Development and implementation of a national online application system for cross-jurisdictional linked data.

The Population Health Research Network (PHRN) is an Australian national data linkage infrastructure that links a wide range of health and human services data in privacy-preserving ways. The data linkage infrastructure enables researchers to apply for access to routinely collected, linked, administrative data from the six states and two territories which make up the Commonwealth of Australia, as well as data collected by the Australian Government. The PHRN is a distributed network where data is collected and managed at the respective jurisdictional and/or cross-jurisdictional levels.

A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance.

Introduction: Assisted reproductive technologies (ART), such as in-vitro fertilisation (IVF), have revolutionised the treatment of infertility, with an estimated 8 million babies born worldwide. However, the long-term health outcomes for women and their offspring remain an area of concern. Linking IVF treatment data to long-term health data is the most efficient method for assessing such outcomes.

Sharing administrative health data with private industry: A report on two citizens' juries.

Background: There is good evidence of both community support for sharing public sector administrative health data in the public interest and concern about data security, misuse and loss of control over health information, particularly if private sector organizations are the data recipients. To date, there is little research describing the perspectives of informed community members on private sector use of public health data and, particularly, on the conditions under which that use might be justified.

Methods: Two citizens' juries were held in February 2020 in two locations close to Sydney, Australia.

Lumos: a statewide linkage programme in Australia integrating general practice data to guide system redesign.

Objective: With ageing of the Australian population, more people are living longer and experiencing chronic or complex health conditions. The challenge is to have information that supports the integration of services across the continuum of settings and providers, to deliver person-centred, seamless, efficient and effective healthcare. However, in Australia, data are typically siloed within health settings, precluding a comprehensive view of patient journeys.

Quantification of NSW Ambulance Record Linkages with Multiple External Datasets.

This study has two aims: 1) to describe linkage rates between ambulance data and external datasets for "episodes of care" and "patient only" linkages in New South Wales (NSW), Australia; and 2) to detect and report any systematic issues with linkage that relate to patients, and operational or clinical variables that may introduce bias in subsequent studies if not adequately addressed. During 2010-11, the Centre for Health Record Linkage (CHeReL) in NSW, linked the records for patients attended by NSW Ambulance paramedics for the period July 2006 to June 2009, with four external datasets: Emergency Department Data Collection; Admitted Patient Data Collection; NSW Registry of Births, Deaths and Marriages death registration data; and the Australian Bureau of Statistics mortality data. This study reports linkage rates in terms of those "expected" to link and those who were "not expected" to link with external databases within 24 hours of paramedic attendance.

Optimal strategy for linkage of datasets containing a statistical linkage key and datasets with full personal identifiers.

Background: Linkage of aged care and hospitalisation data provides valuable information on patterns of health service utilisation among aged care service recipients. Many aged care datasets in Australia contain a Statistical Linkage Key (SLK-581) instead of full personal identifiers. We linked hospital and death records using a full probabilistic strategy, the SLK-581, and three combined strategies; and compared results for each strategy.

Investigating linkage rates among probabilistically linked birth and hospitalization records.

Background: With the increasing use of probabilistically linked administrative data in health research, it is important to understand whether systematic differences occur between the populations with linked and unlinked records. While probabilistic linkage involves combining records for individuals, population perinatal health research requires a combination of information from both the mother and her infant(s). The aims of this study were to (i) describe probabilistic linkage for perinatal records in New South Wales (NSW) Australia, (ii) determine linkage proportions for these perinatal records, and (iii) assess records with linked mother and infant hospital-birth record, and unlinked records for systematic differences.

Investigating health effects in a community surrounding a road tunnel stack--a cross sectional study.

Background: Extended tunnelled roadways requiring ventilation via exhaust stacks are an increasingly common solution to traffic congestion around the world. In response to community concerns about adverse health effects associated with emissions from a new road tunnel exhaust stack, despite no demonstrable change in local ambient air quality, we conducted a cross sectional study to test for an association between exposure to the exhaust stack emissions and the presence of eye, nose and throat symptoms.

Methods: Stack emissions were modelled and categorised into areas of high, medium and low levels of exposure to emissions.

An epidemiological investigation into an outbreak of rash illness among methadone maintenance clients in Australia.

In late 2004, NSW Health received several reports of a serious desquamating rash among clients of the methadone program. We sought to identify the extent and likely cause of this outbreak. We initiated active surveillance for cases throughout Australia, a survey of dosing points in NSW, and a case control study of clients receiving methadone syrup (MS) at two clinics.