Anna Ferrante

Privacy-preserving record linkage on large real world datasets.

Record linkage typically involves the use of dedicated linkage units who are supplied with personally identifying information to determine individuals from within and across datasets. The personally identifying information supplied to linkage units is separated from clinical information prior to release by data custodians. While this substantially reduces the risk of disclosure of sensitive information, some residual risks still exist and remain a concern for some custodians. In this paper we trial a method of record linkage which reduces privacy risk still further on large real world administrative data. The method uses encrypted personal identifying information (bloom filters) in a probability-based linkage framework. The privacy preserving linkage method was tested on ten years of New South Wales (NSW) and Western Australian (WA) hospital admissions data, comprising in total over 26 million records. No difference in linkage quality was found when the results were compared to traditional probabilistic methods using full unencrypted personal identifiers. This presents as a possible means of reducing privacy risks related to record linkage in population level research studies. It is hoped that through adaptations of this method or similar privacy preserving methods, risks related to information disclosure can be reduced so that the benefits of linked research taking place can be fully realised.

The construction of a road injury database

In order to effectively examine possible causes and determinants of road trauma, reliable information on the participants, circumstances, and resultant injuries and deaths must be available. Characteristics of participants (persons and vehicles) and the circumstances of road accidents are routinely collected by police and road authorities, whereas details of the injuries and medical care provided to casualties are collected by hospital and ambulance services. A road injury database, linking data collected by the Health, Police, and Main Roads Departments of the Government of Western Australia with records of the St. John Ambulance Association and the Death Register, has been established. This paper describes the procedures used to link the various sources of data and discusses the design, construction, and quality of the resultant relational database.

Data linkage infrastructure for cross-jurisdictional health-related research in Australia

BackgroundThe Centre for Data Linkage (CDL) has been established to enable national and cross-jurisdictional health-related research in Australia. It has been funded through the Population Health Research Network (PHRN), a national initiative established under the National Collaborative Research Infrastructure Strategy (NCRIS). This paper describes the development of the processes and methodology required to create cross-jurisdictional research infrastructure and enable aggregation of State and Territory linkages into a single linkage “map”.MethodsThe CDL has implemented a linkage model which incorporates best practice in data linkage and adheres to data integration principles set down by the Australian Government. Working closely with data custodians and State-based data linkage facilities, the CDL has designed and implemented a linkage system to enable research at national or cross-jurisdictional level. A secure operational environment has also been established with strong governance arrangements to maximise privacy and the confidentiality of data.ResultsThe development and implementation of a cross-jurisdictional linkage model overcomes a number of challenges associated with the federated nature of health data collections in Australia. The infrastructure expands Australia’s data linkage capability and provides opportunities for population-level research. The CDL linkage model, infrastructure architecture and governance arrangements are presented. The quality and capability of the new infrastructure is demonstrated through the conduct of data linkage for the first PHRN Proof of Concept Collaboration project, where more than 25 million records were successfully linked to a very high quality.ConclusionsThis infrastructure provides researchers and policy-makers with the ability to undertake linkage-based research that extends across jurisdictional boundaries. It represents an advance in Australia’s national data linkage capabilities and sets the scene for stronger government-research collaboration.

The effect of data cleaning on record linkage quality

BackgroundWithin the field of record linkage, numerous data cleaning and standardisation techniques are employed to ensure the highest quality of links. While these facilities are common in record linkage software packages and are regularly deployed across record linkage units, little work has been published demonstrating the impact of data cleaning on linkage quality.MethodsA range of cleaning techniques was applied to both a synthetically generated dataset and a large administrative dataset previously linked to a high standard. The effect of these changes on linkage quality was investigated using pairwise F-measure to determine quality.ResultsData cleaning made little difference to the overall linkage quality, with heavy cleaning leading to a decrease in quality. Further examination showed that decreases in linkage quality were due to cleaning techniques typically reducing the variability – although correct records were now more likely to match, incorrect records were also more likely to match, and these incorrect matches outweighed the correct matches, reducing quality overall.ConclusionsData cleaning techniques have minimal effect on linkage quality. Care should be taken during the data cleaning process.

