Simplifying Parameter Conversion and Documentation: Introducing ParCC v1.4 for Health Economic Evaluation

Deriving parameters for health economic models often requires multiple conversions, assumptions, and adjustments based on evidence from different sources. Without systematic documentation, these transformations can be difficult to reproduce, justify, or report transparently during peer review and HTA submissions. This raises an important question: how can researchers streamline these processes without compromising methodological rigour?

ParCC v1.4 is an R Shiny web application developed by the Regional Resource Centre for HTA at the All India Institute of Medical Sciences (AIIMS) Bhopal, to address these challenges. The tool extends beyond conversions and calculations, enabling users to maintain an auditable record of parameter transformations by documenting formulas, literature sources, and assumptions throughout the modelling process and HTA submission workflow. Each calculation can be reviewed, timestamped, and exported as an HTML/CSV report, helping researchers build their technical appendix with every step. Users can access the tool at the following link: https://cfm-parcc.share.connect.posit.cloud/

So, when should you use this tool? ParCC v1.4 is most useful during evidence synthesis and model parameterization, especially when inputs originate from multiple studies and require several conversions. The tool can boost efficiency by allowing the user to review, reproduce, and justify every step involved in deriving model inputs following nuanced economic calculations. 

The application converts between rates, probabilities, odds rations and hazard ratios while maintaining a documented record of the methods used, including approaches such that proposed by Zhang and Yu (1998). ParCC v1.4 now also supports survival extrapolation using exponential, Weibull, and log-logistic models, allowing users to generate long-term survival estimates critical to health economic evaluations.

In addition, ParCC v1.4:

• Fits beta, gamma, log-normal, and Dirichlet distributions for probabilistic sensitivity analysis using methods of moments
• Performs economic calculations central to decision modelling, including incremental cost-effectiveness ratios (ICERs), net monetary benefit (NMB), value-based pricing, and budget impact analyses
• Adjusts costs through inflation, discounting, purchasing power parity, and background mortality calculations using life-table methods

The current version – ParCC v1.4, at this stage, will require a final step to export accumulated workings before leaving the application since the session log can disappear when closing the browser. Additionally, it is advised for users to exert methodological judgement when selecting appropriate conversion methods and model inputs on this platform.

Ultimately, ParCC v1.4 offers users a practical solution for improving transparency, reproducibility, and documentation throughout the modelling process.

You can explore and start using ParCC v1.4 through the links below:

1. Live app: cfm-parcc.share.connect.posit.cloud 

2. CRAN: CRAN.R-project.org/package=ParCC 

3. GitHub: github.com/drpakhare/ParCC 

4. Tutorials and formula references: drpakhare.github.io/ParCC 

Acknowledgements:

This tool was developed by the Regional Resource Centre for HTA at AIIMS Bhopal. We thank Abhijit P. Pakhare, Soumya Jain, Shivansh Verma, Varun Kumar Kashyap, Anvita G. Malhotra, Biju Soman, Oshima Sachin, Beena Joshi, and Ankur Joshi for their guidance, input, and suggestions.

To report a bug, suggest a feature, or provide feedback on ParCC, please contact the development team at: [email protected]

References:

1.      Rstudio.com. (2023). Getting Started with ParCC. [online] Available at: https://cran.rstudio.com/web/packages/ParCC/vignettes/getting-started.html  

2.      Zhang, J. and Yu, K.F. (1998). What’s the Relative Risk? JAMA, 280(19), p.1690. doi: https://doi.org/10.1001/jama.280.19.1690.