Module 1: The Value Question

Economic evaluation in healthcare begins with a deceptively simple question: is this intervention worth it? Our first module examines what that question really means, why it is harder to answer than it appears and how cost-effectiveness analysis (CEA) provides a structured framework for doing so.

• opportunity cost as the foundational concept — every healthcare decision displaces an alternative and economic evaluation makes that trade-off explicit
• the CEA framework — incremental costs, incremental outcomes and the incremental cost-effectiveness ratio (ICER) as the primary metric of value
• the spectrum of economic evaluation — cost-minimisation, cost-effectiveness, cost-utility, cost-benefit — and why cost-utility analysis has become the dominant form
• a brief history of economic evaluation in health technology assessment (HTA) — from academic curiosity to regulatory requirement

Module 2: Measuring What Matters — Health Outcomes in Economic Evaluation

Before a health economic model can be built the analyst must decide what to measure. This module explores the range of outcome measures used in CEA, from natural clinical units to generic preference-based measures, and explains why the choice of outcome metric shapes everything that follows.

• clinical endpoints versus economic outcomes — why survival rates and disease-free progression cannot simply be imported from a trial into an economic model
• intermediate and final outcomes— the challenge of linking surrogate endpoints to long-run health gain
• generic preference-based outcome measurement — what makes an instrument suitable for use in HTA and why agencies specify particular instruments
• an introduction to the quality-adjusted life year (QALY) as the currency that makes health gains comparable across diseases, interventions, and patient populations

Module 3: The QALY — Theory, Practice and Controversy

The QALY is the most important and most contested concept in HTA. This module gives learners the thorough grounding in QALY methodology that is essential for building credible submissions and engaging critically with HTA decisions.

• utility theory and the von Neumann-Morgenstern framework — the theoretical basis for attaching numerical values to health states
• health state valuation methods: time trade-off, standard gamble and visual analogue scale — how each works, what each measures and their relative strengths and limitations
• the EQ-5D in practice: the 3L and 5L versions, NICE-preferred value sets and how mapping studies derive utility values from non-preference-based clinical instruments
• the active controversies surrounding the QALY: severity, end-of-life conditions and the experiences of disabled patients — and the implications for submissions

Module 4: Designing the Analytical Framework

Economic models are only as credible as the decisions made before the first formula is entered. This module works through the structural choices that determine whether a submission will be considered methodologically sound by HTA reviewers.

• the NICE reference case — what it requires, why it exists, and how departures from it must be justified
• defining the comparator and perspective: what “standard of care” means in practice and how perspective choices differ across jurisdictions
• time horizons  — why chronic conditions typically require lifetime modelling and how to justify a shorter horizon when trial data does not support extrapolation
• discounting costs and health outcomes at 3.5% per annum — the rationale, the mechanics, and the common errors analysts make

Module 5: Modelling Short-Term Decisions — Decision Trees

This module introduces decision trees as the appropriate structure for interventions with short time horizons or acute decision problems.

• when a decision tree is the right modelling choice — acute conditions, screening programmes, diagnostic pathways and procedural interventions
• tree anatomy — decision nodes, chance nodes, terminal nodes, branches and probabilities
• assigning costs and utility values to pathways and calculating expected costs and expected QALYs
• the limits of decision trees — why a model that cannot represent disease progression will not satisfy HTA requirements for most chronic condition submissions

Module 6: Modelling Disease Progression — Markov Models

Markov models are the most widely used structure in HTA and building one well is the core practical competency this course delivers. This module takes learners from the conceptual framework through to a fully populated model using Microsoft Excel.

• the Markov framework — defining mutually exclusive and exhaustive health states that reflect the clinical and economic pathway of the disease
• transition probabilities — sources, structures and how to handle time-varying transitions when constant rates are not clinically plausible
• cycle length, cohort simulation and the half-cycle correction — technical choices that affect results and attract scrutiny from reviewers
• tunnel states and other structural refinements for conditions where a patient’s history within a state affects their subsequent transitions

Module 7: Building the Cost-Effectiveness Model in Excel

This is the hands-on core of the course. Working from the Markov structure introduced in Module 6, participants will build a complete, auditable cost-effectiveness model using Microsoft Excel — generating an ICER, a cost-effectiveness plane and a cost-effectiveness acceptability curve.

• workbook architecture for a CEA model — separating parameters, cohort trace, cost and outcome accumulation and results outputs into a logical, auditable structure
• good modelling practice — assumption transparency, colour-coding conventions, version control and the documentation habits that matter when a model faces HTA scrutiny
• costing the model — identifying resource use categories, sourcing unit costs and generating incremental costs and incremental QALYs to compute the ICER
• model validation— internal consistency checks, face validity tests and comparison against published analyses

Module 8: Uncertainty, Thresholds and Making the Case to Decision-Makers

The final module moves from technical construction to the analytical and communication skills needed to present cost-effectiveness evidence persuasively to HTA bodies, payers and clinical stakeholders — and to defend it under scrutiny.

• deterministic sensitivity analysis — varying parameters one at a time and in combination to identify the key drivers of the ICER, presented as Tornado diagrams
• probabilistic sensitivity analysis — assigning distributions to uncertain parameters, running Monte Carlo simulations and generating the cost-effectiveness plane scatter plot and cost-effectiveness acceptability curve
• threshold analysis and cost-effectiveness criteria in context — NICE’s £20–30k base range, end-of-life flexibilities, the severity modifier and the role of commercial negotiation
• presenting to non-technical audiences — translating ICERs and acceptability curves into value narratives that resonate with procurement committees and clinical champions