Budget impact analysis: health economic studies
How to use a budget impact analysis to evaluate your digital health product.
This page is part of a collection of guidance on evaluating digital health products.
Budget impact analysis (BIA) is an analysis tool that can help you assess the expected changes in the health expenditure of the budget holder (for example, the healthcare system) as a result of implementing your digital product.
BIA can be conducted:
- on its own – for example, to assess how affordable your product is likely to be, given potential budget constraints
- alongside a health economic evaluation – for example, to help decision makers assess the financial consequences of recommending your product for the healthcare system
BIA often complements health economic evaluations, but it has a distinct focus. BIA:
- often takes the budget holder perspective
- only includes costs and any savings that might accrue
- evaluates affordability not value for money
What to use it for
Use a BIA when:
- you want to assess the likely financial impact of your product before you implement it
- you need to work out whether your product will be affordable within the decision maker’s budget constraints if it is recommended for use
Pros
Advantages of BIA include:
- it helps you to understand costs both incurred and saved by implementing your product
- it gives an estimate of the impact of your product on the decision maker’s budget
Cons
Drawbacks of BIA include:
- it cannot tell you whether your product is good value for money or not
- it usually excludes costs from changes in effects that cannot be monetised, such as benefits captured by clinical measures
How to carry out a budget impact analysis
BIA typically involves the following steps:
1. Specify the target population
Start by working out what population is likely to be impacted by the new product. This includes:
- estimating the population size, which usually corresponds to the number of individuals with the relevant disease or condition (prevalence) and the number of new cases (incidence) that require treatment and are likely to benefit from your product
- accounting for potential untreated individuals who may decide to seek treatment after you product is made available
- breaking down the population by disease severity or stage as a way of carrying out BIA for population subgroups – and recognising that the proportion of individuals at different stages can change over time as your product is being adopted
2. Set the boundaries of the analysis
You will need to decide the timescale for your impact analysis. This is the duration over which you will measure changes to health expenditure and cost savings.
The duration you choose will depend on the budget holder’s planning timescale and is often not related to the duration of the disease. This means it is important to carefully consider whether the changes in expenditure and cost savings are likely or not to materialise within the timescale you choose.
3. Determine treatment mix
An important element of BIA is determining any changes to treatment mix as a result of making your product available. This will depend on:
- the uptake of your product
- whether your product replaces or supplements current options
For example, if your product replaces an existing one, you will need to make an assumption about the costs saved by displacing the existing product.
4. Estimate product and disease-related costs
To estimate the costs associated with your product you should follow general considerations for measuring costs in health economic evaluations. However, relevant costs for BIA may differ because it often takes a more restrictive budget holder perspective. For example, BIA is unlikely to include development costs or costs to the patient.
You should also consider changes to disease-related costs if your product is likely to affect these. For example, if your product helps patients prevent heart conditions, then the avoided costs of treating those conditions should be considered in BIA. This is particularly relevant when your product is expected to have an immediate impact on disease-related expenditure, which may be the case with acute conditions.
5. Report the results
Budget impact results should be reported in a disaggregated way – that is, with main cost components reported individually. This will enable the budget holder to understand the relative weight of each cost component to the total cost impact. The budget impact should also be reported separately for each year considered in the analysis.
BIA studies should include a set of sensitivity analysis scenarios (see ‘Sensitivity analysis’ in Analyse your data: evaluating digital health products). These scenarios allow you to understand the impact of making alternative assumptions about important aspects of the study on the budget impact assessment. For example, it may be helpful for you to understand how the budget impact changes according to alternative assumptions about population size, treatment mix and cost measurements.
Example: Digital diabetes and hypertension care
See Nordyke and others (2019): Estimating the impact of novel digital therapeutics in type-2 diabetes and hypertension: health economic analysis.
This study explores the economic impact of digital behavioural interventions (mobile apps) for managing patients with high-cost cardiometabolic diseases, such as type-2 diabetes and hypertension. The analysis was conducted from the viewpoint of the US commercial payer. A 3-year timescale was chosen, taking into account significant enrolee turnover and the fact that engagement with and impact of these apps tend to wane over time.
The population expected to benefit from the apps included individuals with active disease (either type-2 diabetes or hypertension) who were receiving conventional pharmacological treatment.
The digital interventions were expected to supplement conventional pharmacological treatments, so the budget assessment focused on the cost implications of adding the behavioural intervention to the existing treatment mix. The study allowed for potential drop-out (treatment discontinuation) over the 3-year period.
The study considered 3 budget components:
- cost of implementing the digital interventions
- medications costs – including any changes to pharmacological treatments as a result of adopting the behavioural interventions
- cost savings associated with likely reduction in cardiovascular events and related hospitalisations
The study found that the digital health interventions would lead to an estimated cost saving of:
- $145 per patient, per month, for the type-2 diabetes population
- $97 per patient, per month, for hypertensive patients
This would represent a reduction of 22% and 29% in total health expenditures compared to the conventional pharmacological care pathways. Any assumed savings, such as the proposed cost savings due to reduction in cardiovascular disease-related hospitalisations, should be examined in sensitivity analysis (not done in this study).
More information and resources
NICE Evidence Standards Framework for Digital Health Technologies (2019) – Cost Consequences and Budget Impact Analyses and Data Sources. This guide describes the principles of budget impact analysis (BIA) as part of NICE’s evidence standards framework for digital health technologies.
NICE Budget Impact template. This is the recommended budget assessment template document for submitting BIA to NICE as part of its health technology assessment programme.
NICE Assessing resource impact process manual – technology appraisal and highly specialised technologies (2017). This manual describes the processes involved in assessing resource impact of health technologies.
Sullivan and others (2012): Budget impact analysis – principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. The study provides a methods guide for conducting BIA. This includes methodological insights on the analytic framework for BIA, recommendations of data sources to inform budget assessments and guidance on reporting standards.
Mauskopf and Earnshaw (2016): A methodological review of US budget impact models for new drugs. This study critically assesses the extent to which published BIA studies follow recommended methodological guidelines. While the review covered budget assessment studies that inform recommendations about new drugs, the findings of the review are fully relevant to anyone conducting BIA of novel digital products.