CPAP Module 24, Section 4: Health Economics and Outcomes Research (HEOR)
MODULE 24: THE ECONOMICS & STRATEGY OF FORMULARY MANAGEMENT

Section 24.4: Health Economics and Outcomes Research (HEOR)

Quantifying Value: A Primer on the Analytical Methods Payers Use to Decide if a New Drug is “Worth It.”

SECTION 24.4

Health Economics and Outcomes Research (HEOR)

From QALYs to ICERs: Mastering the Language of Economic Value in Healthcare.

24.4.1 The “Why”: Translating Clinical Benefit into Economic Value

You now have a firm grasp of the two great forces that shape a formulary: the clinical evidence evaluated by the P&T Committee and the financial negotiations that determine a drug’s net cost. We now turn to the specialized discipline that bridges these two worlds: Health Economics and Outcomes Research (HEOR). HEOR is the science of quantifying the value of a medical intervention. It provides payers with a structured, analytical framework to answer what is perhaps the most difficult question in modern healthcare: with a finite budget, how do we decide if a new, effective, but often staggeringly expensive therapy is truly “worth it” for the population we cover?

As a CPAP specialist, you might wonder why you need to understand this highly academic field. The reason is simple: the output of HEOR analyses—metrics like the Quality-Adjusted Life Year (QALY) and the Incremental Cost-Effectiveness Ratio (ICER)—forms the rational, evidence-based justification for many of the most restrictive prior authorization criteria you will ever encounter. When a payer decides to limit a breakthrough oncology drug to only those patients who have failed three other treatments, it is often not an arbitrary decision. It is a decision rooted in a complex HEOR model that demonstrated the drug was only “cost-effective” (i.e., provided good value for the money) in that specific, heavily pre-treated population.

This section is your primer on HEOR. We are not going to turn you into a health economist, but we will equip you with a mastery of the core concepts and terminology. You will learn to speak the language of value that payers use internally. This knowledge is a profound strategic advantage. It allows you to understand the payer’s perspective on a deeper level. When you see a PA requiring a specific disease severity score, you will recognize it as a threshold derived from a cost-effectiveness model. When a drug is denied as “not medically necessary” despite being FDA-approved, you will understand that “necessary” in the payer’s language is often a synonym for “cost-effective.” By understanding how value is quantified, you can better articulate the unique value your patient represents, crafting appeals that are not just clinically persuasive but also economically intelligent.

Pharmacist Analogy: The Fleet Vehicle Purchasing Decision

Imagine you are the fleet manager for a massive national delivery company. You are responsible for purchasing 10,000 new delivery vans. Your job is not simply to buy the cheapest van, but to acquire the fleet that provides the best overall value to the company over the next five years. This is a classic HEOR problem.

You have two final contenders:

  • The “Standard Van”: A traditional gasoline-powered van. It has a low upfront purchase price of $30,000. It’s reliable but has mediocre fuel efficiency and requires oil changes every 5,000 miles.
  • The “Advanced Van”: A new hybrid-electric van. It has a much higher upfront purchase price of $45,000. However, it gets double the fuel mileage, has lower maintenance costs (no oil changes), and its advanced safety features are projected to reduce accidents and insurance premiums.

How do you decide? You don’t just look at the sticker price. You perform a comprehensive economic analysis, just like a health economist:

  1. You Define Your “Outcome”: Your primary outcome is not “owning a van.” It’s “cost per package delivered over 5 years.” This is your version of a QALY.
  2. You Build a Model: You create a sophisticated spreadsheet (your “economic model”) that projects all costs and outcomes over the 5-year lifespan of the vans.
    • Costs: Purchase price, projected fuel costs, scheduled maintenance, insurance premiums, potential accident repair costs.
    • Benefits: Number of packages delivered, potential savings from fewer accidents, lower fuel consumption.
  3. You Calculate the “ICER”: You calculate the Incremental Cost per package delivered for choosing the Advanced Van over the Standard Van. The math might show that despite the $15,000 higher upfront cost, the lifetime savings on fuel and maintenance make the Advanced Van’s cost per package delivered significantly lower.
  4. You Make the “Formulary” Decision: Based on your analysis, you issue a company-wide mandate: “The Advanced Van is now our preferred, ‘formulary’ vehicle. The Standard Van is ‘non-preferred’ and requires special approval from corporate.”

A local branch manager who only sees the $45,000 sticker price might be furious, demanding to know why they can’t buy the “cheaper” $30,000 van. Your job is to explain that the decision was based on a comprehensive analysis of long-term value, not just the upfront price. This is exactly the role HEOR plays for payers, and understanding this logic is key to your success.

