Module 1: Foundations of Budget Impact Analysis

This module introduces the core concepts of budget impact analysis (BIA) – establishing how it differs from other forms of economic evaluation and why healthcare payers increasingly require it.

• the distinction between affordability and value – and why payers need to evaluate both
• the payer’s perspective: how budget holders think about the financial consequences of adopting new technologies
• the ISPOR Principles of Good Practice for Budget Impact Analysis as the methodological foundation for the course
• how a technology can be cost-effective yet unaffordable: a case study illustrating why BIA exists as a distinct discipline
• the growing importance of BIA in reimbursement, formulary, and procurement decisions worldwide

Module 2: The Role of Budget Impact Analysis in Health Technology Assessment

This module maps the global health technology assessment (HTA) landscape and examines the specific role BIA plays in each system’s decision-making framework.

• HTA requirements for BIA across major jurisdictions including NICE, G-BA/IQWiG, HAS, CADTH and PBAC
• NICE’s budget impact test in practice: the £40m threshold, commercial negotiations, and managed access arrangements
• how BIA requirements differ for pharmaceuticals, medical devices and diagnostics
• reviewing real-life HTA submission dossiers to understand how BIA evidence is presented alongside clinical and economic data

Module 3: Conceptualising a Budget Impact Model

This module works through the key structural choices that determine whether a budget impact model is fit for purpose, culminating in the development of a model concept document.

• defining the relevant budget holder’s perspective and the appropriate cost categories that flow from it
• estimating the eligible patient population using prevalence-based and incidence-based approaches
• selecting the appropriate time horizon, typically one to five years, and justifying the choice
• designing the current and future treatment mix scenarios, including market uptake curves and diffusion assumptions
• developing a model concept document that mirrors real-world HTA submission and payer dossier practice

Module 4: Populating the Model I — Epidemiological and Clinical Inputs

This module addresses the critical challenge of estimating the size of an eligible population and incorporating the clinical inputs that determine resource use differences between comparators.

• building an epidemiological funnel in Excel: from total population through to diagnosed, treated, eligible, and uptake-adjusted patients
• sourcing population and prevalence data from published epidemiology, disease registries and hospital episode statistics
• incorporating treatment patterns and market share data using sources such as OpenPrescribing and IQVIA
• structuring clinical inputs including efficacy, treatment duration, discontinuation rates and adverse event rates
• critically appraising data sources for relevance, quality and transferability to the decision-making context

Module 5: Populating the Model II — Cost and Resource Use Inputs

This module focuses on identifying, sourcing and structuring the cost inputs that allow a model to estimate the financial consequences of adopting a health intervention.

• identifying all relevant cost categories: acquisition, administration, monitoring, adverse event management and hospital resource use
• how to source unit costs from standard references
• calculating gross budget impact versus net budget impact and understanding when each is appropriate
• handling one-off versus recurring costs, capital versus revenue expenditure and the challenge of budget silos
• structuring cost inputs for transparency and auditability within the model workbook

Module 6: Building the Budget Impact Model in Excel

This is the core practical module in which learners build a fully functional budget impact model in Excel, step by step, following a structured workbook architecture.

• workbook design and architecture: inputs, population, market share, costs, results and scenario sheets
• good modelling practice: transparent formulae, colour-coding conventions, error checks and version control
• building the model end-to-end using a realistic case study, from population sizing through to a three-to-five-year budget impact trajectory
• validation and debugging techniques to ensure the model produces credible and defensible results
• adapting the model structure for different technology types, including devices, diagnostics and pharmaceuticals

Module 7: Uncertainty, Sensitivity Analysis and Scenario Planning

This module teaches learners how to characterise, quantify, and communicate the uncertainty inherent in every budget impact model.

• Conducting one-way and multi-way deterministic sensitivity analysis to identify the parameters that most influence results
• creating tornado diagrams and threshold analyses to visualise the drivers of budget impact
• designing meaningful scenario analyses — best case, worst case and base case — that resonate with budget holders
• understanding when probabilistic sensitivity analysis is and is not appropriate in the context of BIA
• transparent presentation of uncertainty results so that decision-makers understand the range of possible financial outcomes

Module 8: Interpreting, Presenting and Defending Budget Impact Results

The final module bridges the gap between technical modelling and real-world decision-making, equipping learners to present and defend their findings in any payer context.

• presenting BIA results effectively in HTA submission dossiers, business cases and payer value propositions
• common pitfalls that undermine credibility: double-counting, inappropriate time horizons and unrealistic uptake assumptions
• how HTA reviewers critique BIA submissions, with lessons drawn from published NICE technology appraisals
• structuring a compelling budget impact narrative that connects financial projections to the payer’s strategic priorities
• emerging trends: real-world evidence in BIA, dynamic budget impact modelling and the expanding role of BIA for medical devices