The National Antimicrobial Prescribing Survey

Project Details

The aim of this project is to utilise the Patron dataset to apply data science methodologies to enable the automation aspects of antimicrobial guideline compliance and appropriateness antibiotic assessment. This dataset will enable the research team to develop algorithms to determine compliance with Therapeutic Guidelines (the national standard) and appropriateness assessments, using natural language processing and machine learning technologies.

Patron ID: PAT061

Project Lead:

Dr Ruby Biezen

This project will apply and utilise novel data science methodologies such as machine learning and natural language processing to transform clinical and prescribing data. It will also automate the assessment of prescription quality and appropriateness, which will drive surveillance and stewardship programs using a Learning Health System.

This MRFF grant will bring together different healthcare components of projects (general practice, hospital and veterinary practice) to establish a data research platform that will enable a pipeline for future coordinated antimicrobial surveillance and reporting across Australia.

We will be applying machine learning techniques to automate the assessment of appropriateness of prescriptions in the Patron dataset.

The Patron Data will be used for the first phase of the general practice component only.