1. Pharmacoeconomics David Matthews 2012 AMCP P&T Competition National Finalist The Ohio State University AMCP Chapter October 9 th, 2012 An Introduction for the P&T Competition

2. Outline Types of economic analyses Definition of cost-effectiveness Determining cost-effectiveness Markov modeling

3. What is Pharmacoeconomics? Economics is the science of balancing best outcomes with limited resources Pharmacoeconomics applies this concept to pharmacologic interventions

4. Types of Economic Analyses Cost-minimization analysis Cost-benefit analysis Cost-effectiveness analysis Cost-utility analysis

5. Cost-Minimization Analysis Compares two interventions considered equally effective and tolerable Determines which intervention costs less Costs include more than the price of meds  Costs of treatment failure  Costs of adverse effects  Drug monitoring or other healthcare services

6. Cost-Benefit Analysis Adds up costs associated with intervention Compares to monetary benefits of intervention  Outcomes must be converted to dollars Compares input dollars vs. output dollars Determines whether benefits > cost

7. Cost-Effectiveness Analysis Usually compares two interventions Determines the cost to produce an effect Expresses cost of an effect as a ratio:  Numerator = cost ($)  Denominator = clinically appropriate marker, for example: mm Hg blood pressure lowering mg/dL of LDL lowering Quality-adjusted life-years (cost-utility analysis)

8. Cost-Utility Analysis Subset of cost-effectiveness analysis Determines the cost of adding one year of perfect health to a patient’s life Calculates incremental cost-effectiveness ratio (ICER)  Ratio of cost to effectiveness: Numerator = cost ($) Denominator = Quality-adjusted life-years

9. Cost-Effective ≠ Cost-Saving!!!

10. Cost-Saving vs. Cost-Effective Cost-saving  An intervention that has a lower total cost than an alternative intervention Cost-effective  An intervention that is sufficiently effective relative to its total cost when compared with an alternative intervention

11. Cost-Effectiveness Plane cost effect NE quadrant: more costly, more effective NW quadrant: more costly, less effective SW quadrant: less costly, less effective SE quadrant: less costly, more effective PERFORM CEA DOMINATED DOMINATES Adapted from: Smith KJ et al. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 95-108.

12. Domination Occurs when one treatment is both cheaper and more effective Occurs in NW and SE quadrants of plane The cheaper/more effective treatment “dominates” the alternative The dominating treatment is the preferred treatment

13. Determining Cost-Effectiveness New intervention in NE or SW quadrant Example:  Drug A is a new drug  Drug B is the current standard of care  Drug A works better than Drug B  Drug A is more costly than Drug B Question:  Using Drug A instead of Drug B, how much does it cost us to add one year of perfect health onto the life of our patient?

14. Incremental Cost-Effectiveness Ratio (ICER) Represents the amount of money spent to add one year of perfect health onto the life of our patient

15. KEY POINT: The ICER is the single most important indicator of an intervention’s cost- effectiveness. Its calculation can be complex, and will be the focus of the next several slides.

16. Terminology Utility  Numerical estimate of quality of life (QOL) associated with a disease state or treatment  Perfect health = 1, Dead = 0  Anything else…somewhere in between  Measured using questionnaires

17. Terminology Quality-Adjusted Life-Year (QALY)  Life expectancy adjusted based on utility  QALY = time in health state × utility of state  If patient remains in the state for the remainder of their life, we can use life expectancy for time

18. QALY Example Consider 2 hypothetical chemo drugs  Standard of care vs. new therapy  Both prolong life  Both cause side effects which reduce QOL

19. QALY Example Standard of care treatment:  Prolongs life by an average of 1 year  Estimated utility of 0.65 due to side effects New treatment:  Prolongs life by an average of 1.5 years  Estimated utility of 0.5 due to side effects

20. Standard of Care QALYs QALY = Life expectancy × utility = 1 year × 0.65 utility = 0.65 QALYs The standard of care is expected to add 0.65 quality-adjusted life-years to our patient’s life.

21. New Treatment QALYs QALY = Life expectancy × utility = 1.5 years × 0.5 utility = 0.75 QALYs The new treatment is expected to add 0.75 quality-adjusted life-years to our patient’s life.

22. Calculating ICER ICER = difference in cost difference in effectiveness Or… ICER = C2 – C1  $’s E2 – E1  QALYs

23. Back to Our Chemo Drugs… Suppose a full course of treatment costs…  $12,000 for standard of care  $15,000 for new treatment

24. ICER of Chemo Drugs ICER = C2 – C1 E2 – E1 ICER = $15,000 – $12,000 0.75 QALY – 0.65 QALY ICER = $30,000/QALY

25. Interpretation of ICER On average, it costs us $30,000 to add one year of perfect health onto the life of our patient. So is this considered cost-effective?

26. Threshold of Cost-Effectiveness Subjective $50,000/QALY commonly reported in studies WHO recommends 3x per capita GDP for a given country  Would be around $150,000/QALY in USA National Institute for Health and Clinical Experience (NICE) recommends £30,000/QALY ($48,396/QALY) Dasbach EJ et al.. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 119-143. World Health Organization. Available from: http://www.who.int/choice/costs/CER_thresholds/en/index.htmlhttp://www.who.int/choice/costs/CER_thresholds/en/index.html McCabe C et al.. Pharmacoeconomics. 2008;26(9):733-44. Review.

