Given the advantages in transparency, reproducibility, adaptability and computational efficiency in R, there is a growing interest
in converting existing spreadsheet-based models into an R script for model re-use and upskilling training among health
economic modellers. The objective of this exercise was to convert the Scottish Cardiovascular Disease (CVD) Policy Model
from Excel to R and discuss the lessons learnt throughout this process. The CVD model is a competing risk state transition
cohort model. Four health economists, with varied experience of R, attempted to replicate an identical model structure in
R based on the model in Excel and reproduce the intermediate and final results. Replications varied in their use of specialist
health economics packages in addition to standard data management packages. Two versions of the CVD model were
created in R along with a Shiny app. Version 1 was developed without health economics specialist packages and produced
identical results to the Excel version. Version 2 used the heemod package and did not achieve the same results, possibly
due to the non-standard elements of the model and limited time to adapt the functions. The R model requires less than half
the computational time than the Excel model. Conversion of the spreadsheet models to script models is feasible for health
economists. A step-by-step guide for the conversion process is provided and modellers’ experience is discussed. Coding
without specialist packages allows full flexibility, while specialist packages may add convenience if the model structure is
suitable. Whichever approach is taken, transparency and replicability remain the key criteria in model programming. Model
conversions must maintain standards in these areas regardless of the choice of software.
