PrAnaViz is a web-browser based R/Shiny tool developed by the Environmental Chemistry and Public Health Group at the University of Bath.

PrAnaViz facilitates users to visualize, explore and report different spatio-temporal and long-term prescription trends of different Active Pharmaceutical Ingredients (APIs) in prescription medications for human use in the UK for wider use. This tool helps to understand the general practice level and postcode level variation of an API. This tool uses the processed dataset generated by the R package, PrAna for the period 2015 to 2018.

PrAna aims to aggregate and normalize England’s national level prescription data, for all groups of drugs. The name is an acronym for Prescription Analysis.

Demo App available in the menu is a prototype tool for demonstration purpose and has the dataset for the years 2015 to 2018 limited to Bath and North East Somerset Clinical Commissioning Group (CCG) region

Citation

Our software and R package paper will be published shortly, until then please cite the preprint

Kishore Kumar Jagadeesan, James Grant, Sue Griffin, Ruth Barden, Barbara Kasprzyk-Hordern, PrAna: An R package to calculate and visualize England NHS primary care prescribing data”, BMC Medical Informatics and Decision Making (under review).

Code and contributions

The code that runs this site is available under the MIT License at https://github.com/PrAnaViz/PrAna. We welcome contributions and issues.

Data sources

Acknowledgments

PrAnaViz and PrAna package were built as a part of the Wastewater Fingerprinting for Public Health Assessment (ENTRUST) project funded by University of Bath, Wessex Water and EPSRC IAA (grant no. EP/R51164X/1).

Feedback

We welcome all feedback, if there are additional features you would like to see added to this site, or you have any feedback, or bug reports, please tell us. If you have access to funding, and would like to collaborate: get in touch

Disclaimer

We accept no liability for any errors in the data or its publication here: use this data at your own risk. You should not use this data to make individual prescribing decisions.