Cost-Effectiveness and Health-Economic Analysis

Overview

Health-economic evaluation compares costs and outcomes of alternative strategies.

Common analyses include:

• cost-effectiveness analysis;
• cost-utility analysis using QALYs;
• cost–benefit analysis;
• budget-impact analysis.

The incremental cost-effectiveness ratio, ICER, is:

where $\Delta C$ is incremental cost and $\Delta E$ incremental health effect.

Why this matters

A treatment can improve health and increase cost.

Decision makers must consider whether additional benefit justifies the additional resources.

ICER interpretation becomes difficult when effects are near zero or when strategies are dominated.

Net benefit often provides a more stable inferential framework.

When to use economic evaluation

Use it when healthcare resources, outcomes and opportunity costs inform a decision.

The perspective may be:

• healthcare payer;
• health system;
• societal;
• patient.

Perspective determines included costs.

Research question and variables

Incremental net monetary benefit is:

where $\lambda$ is willingness to pay per health unit.

Positive NMB favours the new strategy at that threshold.

Data structure

Economic-analysis inputs

simulated data

Component	Example
Costs	Treatment, hospital, monitoring
Outcomes	QALYs or events avoided
Time horizon	Lifetime or trial period
Discounting	Costs and outcomes
Uncertainty	Parameter distributions

Statistical assumptions

Dominance

A strategy is strongly dominated if it costs more and produces less health.

Extended dominance occurs when a combination of alternatives is more efficient.

Dominated strategies should not define the final ICER frontier.

Worked example

Worked analysis in R

set.seed(20260806)

n_simulation <- 2000

incremental_cost <- rnorm(
  n_simulation,
  mean = 3500,
  sd = 2200
)

incremental_qaly <- rnorm(
  n_simulation,
  mean = 0.18,
  sd = 0.11
)

icer <- mean(
  incremental_cost
) / mean(
  incremental_qaly
)

willingness_to_pay <- 30000

net_benefit <- (
  willingness_to_pay *
  incremental_qaly -
  incremental_cost
)

c(
  mean_incremental_cost =
    mean(incremental_cost),
  mean_incremental_qaly =
    mean(incremental_qaly),
  icer = icer,
  probability_cost_effective =
    mean(net_benefit > 0)
)

Selected analysis output

Mean incremental cost ≈ 3,500
Mean incremental QALY ≈ 0.18
ICER ≈ 19,700 per QALY
Probability cost-effective at 30,000 per QALY ≈ 0.66.

Visualising joint uncertainty

Cost-effectiveness acceptability curve

A CEAC plots:

$$P(NMB>0)$$

across willingness-to-pay values.

It does not show the magnitude of net benefit or the optimal strategy alone.

Trial-based analysis

Cost data are often skewed and missing.

Use:

• appropriate mean-cost analysis;
• bootstrap or model-based uncertainty;
• multiple imputation;
• joint cost-effect modelling;
• sensitivity analysis beyond trial follow-up.

Median cost is usually not the decision-relevant estimand.

Model-based analysis

Decision models can include:

• decision trees;
• Markov models;
• discrete-event simulation;
• microsimulation.

Validate structure, inputs and code.

Interpreting the output

Presenting the analysis

Suggested reporting

Use CHEERS 2022 [1].

Report decision problem, perspective, comparators, horizon, discounting, model, inputs, currency year, uncertainty, heterogeneity and conflicts.

Standard economic-evaluation, decision-modelling and acceptability-curve methods are developed in specialist sources [2], [3], [4].

Common mistakes

Knowledge check

What is the ICER denominator?

Answer and reasoning

Incremental health effect.

What does positive NMB mean?

Answer and reasoning

The value of incremental health at the threshold exceeds incremental cost.

What is strong dominance?

Answer and reasoning

A strategy costs more and produces less health than another.

What does a CEAC show?

Answer and reasoning

Probability of cost-effectiveness across thresholds.

Why state perspective?

Answer and reasoning

It determines which costs and consequences are included.

Key take-home messages

References

1. Husereau D, Drummond M, Augustovski F, et al. CHEERS 2022 statement. BMJ. 2022;376:e067975. https://doi.org/10.1136/bmj-2021-067975
2. Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. 4th ed. Oxford: Oxford University Press; 2015.
3. Briggs AH, Claxton K, Sculpher MJ. Decision modelling for health economic evaluation. Oxford: Oxford University Press; 2006.
4. Fenwick E, O’Brien BJ, Briggs A. Cost-effectiveness acceptability curves. Health Econ. 2004;13(5):405–415. https://doi.org/10.1002/hec.903