Utilising data for a better understanding of disease
Date
2016
Authors
Agostino, Jason
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
The Australian health system is awash with data. Across our primary and public healthcare systems we are collecting data through administrative systems, medical records, and pathology laboratories, to name just a few. These data have been used by researchers and policy makers, but there remains much to be gained from harnessing new technologies and linking datasets to better inform our understanding of disease. In this thesis, I present four pieces of work on topics that are united through their use of data linkage or new technology. Throughout my four years as a Master of Philosophy in Applied Epidemiology (MAE) scholar I undertook a variety of work in conjunction with four field placement organisations: Apunipima Cape York Health Council, the National Aboriginal Community Controlled Health Organisation, the Hunter New England local hospitals district, and Queensland Health. This thesis presents the results of the applied research from these organisations. My first project is an epidemiological study on early childhood growth in Cape York communities from 1999-2010. By combining routinely collected data on child weights with birth data from the National Perinatal Epidemiology and Statistics Unit we demonstrated a relationship between birth weight and early childhood growth. We also highlighted that while significant improvements have been made in early childhood growth, there remained high rates of low birth weight and prematurity. My second project is an evaluation of the National Key Performance Indicators for Aboriginal and Torres Strait Islander Primary Health Care Services (nKPIs). This collection is the first attempt by the Australian Government to use data extracted from clinical records to monitor the effectiveness of the health system. Our evaluation assessed the quality and usability of the 24 indicators that comprise the nKPIs. While these data have great potential, our evaluation highlighted that they also have important limitations, such as the biases introduced when using these data for population health indicators like smoking status. My third project is a data analysis of Staphylococcus aureus isolates in the Hunter New England region from 2008-2014. This region has established a dataset of patient demographics and hospitalisations that we combined with laboratory data on S. aureus isolates. By combining these data we demonstrated a high proportion of methicillin resistant S. aureus (MRSA) that primarily occurred within young people with no recent exposure to the public healthcare system. This study highlights that control measures for MRSA must move from the hospital into the community setting. My final project is a report on an outbreak investigation of Salmonella Saintpaul that I conducted on behalf of Queensland Health in March 2015. We conducted hypothesis-generating interviews with 23 cases and while our investigation did not reveal a source of the outbreak, analysis with further typing raised the possibility that the increase in reported cases was not in fact an outbreak. This raises the importance of characterisation of Salmonella with genetic tests to identify common strains. My thesis demonstrates the possibilities available through data linkage and molecular characterisation as we move into a new era of public health.
Description
Keywords
Oceanic Ancestory Group, Child health, Infant low birth weight, child nutrition disorders, Indigenous Health Services, health status indicators, Staphylococcus aureus, Methicillin-resistant staphylococcal aureus, Community-acquired infections, Hospital-acquired infections, Salmonella typhimurium
Citation
Collections
Source
Type
Thesis (MPhil)
Book Title
Entity type
Access Statement
License Rights
Restricted until
Downloads
File
Description