat cervical cancer: ________________

27. Saved Costs per person  CIN 1: __________________________________  CIN 2/3: ________________________________  Cervical cancer: ___________________________  Gardasil will prevent (estimates):  CIN 1: 50%  CIN 2: 70%  Cervical Cancer: 70%

28. Calculate Total Savings:  CIN 1: ____________________  CIN 2/3: ____________________  Cervical cancer: _________________  TOTAL SAVINGS: ______________________

29. Savings Now or Later?  Vaccine given (average or target): __________  Cancer prevents: _______________  Difference: ___________________  Discount the cost savings at say, 8% = $16.50  In excel the command would be: =PV(0.08, 43,,-450.2)

30. Savings later  So the total is:  Cost per person: _______________  Savings per person: ___________  QALY per person: 0.038  COST per QALY:__________________  Do the risks of a PR backlash and the need to grow quickly outweigh the benefits of a higher price  Potential entrant is coming (Cervarix approved by FDA in 2009)  Patent is not forever

31. $360 Too Low or Too High?  Suppose prices are set so that cost of QALY is $30,000  What is the maximum price that could be set?  x = cost per person  _____________________

32. ANSWERS TO BLANK SLIDES

33. Calculating Cost per QALY  Cost Per QALY = Cost of a quality life year  STEP 1: Consider the costs per person:  Cost per dose: ____________$120_______  Cost per administration:______$20________  Number of doses: _________3____________  Total cost per patient: ________$420_______

34. Step 2  Additional QALYs per person  At age 50, further life expectancy without cervical cancer: 31.6 years_  QALY per year: ______________________0.8______________  Total QALYs: _____________.8*31.6=25.2____________________  At age 50, further life expectancy with cervical cancer: 20 years__  QALY per year: _______________0.8______________  Total QALYs: _________________0.8*20=16____________________

35. Step 2  Reduction in QALYs with cervical cancer:___25.2-16=9.2___  Gardasil prevents:__________________70%____________  Gardasil incremental QALYs: _______.7*9.2=6.4_________  Chance of Getting cervical cancer without Gardasil: ___0.6%_  Incremental QALYs per person:____0.006*6.4=0.038_______  Cost per QALY:  Vaccination: ___________________$420__________  QALY: ________________________0.038____________  Cost per QALY:_________________420/0.038=$11,053__________

36. Step 2a  This was a rough calculation because it left out an important piece of a puzzle:  COST SAVINGS  Fewer Pap tests  Fewer LLETZ procedures  Fewer cervical cancers to treat

37. Step 2a  Calculate COST savings  Chance that a woman will have CIN 1: _______10%__  Chance that a woman will have CIN 2/3:___2.8%___  Chance that a woman will have cervical cancer: __0.6%_____  Cost to treat CIN 1: ________$55______________  Cost to treat CIN2/3: _________$1400____________  Cost to treat cervical cancer: _______$100,000_________

38. Saved Costs per Person  CIN 1: ________10%*$55=$5.50____________  CIN 2/3: ______2.8% * $1400=$39.20_______  Cervical cancer: __0.6%*$100,000=$600_____  Gardasil will prevent (estimates):  CIN 1: 50%  CIN 2: 70%  Cervical Cancer: 70%

39. Calculate Total Savings:  CIN 1: ________5.50*50%=$2.75____________  CIN 2/3: ______39.20*70%=$27.44__________  Cervical cancer: __600*70%=$420___________  TOTAL SAVINGS: _____$450.20______

40. Savings Now or Later?  Vaccine given (average or target): ___Age 11____  Cancer prevents: _____Age 54_____  Difference: _________43 years______  Discount the cost savings at say, 8% = $16.50  In excel the command would be: =PV(0.08, 43,,-450.2)

41. Savings Later  So the total is  Cost per person: ________$420_______  Savings per person: ______$16.50_____  QALY per person: 0.038  COST per QALY: $10,618.00  Do the risks of a PR backlash and the need to grow quickly outweigh the benefits of a higher price  Potential entrant is coming  Patent is not forever

42. $360 Too Low or Too High?  Suppose prices are set so that cost of QALY is $30,000  What is the maximum price that could be set?  x = cost per person  (x-16.50)/0.038 = 30,000  x =$1156.5  Or $1156.5/3 = $385 per dose