Population Health Research Network Research Articles

Evolution of ad hoc and routine data linkage in Australia

Australia has a rich history of utilising linked administrative data for health and human services research. The Population Health Research Network (PHRN), established in 2009, has developed national population-based data linkage capability and infrastructure. Australia-wide, specialist data linkage units have successfully linked their core population health data for over a decade, and within the network over 200 data collections are routinely linked. Data collections are typically classified as either routinely linked or linked on a project-by-project, ad hoc basis. Over time, linkage of data collections that were originally considered ad hoc, for example some longitudinal cohorts and clinical registries, has become ‘routine’. This paper reports on findings of a study that evaluated the volume and proportion of data linkage requests that have been facilitated through the PHRN over the past 5 years that include ad hoc linkage. The paper also reports on the type of data collections that have been linked on an ad hoc basis and details the type of research projects and fields of research currently supported via ad hoc linkage. Quantifying and characterising the type and most sought-after data collections for ad hoc linkage and the breadth of research being undertaken informs future planning and resource allocation for expanding the Australian national linkage capability. This paper explores the integration of ad hoc data linkage within the evolving landscape of expanded master linkage files and national linked data assets, responding to a growing range of data sources and research that could benefit from population-based data linkage.

A discovery platform to improve visibility of linked data across Australia.

BackgroundMetadata plays a crucial role in the health research infrastructure ecosystem. Despite the abundance of metadata for data collections in Australia, there is no simple way for researchers to search for standardised metadata about linked and linkable data collections across sectors or jurisdictions, making it an arduous and time-intensive task. MethodsThe project comprised three phases: an initial scoping exercise to understand the current state of metadata and best practice; a national consultation involving researchers data linkage staff and data custodians to develop a high-fidelity prototype; and a final build and implementation phase. The platform underwent several prototyping and testing cycles to refine the digital experience. ResultsKey expert interviews confirmed that there is a wealth of metadata available in Australia, but it is difficult for researchers to access and evaluate. Consultations with researchers identified opportunities to standardise metadata and provide a centralised platform to enhance the discoverability of linkable data collections for research. High value platform features included searching, browsing and filtering capabilities, variable list metadata, standardised formats, sample data, and frequently asked questions. The final design and functionality reflected user consultations and data custodian input on feasibility and resulted in the standardisation of metadata for linked data collections across sectors and jurisdictions. ConclusionThe Population Health Research Network developed and implemented a metadata platform to enable researchers to assess and evaluate the suitability of data collections for data linkage projects more readily. Improved metadata accessibility will save time and enhance the quality of linked data applications.

Establishment of an Australian National Master Linkage Key (NMLK) between AIHW Health Linkage spine (HLS) and Jurisdictional Master Linkage Keys (MLK) - NSW example

ObjectivesThis paper describes a Population Health Research Network project establishing the NMLK as a national linkage system utilising an enduring linkage between national and jurisdictional linkage spines. It used keys from existing enduring linkages within each participating jurisdictional Data Linkage Unit (DLU). The process is demonstrated with reference to an enduring map between AIHW Health Linkage Spine (HLS) and Centre for Health Record Linkage (CHeReL) MLK. ApproachThe NMLK has jurisdictional sections. The NSW section was established in four steps. CHeReL provided data from its regularly updated MLK for the NMLK project authorised by existing project ethics approval. AIHW linked NSW MLK subset to HLS and the de-identified linkage map and report were sent to CHeReL for review. CHeReL reviewed the results, particularly the additional duplicates identified through the linkage process. The agreed links form the AIHW-NSW section of NMLK quarantined for a year. The annual update, scheduled for later in 2024, will focus only on linking the new and unlinked individuals in both datasets. ResultsThe NSW cohort was supplied with almost 50 million records, comprising over 14 million unique person ids. Of these, 12 million were matched with reasonable confidence to HLS, or 84.4% of the total (or around 97% if we exclude NSW records with missing personal information and around 140,000 individuals out of scope of HLS.) Conclusion Establishment of the NMLK enabled effective production of high-quality enduring linkage maps used across multiple cross-jurisdictional projects while minimising the privacy risks.

