Economic Evaluation Alongside Clinical Studies

Definition and scope

A comparative analysis of costs and health outcomes collected alongside a randomized or observational study, with a common population, horizon, perspective, and uncertainty analysis. The target population, use, and analysis remain protocol decisions; this card explains the choices and their consequences rather than approving a study.

Operational specification

Define the economic estimand before collecting data: intervention, comparator, perspective, time horizon, resource categories, valuation year, utility instrument and value set. Preserve randomized allocation for an assignment-effect economic analysis; observational comparisons also require a justified causal design. Baseline utility imbalance can affect incremental QALYs even in a randomized study.

Analysis and diagnostics

Estimate adjusted mean costs and QALYs, their joint uncertainty, incremental net monetary benefit, and the cost-effectiveness plane/acceptability curve. Resample at the randomization or dependence unit and preserve cost-effect correlation. Address incomplete utility/resource measurements and censored cost follow-up explicitly. Report within-study results separately from extrapolated lifetime model results.

When NOT to use and common errors

A nonsignificant effect difference does not prove equivalence. Complete-case economic analysis can select survivors or well-observed patients. A ratio of expected incremental costs and effects is not the average of patient-level or simulation-draw ICERs.

Worked example and implementation boundary

Synthetic adjusted group means show an additional cost of 2400 currency units and 0.08 additional QALYs. At a stated illustrative willingness to pay of 50000 per QALY, calculate incremental net monetary benefit. Incremental NMB is 1600 currency units. This is a calculation at an illustrative threshold, not a reimbursement recommendation. The code performs that explicitly stated calculation with synthetic inputs. It is not a complete fitted analysis and does not demonstrate the identification assumptions, estimate sampling uncertainty, or certify application in another population.

Data-source and reporting requirements

Preserve the provenance, dates, units, and observation rule for each input. Claims capture services and transactions under observable benefits; absence of a record is not proof that an event or resource use did not occur. EHR and registry measurements depend on the collection process and may miss care outside the system. Linked sources add reconciliation and selection questions. Primary collection can improve a missing domain but still requires valid measurement and follow-up. Report which of these limitations affects the stated use, which evidence supports the chosen inputs, and what remains uncertain.

Worked example

Scenario

Synthetic adjusted group means show an additional cost of 2400 currency units and 0.08 additional QALYs. At a stated illustrative willingness to pay of 50000 per QALY, calculate incremental net monetary benefit.

Dataset

Synthetic inputs with units defined in the scenario; no patient data.

Steps

Result

Incremental NMB is 1600 currency units. This is a calculation at an illustrative threshold, not a reimbursement recommendation.

Trade-offs

Code example

delta_cost = 2400
delta_qaly = 0.08
threshold = 50000
result = threshold*delta_qaly-delta_cost
assert abs(result - 1600.0) < 1e-9
print(result)

delta_cost <- 2400
delta_qaly <- 0.08
threshold <- 50000
result <- threshold*delta_qaly-delta_cost
stopifnot(abs(result - 1600.0) < 1e-9)
print(result)

Citations

1. [1]Ramsey SD, Willke RJ, Glick H, et al. Cost-effectiveness analysis alongside clinical trials II — an ISPOR Good Research Practices Task Force report. Value in Health. 2015;18(2):161-172.
2. [2]Manca A, Hawkins N, Sculpher MJ. Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility. Health Economics. 2005;14(5):487-496.
3. [3]Husereau D, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Explanation and Elaboration: A Report of the ISPOR CHEERS II Good Practices Task Force. Value in Health. 2022.