Using the electronic Practice Based Research Network (ePBRN) to prevent re-admission for type-2 diabetes

Project Status
Current

Chief Investigators
Dr Sarah Dennis

Co-investigators and Research Team
Prof. Siaw-Teng Liaw, Ms Jane Taggart, Dr Hairong Yu, Prof Mark F Harris, Prof Bin Jalaludin, Prof Nicholas Zwar, A/Prof Vincent Wong, Ms Jenny Wright, Dr Alan McDougal, A/Prof Gawaine Powell Davies, Mr Rene Pennock

Background

The thirty-day hospital re-admission rate for diabetes in NSW is approximately 21%. Many of these re-admissions could be avoided if care were better integrated between the secondary and primary health services. Up-to-date information and information technology is essential to achieve these goals. Routinely collected electronic health care data, aggregated into large databases, are increasingly being used to predict and prevent hospital admission. The applicants have established an electronic practice based research network (ePBRN) in South Western Sydney and are developing methods to link ePBRN data to hospital admission data to improve integrated chronic disease care between general practice and hospitals.

Aim

To extract, link, analyse and model data from a hospital and surrounding general practices in the Fairfield ePBRN in South West Sydney to predict and prevent re-admission for diabetes.

Method

Extract data on patients with type-2 diabetes admitted to Fairfield Hospital and from the Diabetes Clinic and ten general practices using the GRHANITE software. The records will be matched and a linked dataset created which will be analysed to identify predictors for re-admission. These predictors will be tested in a health service intervention.

This project was funded by HCF