24.4.2 The Common Denominator of Health: A Masterclass on the QALY

The first great challenge in health economics is the “apples and oranges” problem. How can a payer possibly compare the value of a new drug for rheumatoid arthritis against a new drug for metastatic lung cancer? One might improve quality of life and function, while the other extends life by a few months. They seem incomparable. To solve this, health economists developed a standardized, universal metric of health outcome that could be used across all disease states: the Quality-Adjusted Life Year (QALY).

Mastering the concept of the QALY is the first step to understanding all of health economics. A QALY is a measure that combines both the quantity (length) and the quality of life into a single number.

The Fundamental Equation of the QALY

$$ \text{QALYs} = (\text{Utility Value}) \times (\text{Years of Life}) $$

Deconstructing the “Utility Value”

The “Utility Value” (or “preference weight”) is the core of the QALY. It is a number on a scale from 0 to 1 that represents the quality of a specific health state.

  • 1 = Perfect Health: A utility value of 1.0 represents a state of perfect health. Therefore, one year lived in perfect health is equal to 1 QALY (1.0 x 1 year = 1 QALY).
  • 0 = Death: A utility value of 0 represents a health state considered equivalent to being dead.
  • Between 0 and 1: All other health states fall somewhere in between. A chronic condition like moderate, well-controlled diabetes might have a utility value of 0.85. A year lived in this state would generate 0.85 QALYs. A severe, debilitating condition like quadriplegia might have a utility value of 0.3.
How are Utility Values Determined?

This is a critical and often controversial question. These numbers are not arbitrary. They are derived from rigorous research studies where thousands of individuals from the general population are asked to rate various health states. Common methods include:

Method Description
Standard Gamble

Participants are offered a choice between two alternatives: (A) living with a chronic health state for a period of time (e.g., 10 years with severe arthritis), or (B) taking a gamble on a medical procedure that has a certain probability (p) of returning them to perfect health for the same period, but also a probability (1-p) of immediate death. The probability ‘p’ is varied until the participant is indifferent between the certain outcome and the gamble. That probability becomes the utility value for the health state.
Time Trade-Off (TTO)

Participants are asked to imagine they have a chronic condition for a certain amount of time (e.g., 10 years) and are then asked how many years of their life they would be willing to give up to live in perfect health instead. If they are willing to trade 10 years in the diseased state for 8 years in perfect health, the utility value of the diseased state is 0.8 (8 years / 10 years).
Rating Scales (e.g., Visual Analogue Scale)

A simpler method where participants are shown descriptions of various health states and asked to rate them on a scale from 0 (worst imaginable health/death) to 100 (best imaginable health). These ratings are then converted to a 0-1 scale.

Researchers have compiled massive catalogs of these utility values for hundreds of different health conditions, which are then used as inputs for economic models.

Putting It All Together: A QALY Calculation in Practice

Let’s consider a patient with a chronic, progressive disease. Without a new treatment, their expected future is:

  • 5 years in a state of moderate disease (Utility = 0.7)
  • Followed by 5 years in a state of severe disease (Utility = 0.4)
  • Followed by death.

The total QALYs generated without the new treatment would be: $$ (0.7 \times 5 \text{ years}) + (0.4 \times 5 \text{ years}) = 3.5 + 2.0 = mathbf{5.5 \text{ QALYs}} $$

Now, a new drug becomes available. With this new treatment, the patient’s expected future is:

  • 10 years in a state of mild, well-controlled disease (Utility = 0.9)
  • Followed by death. (The drug improves quality of life but does not extend it in this example).

The total QALYs generated with the new treatment would be: $$ (0.9 \times 10 \text{ years}) = mathbf{9.0 \text{ QALYs}} $$

The Incremental QALY Gain from the new drug is the difference between the two scenarios: $$ 9.0 \text{ QALYs} – 5.5 \text{ QALYs} = mathbf{3.5 \text{ QALYs}} $$

This number—3.5 QALYs—is the quantified health benefit of the new drug. It is the “Effect” part of the cost-effectiveness equation. The P&T committee now has a standardized way to measure the drug’s value, which can be compared to the value of any other health intervention.

24.4.3 The Ultimate Metric of Value: A Masterclass on the ICER

Once health economists have quantified the benefit of a new drug in terms of QALYs gained, they can proceed to the final and most important calculation in value assessment: the Incremental Cost-Effectiveness Ratio (ICER). The ICER is the metric that brings it all together. It answers the question: “How much extra are we paying for each extra unit of health we are getting?” It is the ratio of the additional cost of a new therapy to its additional health benefit, compared to the current standard of care.

The ICER Formula: The Lynchpin of Payer Decisions

$$ \text{ICER} = \frac{\Delta \text{Cost}}{\Delta \text{Effect}} = \frac{(\text{Cost}_{\text{New Drug}}) – (\text{Cost}_{\text{Standard Care}})}{(\text{QALYs}_{\text{New Drug}}) – (\text{QALYs}_{\text{Standard Care}})} $$

The output of this formula is expressed as a monetary value per QALY gained (e.g., $50,000 per QALY).

