Developing a Budget Impact R Shiney Application to Assess the Financial Implications of Implementing Organized Cancer Screening Programs in Countries with Limited Resources: Breast Cancer as an Example
Author(s)
Khader Al-Habash, PharmD, Abeer A. Al Rabayah, MBA, MSc;
King Hussein Cancer Center, Center for Drug Policy & Technology Assessment, Amman, Jordan
King Hussein Cancer Center, Center for Drug Policy & Technology Assessment, Amman, Jordan
Presentation Documents
OBJECTIVES: To develop an open-source budget impact analysis (BIA) model to assess the financial implications of organized cancer-screening strategies over five years’ time horizon, using breast cancer mammogram screening as an example.
METHODS: The BIA model was built following ISPOR good research practices. We based our methodology on four phases: building the initial model in Excel, writing the script code for BIA using R programming language, transforming the R code to shiny application, and validating the results. The input parameters for our case example from Jordan were: eligible Jordanian population categorized into age groups for screening based on several screening strategies, screening attendance rate, population growth rate, 5-years overall survival per stage, cost of screening, cost of diagnosis and treatment per cancer stage, sensitivity and specificity of mammogram screening, administrative cost of screening program. Costs were calculated based on selected screening strategies for comparison. The incremental cost per each strategy was determined. We included scripts to present the results in tables and charts for clear visualization and interpretation. The costs were presented in disaggregate form to show the cost of screening and the cost of treatment over the model’s time horizon. Costs can be reported in different currencies including Jordanian Dinar and US dollar.
RESULTS: The model is functional and predicts the cost of several screening strategies. We were able to determine the predicted incremental cost of several organized breast cancer-screening strategies compared with the current opportunistic screening strategy in Jordan (40-70 years annually, 3.5% attendance rate). The shiny application can be accessed through GitHub webpage.
CONCLUSIONS: The shiny application was user friendly and generated valid results upon comparing its result to BIA excel form. This open-source model is intended for to support decision makers in countries with limited resources and reduce the time required to develop such models from scratch.
METHODS: The BIA model was built following ISPOR good research practices. We based our methodology on four phases: building the initial model in Excel, writing the script code for BIA using R programming language, transforming the R code to shiny application, and validating the results. The input parameters for our case example from Jordan were: eligible Jordanian population categorized into age groups for screening based on several screening strategies, screening attendance rate, population growth rate, 5-years overall survival per stage, cost of screening, cost of diagnosis and treatment per cancer stage, sensitivity and specificity of mammogram screening, administrative cost of screening program. Costs were calculated based on selected screening strategies for comparison. The incremental cost per each strategy was determined. We included scripts to present the results in tables and charts for clear visualization and interpretation. The costs were presented in disaggregate form to show the cost of screening and the cost of treatment over the model’s time horizon. Costs can be reported in different currencies including Jordanian Dinar and US dollar.
RESULTS: The model is functional and predicts the cost of several screening strategies. We were able to determine the predicted incremental cost of several organized breast cancer-screening strategies compared with the current opportunistic screening strategy in Jordan (40-70 years annually, 3.5% attendance rate). The shiny application can be accessed through GitHub webpage.
CONCLUSIONS: The shiny application was user friendly and generated valid results upon comparing its result to BIA excel form. This open-source model is intended for to support decision makers in countries with limited resources and reduce the time required to develop such models from scratch.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
PT1
Topic
Methodological & Statistical Research
Disease
SDC: Oncology