Novice drink drivers, recidivism and crash involvement.

A group of drink drivers with no prior arrest for drink driving was selected from drink driving arrest records originating in Western Australia between 1987 and 1995. These drink-driving records were linked to road crash records for the same period. The analysis of these combined records focussed on the sequence of driving events (i.e., arrests, crashes and arrests resulting from crashes) and the present article explores the relationship in time between known drink driving incidents and crash involvement. Using multi-variate survival analysis, it was found that if a drivers first drink driving offence resulted from a road crash, especially if this occurred at a younger age, he/she was significantly more likely to drink, drive and crash again.

Dope busts in the West: minor cannabis offences in the Western Australian criminal justice system.

Proponents of cannabis law reform argue that many people who are convicted for minor cannabis offences have no prior criminal conviction and are otherwise law-abiding citizens. This study of criminal justice system data in a strict prohibition jurisdiction (Western Australia) found that over 10% of all charges and 85% of all drug charges were for cannabis. Approximately 90% of these were for minor offences. Over 40% of those charged with cannabis possession/use as their most serious offence had never been arrested for any prior offence. Almost half of those first arrested for cannabis possession/use had not been arrested up to 10 years later. Younger first-time arrested cannabis users were more likely to be re-arrested than older offenders. Almost all adult cannabis offenders who went to court were convicted and fined. Nearly 95% of those imprisoned for possession/use of cannabis were gaoled for fine default. The findings accord with earlier research showing that the vast majority of these offenders are, in all respects apart from their cannabis use, a non-criminal section of the community.

Developing an offender-based tracking system: the Western Australia INOIS Project

In 1989 the Crime Research Centre (University of Western Australia) and criminal justice agencies in Western Australia became involved in the INOIS (Integrated Numerical Offender Identification System) project. The principal aim of this project was to introduce a common, unique identifier for offenders so that a longitudinal database could be established that could “track” offenders through the criminal justice system. This paper explains reasons for establishing this kind of database and explores some of the conceptual and technical issues which arise. Central to the development of the database and, therefore, to the INOIS project, was the underlying need to uniquely identify each offender. This paper focuses on how record-linking techniques were used to achieve this. The record-linking component of the INOIS project is discussed at length, and results from trials and from preliminary runs of the linkage system are presented and discussed. Additional research and operational usages of such a system are also identified.

Cross-border hospital use: analysis using data linkage across four Australian states

Objective: To determine the quality and effectiveness of national data linkage capacity by performing a proof‐of‐concept project investigating cross‐border hospital use and hospital‐related deaths.

A linkage study of Western Australian drink driving arrests and road crash records

Records of drivers in all reported road crashes occurring in Western Australia between 1987 and 1995 were linked with records of all drink driving arrests in the same period. About 7% of all drink driving arrests occurred because of a road crash. Differences were observed between these drink-driving crashes and other types of road crashes. Drink driving crashes tended to be more severe than those not involving alcohol. Serious crashes (involving fatalities or hospitalisations) accounted for 20% of alcohol-related crashes, but only 6% of all crashes reported over the study period. From another perspective, crash-related drink-driving arrests were more likely than routine enforcement arrests to involve younger (18-35 years) and older (65 years and over) drink drivers. Routine enforcement arrests, on the other hand, were likely to involve a greater proportion of Aboriginal drivers.

Assessing the Influence of "Standard" and "Culturally Specific" Risk Factors on the Prevalence and Frequency of Offending: The Case of Indigenous Australians.

This is an empirical study which uses a multifactorial risk framework to investigate the factors that influence the prevalence and frequency of offending by indigenous Australians (as measured through self-reported arrest rates). The study uses regression modeling of data from the 2002 National Aboriginal and Torres Strait Islander Social Survey to estimate the effects of a range of individual, family, and community factors on indigenous arrest rates. The study considers a range of explanatory factors and includes both “standard” and “culturally specific” influences. Drawing upon the works of Homel, Lynch, and Herd, Broadhurst, and other Australian researchers, the study investigates the influence of multiple risk factors (including factors such as cultural strength and connection to community) and assesses whether these play a part in explaining the interaction between the indigenous population and the Australian criminal justice system.