A Step-by-Step ICER Calculation: The Case of “Innovate-mab” for Rheumatoid Arthritis

Let’s walk through a detailed, realistic calculation that a P&T committee would review. A new biologic, “Innovate-mab,” has been approved for rheumatoid arthritis in patients who have failed methotrexate.

Standard of Care: “Legacy-cept”
  • Total 10-Year Cost: Includes drug cost, administration, monitoring labs, and projected costs of treating flare-ups. Total = $200,000
  • Total 10-Year Health Outcome: Based on clinical trial data and utility values for RA, patients are projected to gain 6.2 QALYs.
New Drug: “Innovate-mab”
  • Total 10-Year Cost: Higher drug cost but lower costs from averted flare-ups and hospitalizations. Total = $350,000
  • Total 10-Year Health Outcome: Superior efficacy leads to more time in remission and a better quality of life. Patients are projected to gain 7.7 QALYs.
Step 1: Calculate the Incremental Cost ((Delta)Cost)

This is the additional cost of using Innovate-mab over Legacy-cept.

$$ \Delta \text{Cost} = $350,000 – $200,000 = mathbf{$150,000} $$

Step 2: Calculate the Incremental Effect ((Delta)Effect)

This is the additional health benefit, in QALYs, gained by using Innovate-mab.

$$ \Delta \text{Effect} = 7.7 \text{ QALYs} – 6.2 \text{ QALYs} = mathbf{1.5 \text{ QALYs}} $$

Step 3: Calculate the Final ICER

Divide the incremental cost by the incremental effect.

$$ \text{ICER} = \frac{$150,000}{1.5 \text{ QALYs}} = mathbf{$100,000 \text{ per QALY gained}} $$

Interpreting the Result: The Willingness-to-Pay (WTP) Threshold

The P&T committee is now faced with a clear value proposition: “To gain one extra year of perfect health for a patient with RA by using Innovate-mab instead of Legacy-cept, we must spend an additional $100,000.” Is this a good value?

To answer this, payers compare the ICER to a Willingness-to-Pay (WTP) threshold. This is the maximum amount a society or health system is willing to spend to gain one QALY. In the United States, there is no official, government-mandated WTP threshold. However, an informal consensus has emerged, and analysts often use benchmarks like:

  • ICER < $50,000/QALY: Highly cost-effective. Very likely to be covered with minimal restrictions.
  • ICER $50,000 – $150,000/QALY: Often considered cost-effective and a reasonable value. Likely to be covered, perhaps on a preferred tier.
  • ICER > $150,000/QALY: May not be considered a good value. Likely to face significant access restrictions, such as placement on a non-preferred tier with a PA requiring failure of all cheaper options.

In our example, the ICER of $100,000 per QALY falls squarely in the “reasonable value” category. The P&T committee would likely recommend adding Innovate-mab to the formulary. The final tiering would then depend on the rebate negotiation.

24.4.4 The Affordability Question: Budget Impact Models (BIM)

A favorable cost-effectiveness ratio is a necessary, but not sufficient, condition for a drug to gain unrestricted formulary access. A drug can represent a “good value” but still be unaffordable if too many people need it. This is where the second major tool of HEOR comes into play: the Budget Impact Model (BIM).

While a Cost-Effectiveness Analysis (CEA) answers the question of “Is it worth it?”, a BIM answers the question of “Can we afford it?”. A BIM is essentially a sophisticated financial forecast. It does not measure value in terms of QALYs. It measures the total financial consequence of a formulary change on the health plan’s budget over a defined period, typically 1 to 5 years.

Deconstructing a Budget Impact Model

A BIM is a mathematical model with several key inputs that produce a single, critical output.

Model Inputs
Population Size

Total number of members in the health plan.

Disease Prevalence

What percentage of the members have the target disease?

Market Share Projections

What percentage of eligible patients are expected to use the new drug versus existing drugs, year by year?

Drug Costs

The net cost (after rebates) of the new drug and all comparator drugs.

Medical Cost Offsets

Any savings from averted hospitalizations, ER visits, or other medical procedures due to the new drug’s efficacy.

Model Output
Net Budget Impact

The total change in the health plan’s pharmacy and medical spending over the next 1-5 years, often expressed as a Per Member Per Month (PMPM) cost increase.

A P&T committee will review the BIM alongside the CEA. Even if the CEA shows the drug is cost-effective (a good value), if the BIM shows that adding the drug to the formulary will increase the plan’s total PMPM costs by an unacceptably high amount, the plan will be forced to implement restrictive utilization management. This is the origin of many step-therapy protocols. The plan is essentially saying, “We agree this drug is a good value for some patients, but we can’t afford to give it to everyone first-line. Therefore, we will require patients to try and fail the cheaper alternative(s) first to manage the overall budget impact.”