A Simple Cost-Effectiveness Model of Screening: An Open-Source Teaching and Research Tool Coded in R

Area of Science:

• Health economics
• Biostatistics
• Public health

Background:

• Cost-effectiveness analysis (CEA) models are crucial for evaluating healthcare interventions.
• Existing CEA models are often complex and not ideal for illustrating fundamental methods.
• There is a need for accessible tools for teaching and researching disease screening cost-effectiveness.

Purpose of the Study:

• To develop a simple, open-source simulation model for disease screening cost-effectiveness.
• To provide a platform for teaching and research in health economic evaluations.
• To examine how variations in input parameters affect screening efficiency.

Main Methods:

• A vectorised, discrete-event simulation of screening was developed in R.
• An Excel interface was created for parameter definition and results inspection.
• An R Shiny app was implemented for dynamic interpretation of simulation outputs.

Main Results:

• The model illustrates the impact of screening parameters (e.g., cost, effectiveness, test performance) on cost-effectiveness.
• Reduced screening costs generally improve cost-effectiveness.
• Enhanced treatment of symptomatic disease can decrease net effectiveness and cost-effectiveness of screening.

Conclusions:

• The developed model serves as an accessible platform for methods research and teaching in cost-effectiveness analysis.
• The tool promotes an intuitive understanding of disease screening cost-effectiveness.
• The open-source model can be a public good for the research community.