CLIMIGRANT: An educational resource about climate change, human movements and health

Abstract Background Climate change in combination with other social, economic, and political factors, can result in population displacement, relocation or migration, which may be forced or may be a voluntary adaptation strategy. For some, however, moving is not an option due to a lack of access to resources, capacity and power. These experiences have implications for health. Our objective was to develop an educational resource to raise awareness about climate change and their impacts on human movement and health. Methods This project was an initiative of the Quebec Population Health Research Network, in Quebec, Canada. A survey was distributed to 28 network members who have diverse expertise, including migration, climate change, environmental sciences, law, ethics, and public health, to identify key themes and messages to convey, and to gather supporting references and materials. A workshop was subsequently held with 10 survey participants to brainstorm ideas for the content, approach and format. A core working group then developed CLIMIGRANT in consultation and collaboration with a number of experts. Results Two illustrated stories (for a general public, including children) and an online course (for students, frontline workers, researchers and other stakeholders) were developed in English and French (available at Climigrant.org). Each provides an overview of how climate induced disasters or environment changes can result in inequitable and complex situations regarding migration/relocation. They also highlight the number of health consequences, both physical and psychological, and challenges related to addressing these. Solutions for prevention and adaptation are presented as well. The resource illustrates how anyone can be affected by climate change, regardless of where they live and conveys a message of solidarity and collective responsibility. Conclusions CLIMIGRANT can be used to inform and educate a broad population on climate change, human movement and health. Key messages • A diversity of methods can be used to raise awareness about climate change, human movements and health. • Anyone, anywhere can be impacted and displaced by climate change and we all have a role to play in addressing climate change and its impacts.

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. As a result, access to linked data from multiple jurisdictions requires complex approval processes. This paper describes Australia’s approach to enabling access to linked data from multiple jurisdictions. It covers the identification of, and agreement to, a minimum set of data items to be included in a unified national application form, the development and implementation of a national online application system and the harmonisation of business processes for cross-jurisdictional research projects. Utilisation of the online application system and the ongoing challenges of data linkage across jurisdictions are discussed. Changes to the data custodian and ethics committee approval criteria were out of scope for this project.

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. As a result, access to linked data from multiple jurisdictions requires complex approval processes. This paper describes Australia's approach to enabling access to linked data from multiple jurisdictions. It covers the identification of, and agreement to, a minimum set of data items to be included in a unified national application form, the development and implementation of a national online application system and the harmonisation of business processes for cross-jurisdictional research projects. Utilisation of the online application system and the ongoing challenges of data linkage across jurisdictions are discussed. Changes to the data custodian and ethics committee approval criteria were out of scope for this project.

A National Approach to The Management of Multi-Jurisdictional Linked Data Projects in Australia

IntroductionThe Population Health Research Network (PHRN) is an Australian data linkage infrastructure capable of securely and safely linking and integrating data collections from a wide range of sources. Australia, as a federated nation, has taken a national approach because:
 
 Australia’s population is mobile and there is significant cross border service use
 Commonwealth, state and territory government agencies collect and store their own data.
 
 The national data linkage infrastructure enables researchers to apply for access to routinely collected and linked administrative data from the Commonwealth, six states and two territories. The application and approvals has been described by researchers as a time-consuming and administratively burdensome process.
 Objectives and ApproachThe primary objective of this project was to improve coordination of the application and approval processes for researchers requesting linked data from multiple jurisdictions in Australia. The approach taken was to develop a single application form/online application system (OAS) and standardise the business processes for multi-jurisdictional research applications.
 ResultsThe PHRN OAS was launched in 2014. All jurisdictions agreed to use the system for multi-jurisdictional linked data projects and SA NT DataLink agreed to use the system for their single-jurisdictional projects.
 Each year since the PHRN OAS’s launch, both the total number of registered users and the number of submissions each year has increased. The majority oforganisations that lodge submissions are universities and medical research institutes.
 There has been a significant reduction in the time taken by data linkage units to issue quotes and the time taken to achieve all approvals for multi-jurisdictional projects since the introduction of the standardised business processes.
 Conclusion / ImplicationsThis paper demonstrates that despite the challenges and complexities associated with applying for linked data from multiple jurisdictions a coordinated application and approval approach can be achieved.