27. Problems with Oversimplification Much more complex than “averages” in the real world Some people will tolerate the drugs better or worse than others Patients do not remain in one health state Each individual experiences different quality of life, incurs different costs, etc.

28. Markov Models Common in pharmacoeconomic research Used to calculate the entire cost and QALYs gained for a population Uses a hypothetical cohort of patients Patients move between health states Each state has associated probabilities, costs, and utilities

29. Components of Markov Models Expected health states Probabilities related to treatment failure, side effects, etc.  Normally from probabilities seen in studies Cycle length  How frequently would patients be expected to transition through health states? Utility and cost estimates for each state Time horizon

30. Simplified Example New treatment for a terminal illness More costly, more effective than standard of care Patients whose disease progresses incur greater costs  Hospitalizations  More treatments

31. Example Markov Model Cycles patients through health states based on preset probabilities Example model:  Healthy  Sick  Dead Each state is assigned its own utility and cost

32. Summary of Therapies TherapyStandard of careNew treatment Cost of treatment, one month $800$1,500 Progression from healthy to sick per month 8%4% Cost of tx + disease progression per month $2,500$3,200 Progression from sick to death per month 20%10%

33. Markov Model Example Standard of Care 0.92 0.8 0.08 0.2 Healthy Sick Dead

34. Markov Model Example New Treatment 0.96 0.9 0.04 0.1 Healthy Sick Dead

35. Health State Utilities Healthy  Utility = 0.8 (not 1.0 due to side effects) Sick  Utility = 0.4 Dead  Utility = 0

36. 10,000 Patient Cohort: New Treatment 0.96 0.9 0.04 0.1 Healthy Sick Dead 10,000 pts

37. After 1 month 0.96 0.9 0.04 0.1 Healthy Sick Dead 9,600 pts 400 pts COST: 400 x $3,200 =$1.3M QALY: 1/12 x 400 x 0.4 =13 QALY COST: 9,600 x $1,500 =$14.4M QALY: 1/12 x 9,600 x 0.8 =640 QALY

38. After 2 months 0.96 0.9 0.04 0.1 Healthy Sick Dead 9,216 pts 744 pts 40 pts COST: 744 x $3,200 =$2.4M QALY: 1/12 x 744 x 0.4 =25 QALY COST: 9,216 x $1,500 =$13.8M QALY: 1/12 x 9,216 x 0.8 =614 QALY

39. After 3 months 0.96 0.9 0.04 0.1 Healthy Sick Dead 8,847 pts 1,039 pts 114 pts And so on until all patients are in the “absorbing state” (death) COST: 1,039 x $3,200 =$3.3M QALY: 1/12 x 1,039 x 0.4 =35 QALY COST: 8,847 x $1,500 =$13.2M QALY: 1/12 x 8,847 x 0.8 =590 QALY

40. Markov Model Results Model continues until all patients in absorbing state or time horizon complete Patients accrue QALYs and costs each cycle Separate models run for new treatment and standard of care Once complete, ICER is calculated  (difference in cost) / (difference in QALYs)

41. Markov Models in the Real World Theoretically, models could be completed by hand Real life models become much more complex  More health states  Ability to move more freely through states  Account for issues such as adverse events Computers solve complex models

42. Real Life Example Shaheen NJ et al. Gut. 2004 Dec;53(12):1736-44.

43. Problems with Markov Models Complex models are difficult to understand Validity of model depends upon utility and cost estimates  Sensitivity analysis to account for variability

44. Sensitivity Analysis The scenario based off initial estimates is called the “base case scenario” Real life probabilities and costs may be higher or lower than predicted Adjust assumptions upward and downward and recalculate ICER Provides a range of possible economic outcomes

45. Conclusion New interventions are usually more effective but at a higher price Cost-effectiveness analysis helps determine if a new intervention is effective enough to be worth our limited resources ICER is a numerical value that summarizes cost-effectiveness Markov models are used to calculate ICER

46. Questions?

47. References McGhan WF. Introduction to pharmacoeconomics. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 1-16. Haycox A. What is cost-minimization analysis? In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 83-94. Smith KJ and Robers MS. Cost-effectiveness analysis. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 95-108. Dasbach EJ, Insinga RP, and Elbasha EH. Cost-utility analysis: a case study of a quadrivalent human papillomavirus vaccine. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 119-143. Beck JR. Markov modeling in decision analysis. In: Arnold, RJG, editor. Pharmacoeconomics from theory to practice. Boca Raton: CRC Press; 2010. p. 47-58. World Health Organization. Choosing interventions that are cost-effective [Internet]. [Geneva]: WHO; c2012 [cited 7 Oct 2012]. Available from: http://www.who.int/choice/costs/CER_thresholds/en/index.html http://www.who.int/choice/costs/CER_thresholds/en/index.html McCabe C, Claxton K, Culyer AJ. The NICE cost-effectiveness threshold: what it is and what that means. Pharmacoeconomics. 2008;26(9):733-44. Review. Shaheen NJ, Inadomi JM, Overholt BF, Sharma P. What is the best management strategy for high grade dysplasia in Barrett's oesophagus? A cost effectiveness analysis. Gut. 2004 Dec;53(12):1736-44.