Waiting list examples and communication aids

Currently contains:

• example_of_sim.R - example sim showing my simulation route to estimate them simulate a waiting list.
• waiting_times_distribution.R - plot showing the proportion of compliant patients at 18weeks, given different average waits.
• WL_factor_vs_probability_compliance - Shiny app, showing how factor argument interacts with % compliance, and calculates a target queue size.

Exponential Factor Compliance App

Access the app here: https://chrismainey.shinyapps.io/wl_factor_vs_probability_compliance/

This repository contains an interactive Shiny application that visualises the relationship between compliance (expressed as a percentage) and the exponential distribution factor required to meet a waiting list target.

The app uses:

• ggplot2 for plotting
• plotly for interactive graph features
• BSOLutils for Birmingham & Solihull ICB theme and colour styling
• shiny for the reactive interface

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Features

• Interactive compliance input (as a percentage)
• Dynamic exponential factor calculation using qexp()
• Interactive plotly-based visualisation with tooltips
• Display of:
  • Selected compliance (%)
  • Corresponding exponential factor
• Customised ICB colour palette and theme
• Enlarged graph area and refined layout for readability

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Running the App Locally

Clone the repository:

git clone https://github.com/Birmingham-and-Solihull-ICS/waiting_list_examples
cd waiting_list_examples/R

# Run the app from command line with:
Rscript -e "shiny::runApp('shiny_wl_factor.R', launch.browser = TRUE)"

or clone within RStudio, Positron or similar and run interactively. You can view the deployed app at: https://chrismainey.shinyapps.io/wl_factor_vs_probability_compliance/

This repository is dual licensed under the Open Government v3 & MIT. All code and outputs are subject to Crown Copyright.