Local adaptation of cost-effectiveness and budget impact models

The problem

Many economic evaluations used in African decision-making were built for another setting. Unit costs, care pathways, epidemiology, discount rates and comparators are often carried over from high-income or regional models without adjustment. Decision-makers and technical reviewers rightly question results they cannot trace to local evidence, and a global model that is not adapted rarely answers the question a ministry, insurer or technical working group is actually asking.

Our approach

1. 01

   Scope the decision problem

   Agree the population, comparators, perspective, time horizon and outcome measure (DALYs or QALYs) with you and, where relevant, the end user of the evidence.

2. 02

   Review the source model

   Rebuild or audit the original model structure in R so that every calculation is transparent and reproducible, and document any errors or limitations we find.

3. 03

   Replace inputs with local evidence

   Source local costs, resource use, epidemiology and practice patterns; where local data do not exist, we state the proxy used and test it in sensitivity analysis.

4. 04

   Analyse and check

   Run deterministic and probabilistic analyses and scenario tests, then pass the model through independent quality control before results are released.

All work follows our six-step pipeline with three expert sign-off gates.

Deliverables

• Adapted model in R (or Excel on request) with a version-controlled code repository
• Parameter table with a source, justification and range for every input
• Technical report aligned with CHEERS 2022
• Budget impact analysis over a payer-relevant horizon, where required
• Results briefing for technical and non-technical audiences