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

## Background

During the last decade, wide range of active pharmaceutical ingredients (APIs) have been identified and quantified in aquatic environment across several studies and indicated their impacts on exposed environmental species and humans. For the prediction of total amount of the APIs released to the environment, information about APIs consumption data is vital. Globally, several methods were reported to estimate the APIs consumption data based on the national prescription data, manufacturers, importers and dispenser’s data.

In the UK, national prescription data provided by National Health Service was used to calculate the consumption data. This data is freely accessible and consist of individual files for each month. With the large file with over 10 million records every month, the data from the NHS cannot be used for the direct calculation of the prescription levels of different APIs. Re-organisation and processing of the files is required before to do any exploration or analysis and to speed up the data reading.

The aim of PrAna is to aggregate and normalize prescription data to calculate total prescribed quantity of different APIs, using open source statistical software [R language][@R-base].

Apart, from the calculation of the total prescribed quantity of an API or a group of APIs, specified to a postcode or region, We have also developed, an open interactive web-based tool, PrAnaViz with the processed dataset for the period 2015 to 2018.

PrAnaViz facilitates users to visualise, explore and report different spatiotemporal and long-term prescription trends for wider use.

## Workflow

Below is an overview of the workflow:

• Data Preparation: Download monthly NHS prescription datasets and Dictionary of medicines and devices release files (dm+d).
• Data Conversion: Aggregation and conversion of the locally stored datasets into practice wise dataset achieved using the functions in PrAna.
• Visualise and Analyse the data: Visualise and analyse the processed dataset using the in-built ShinyApp PrAnaViz.
• Database service: Linking of the processed dataset to the PrAnaViz can be achieved by uploading the processed dataset to a local or a remote database service, for example, MySQL.
• Download images and processed data: Users can download processed data as .csv file and publication ready image .eps and .pdf files.

## Get this package

PrAna can be installed as any other R package, as follows,

To install the development version of PrAna from GitHub:

install.packages("devtools")
library(devtools)
install_github("jkkishore85/PrAna")

However, since it is dependent on some other software tools some extra steps are required for the installation. Please see the installation section in the handbook for more information.

However, for a better guide to get started it is recommended to read the tutorial.

## Acknowledgements

This package was 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).

## 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.