Pharmacoeconomics

David Matthews2012 AMCP P&T Competition National Finalist

The Ohio State University AMCP ChapterOctober 9th, 2012

An Introduction for the P&T Competition

Outline

Types of economic analyses Definition of cost-effectiveness Determining cost-effectiveness Markov modeling

What is Pharmacoeconomics?

Economics is the science of balancing best outcomes with limited resources

Pharmacoeconomics applies this concept to pharmacologic interventions

Types of Economic Analyses

Cost-minimization analysis Cost-benefit analysis Cost-effectiveness analysis Cost-utility analysis

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 failureCosts of adverse effectsDrug monitoring or other healthcare services

Cost-Benefit Analysis

Adds up costs associated with intervention Compares to monetary benefits of

interventionOutcomes must be converted to dollars

Compares input dollars vs. output dollars Determines whether benefits > cost

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)

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

Cost-Effective ≠ Cost-Saving!!!

Cost-Saving vs. Cost-Effective

Cost-savingAn intervention that has a lower total cost

than an alternative intervention

Cost-effectiveAn intervention that is sufficiently effective

relative to its total cost when compared with an alternative intervention

Cost-Effectiveness Planecost

cost

effecteffect

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

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.

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

Determining Cost-Effectiveness New intervention in NE or SW quadrant Example:

Drug A is a new drugDrug B is the current standard of careDrug A works better than Drug BDrug 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?

Incremental Cost-Effectiveness Ratio (ICER)

Represents the amount of money spent to add one year of perfect health onto the life of our patient

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.

Terminology

UtilityNumerical estimate of quality of life (QOL)

associated with a disease state or treatmentPerfect health = 1, Dead = 0Anything else…somewhere in betweenMeasured using questionnaires

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

QALY Example

Consider 2 hypothetical chemo drugsStandard of care vs. new therapyBoth prolong lifeBoth cause side effects which reduce QOL

QALY Example

Standard of care treatment:Prolongs life by an average of 1 yearEstimated utility of 0.65 due to side effects

New treatment:Prolongs life by an average of 1.5 yearsEstimated utility of 0.5 due to side effects

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.

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.

Calculating ICER

ICER = difference in cost

difference in effectiveness

Or…

ICER = C2 – C1 $’s

E2 – E1 QALYs

Back to Our Chemo Drugs…

Suppose a full course of treatment costs…$12,000 for standard of care$15,000 for new treatment

ICER of Chemo Drugs

ICER = C2 – C1

E2 – E1

ICER = $15,000 – $12,000

0.75 QALY – 0.65 QALY

ICER = $30,000/QALY

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?

Threshold of Cost-Effectiveness Subjective $50,000/QALY commonly reported in studies WHO recommends 3x per capita GDP for a

given countryWould 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.html

McCabe C et al.. Pharmacoeconomics. 2008;26(9):733-44. Review.

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.

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

Components of Markov Models Expected health states Probabilities related to treatment failure,

side effects, etc.Normally from probabilities seen in studies

Cycle lengthHow frequently would patients be expected to

transition through health states? Utility and cost estimates for each state Time horizon

Simplified Example

New treatment for a terminal illness More costly, more effective than standard

of care Patients whose disease progresses incur

greater costsHospitalizationsMore treatments

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

Summary of Therapies

Therapy Standard of care New 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%

Markov Model ExampleStandard of Care

0.92

0.8

0.08

0.2

Healthy

Sick

Dead

Markov Model ExampleNew Treatment

0.96

0.9

0.04

0.1

Healthy

Sick

Dead

Health State Utilities

HealthyUtility = 0.8 (not 1.0 due to side effects)

SickUtility = 0.4

DeadUtility = 0

10,000 Patient Cohort: New Treatment

0.96

0.9

0.04

0.1

Healthy

Sick

Dead

10,000 pts

After 1 month

0.96

0.9

0.04

0.1

Healthy

Sick

Dead

9,600 pts

400 ptsCOST: 400 x $3,200 =$1.3MQALY: 1/12 x 400 x 0.4 =13 QALY

COST: 9,600 x $1,500 =$14.4MQALY: 1/12 x 9,600 x 0.8 =640 QALY

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 =$2.4MQALY: 1/12 x 744 x 0.4 =25 QALY

COST: 9,216 x $1,500 =$13.8MQALY: 1/12 x 9,216 x 0.8 =614 QALY

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 =$3.3MQALY: 1/12 x 1,039 x 0.4 =35 QALY

COST: 8,847 x $1,500 =$13.2MQALY: 1/12 x 8,847 x 0.8 =590 QALY

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)

Markov Models in the Real World

Theoretically, models could be completed by hand

Real life models become much more complexMore health statesAbility to move more freely through statesAccount for issues such as adverse events

Computers solve complex models

Real Life Example

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

Problems with Markov Models

Complex models are difficult to understand Validity of model depends upon utility and

cost estimatesSensitivity analysis to account for variability

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

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

Questions?

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

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.