ICER: The Gatekeeper of European Healthcare, or a Flawed Oracle?

The Incremental Cost-Effectiveness Ratio (ICER) is the darling of health economists and the bane of pharmaceutical companies. At its heart, ICER asks a seemingly simple question: how much are we willing to pay for one extra year of quality life? In practice, however, it has become a highly sophisticated—and occasionally absurd—framework for deciding which treatments make the cut in Europe’s health systems.

The ICER is both the gatekeeper and the scapegoat of modern healthcare. Pharmaceutical companies accuse it of stifling innovation; health systems use it to justify rationing care. And somewhere in the middle sits the patient, wondering why their life-saving treatment didn’t make it past the algorithm. Let’s unpack how ICER works, its glaring flaws, and the real-world drama it creates—sprinkled with a bit of humor because, frankly, health economics could use it.

The ICER Formula: Simple, Yet Problematic

The ICER is calculated as follows:

$$
\text{ICER} = \frac{\text{Cost of New Treatment} - \text{Cost of Standard Treatment}}{\text{Effectiveness of New Treatment} - \text{Effectiveness of Standard Treatment}}
$$

Here, costs include drug prices, hospital stays, and other direct medical expenses, while effectiveness is typically measured in Quality-Adjusted Life Years (QALYs). A treatment that costs $50,000 more than the standard but adds 2 QALYs has an ICER of $25,000 per QALY.

If the ICER falls below a pre-determined threshold, the treatment is deemed cost-effective. Simple enough—except that every step of this process is riddled with assumptions and value judgments.

ICER in Practice: A European Tour

United Kingdom: NICE and the £30,000 Threshold

The National Institute for Health and Care Excellence (NICE) employs ICER to assess the cost-effectiveness of treatments, generally using a threshold range of £20,000 to £30,000 per QALY. Treatments with ICERs below this range are typically considered cost-effective.

In 2016, NICE evaluated Orkambi, a cystic fibrosis medication, and concluded that its benefits did not justify its high cost, leading to its rejection for NHS use. This decision sparked public outcry and highlighted the challenges of applying rigid ICER thresholds to life-saving treatments.

Germany: IQWiG's Approach to Added Benefit

Germany's Institute for Quality and Efficiency in Health Care (IQWiG) does not rely on explicit ICER thresholds. Instead, it evaluates the "added benefit" of new treatments over existing ones. For example, in its assessment of empagliflozin for renal insufficiency, IQWiG concluded that an added benefit was not proven.

ICER’s Limitations

1. Arbitrary Thresholds

ICER thresholds vary widely across Europe, reflecting cultural and political factors rather than scientific consensus. Why is £30,000/QALY acceptable in the UK but €50,000/QALY in France? Such inconsistencies reveal ICER’s inherent subjectivity and erode its credibility as an objective tool.

2. The Subjectivity of QALYs

QALYs are intended to measure both the quantity and quality of life gained from a treatment. But how do you quantify "quality"? Assigning a score of 0.7 to a year spent living with moderate pain is a deeply subjective exercise, open to cultural and personal biases.

For instance, a treatment that improves mobility might score highly in a younger population but much lower in an elderly group that values cognitive improvements more. This subjectivity undermines ICER’s claims of precision.

3. Ignoring Indirect Benefits

ICER focuses narrowly on direct health outcomes, often neglecting broader societal impacts. Consider Alzheimer’s treatments: while their impact on QALYs may seem modest, they can significantly reduce caregiver burden and healthcare costs associated with institutional care. ICER’s failure to capture such benefits skews its assessments.

4. Gaming the System

Pharmaceutical companies may potentially manipulate ICER calculations. By choosing weaker comparator drugs or emphasizing short-term benefits, they can produce ICERs that appear far more favorable than real-world outcomes would suggest. This gaming erodes trust in the metric.

5. Rare Events and Tail Risks

ICER assumes a smooth distribution of outcomes, but healthcare is rife with tail risks—rare, high-impact events that dominate costs and outcomes. Extreme Value Theory (EVT) offers a more nuanced framework for capturing these risks:

$$
P(X > x) = \left( 1 + \xi \frac{x - \mu}{\sigma} \right)^{-\frac{1}{\xi}}
$$

EVT helps account for outliers, such as rare adverse events or unexpectedly high efficacy in certain subgroups, which traditional ICER models often overlook.

A Personal Take: The Economist Meets the Health Economist

ICER is a powerful idea shackled by its own limitations. Its reliance on QALYs, arbitrary thresholds, and narrow definitions of value make it feel more like an economic litmus test than a true measure of societal benefit.

But perhaps the real problem lies in our expectations. ICER was never meant to be a perfect arbiter—it’s a tool, not a verdict. Like all tools, it is only as good as the hands that wield it. And in healthcare, where life and death hang in the balance, those hands must exercise both rigor and humility.

Until then, ICER will remain what it has always been: a crystal ball with cracks, illuminating just enough to guide us, but never quite enough to reveal the full picture.