Base Case Analysis

The base case analysis is the primary analysis in a health economic evaluation that uses the most plausible, best supported set of assumptions and parameter values. It represents the central estimate of cost effectiveness or budget impact, and it serves as the reference point against which all sensitivity analyses are compared.

Health economic evaluations inform high stakes decisions about resource allocation, drug reimbursement, and clinical guideline development. The base case analysis provides the "headline" result that decision makers, including health technology assessment agencies such as NICE in England, Canada's Drug Agency (formerly CADTH), and PBAC in Australia, use as the starting point for their deliberations. The credibility of the entire evaluation rests on whether the base case assumptions are transparent, well justified, and consistent with the best available evidence. If the base case uses biased or poorly justified parameter values, even the most sophisticated sensitivity analyses cannot rescue the evaluation's conclusions.

Constructing the base case involves selecting values for every parameter in the economic model: clinical effectiveness estimates, baseline event rates, utility values, costs, time horizons, discount rates, and transition probabilities. Each parameter should be derived from the best available evidence, prioritizing data from high quality randomized controlled trials, systematic reviews, and validated cost databases.

The analyst must also make structural assumptions about the model itself, such as the choice of model type (decision tree, Markov model, discrete event simulation), the health states or pathways included, the cycle length, and the perspective (healthcare system, societal, or payer). Each of these choices affects the results and should be justified with reference to clinical guidelines, methodological guidance from the relevant health technology assessment body, and the specific decision context.

The base case typically adopts the perspective and discount rate recommended by the target audience. For example, NICE guidance specifies an NHS and Personal Social Services perspective with costs and health outcomes discounted at 3.5% per year. The time horizon should be long enough to capture all relevant costs and outcomes, which for chronic diseases may mean a lifetime horizon.

Results of the base case analysis are usually expressed as an incremental cost effectiveness ratio (ICER), calculated as the difference in costs between the intervention and comparator divided by the difference in health outcomes (typically quality adjusted life years). The ICER is then compared to the willingness to pay threshold to determine whether the intervention represents good value for money. For example, NICE in England has used a range of 25,000 to 35,000 pounds per QALY since April 2026 (previously 20,000 to 30,000 pounds).

A base case analysis is the reference result of a formal health economic evaluation, whether it is a cost effectiveness analysis, cost utility analysis, cost benefit analysis, or budget impact analysis. It provides the central estimate that decision makers need, and it anchors the sensitivity analyses that explore the impact of uncertainty. Researchers should clearly label the base case and distinguish it from scenario analyses and sensitivity analyses in their reporting.

A common error is selecting base case parameter values that favor a particular outcome, whether intentionally or through selective use of evidence. Analysts should use a systematic approach to parameter selection, documenting the sources and justifications for each value. Another mistake is adopting assumptions that are inconsistent with the relevant methodological guidelines, such as using a societal perspective when the target decision maker requires a healthcare payer perspective.

Researchers sometimes also confuse the base case with a "best case" scenario, selecting the most optimistic values for every parameter. The base case should use the most plausible values, not the most favorable ones. Finally, inadequate documentation of base case assumptions makes it difficult for reviewers and decision makers to evaluate the analysis and undermines its transparency and credibility.

A health economist constructs a Markov model to evaluate the cost effectiveness of a new biologic therapy for moderate to severe psoriasis. The base case uses efficacy data from a Phase III trial (PASI 75 response rate: 68% for the biologic vs. 22% for the comparator), utility values from a published systematic review of EQ 5D data in psoriasis, drug costs from the national formulary, and a 10 year time horizon with 3.5% discounting. The base case ICER is 24,500 pounds per QALY gained. Deterministic sensitivity analysis shows that the ICER is most sensitive to the drug price and the long term treatment discontinuation rate, while probabilistic sensitivity analysis indicates a 62% probability of cost effectiveness at a willingness to pay threshold of 30,000 pounds per QALY.