Benchmarking Computational Performance of Virtual Machines Within the Secure Unified Research Environment Versus Physical Computers

IntroductionThe Secure Unified Research Environment (SURE) is a high-powered computing environment located within Sax Institute (Sydney, Australia). SURE was established through the financial support of the Australian Government National Collaborative Research Infrastructure Strategy (NCRIS) as part of the Population Health Research Network (PHRN). SURE is approved by the Australian Government as the only secure platform for analysing unit record level sensitive health and other Australian Government data, providing computational resources and secure infrastructure in a form of virtual machines (VMs) accessible by approved researchers in Australia and overseas.
 Objectives and ApproachWe aim to compare computational performance of SURE VMs of different configurations with the performance of physical computers by running a series of standardised computational tasks involving different numbers of central processingunit (CPU) cores available on each computer. The approach utilised the benchmark test maintained by the H2O.ai group (https://h2oai.github.io/db-benchmark/). The results were measured over the datasets of different sizes, ranging from 500MB to 50GB in Random Access Memory (RAM).
 ResultsOur benchmarking outcomes have revealed that computational efficiency of physical computers uniformly outperform the efficiency of the current standard SURE VM configuration offerings, sometimes demonstrating a nearly double performance. For the range of typical analytical tasks assessed, computational performance greatly benefits from extending the number of computational cores available on a machine.
 Conclusion / ImplicationsSURE is a highly valuable tool enabling research and collaborations involving confidential population-based data. The shortage of RAM and CPU cores can be a major bottleneck even for moderately large datasets. VMs currently offered by SURE yet fall short of reaching computational performance of physical desktop computers. The results are to guide the funders and providers of secure remote access data laboratories responsible for providing Research Infrastructure as a Service (IaaS) tailored to meet the needs of participating research groups.

Tasmanian Data Linkage Unit: Supporting innovative research, planning and policy formulation in Australia through the provision of high-quality linked-data services.

As a member of the Population Health Research Network Australia, being an Australian collaboration established to support the use of linked data for research and other purposes, the Tasmanian Data Linkage Unit [TDLU) provides linked-data services in Australia’s smallest state, and as part of the Menzies Institute for Medical Research at the state’s only University, the University of Tasmania. The TDLU works in close collaboration with the Tasmanian Government Department of Health and other key stakeholders both in Tasmania and Australia representing government, education, research, and the community sector. The TDLU is one of the newest data linkage services in Australia, and the smallest node of the PHRN having operated for almost nine years by less than three full time equivalent staff. However, despite its size and relative maturity as a provider of linked-data services, the TDLU continues to grow the number of datasets linked on a routine and ad-hoc basis, the number of projects completed, the size of its Master Linkage Map and number of ‘keys’ stored in this Map. The TDLU places high-emphasis on security, privacy preservation, innovation, quality assurance, stakeholder engagement and providing responsive and exemplary services to users of linked-data.

The Population Health Research Network - Population Data Centre Profile.

The Population Health Research Network (PHRN) is an Australian data linkage infrastructure capable of securely and safely linking and integrating data collections from a wide range of sources. It is an example of a national data linkage infrastructure in a country with a federated system of government. This population data centre profile describes Australia’s unique approach to enabling access to linked data from single jurisdictions and from multiple jurisdictions. It covers the background to the establishment of the PHRN as well as information about how it operates today including operating models, governance, data, data linkage and data access. Some of the challenges of data linkage across jurisdictions are also discussed.

Health data linkage research in Australia remains challenging.

Data linkage is a valuable technique for uniting information from multiple sources that relates to the same person, place, family or event. Despite its value, establishing such linkages in Australia remains challenging. Existing policies are a missed opportunity for research and innovation and engender a negative attitude among researchers when considering data linkage as a research means. Greater leadership from the Population Health Research Network and cooperation from data custodians and Human Research Ethics Committees are necessary to access optimally Australia's enormous data potential.

The International Population Data Linkage Network – Banff and Beyond

We write to you, here in the pages of the International Journal of Population Data Science, for the second time in our capacity of co-directors of the International Population Data Linkage Network (IPDLN – www.ipdln.org). Time has certainly passed quickly since our first communication, where we introduced ourselves, and discussed planned initiatives for our tenure as leads of the IPDLN. Our network’s scientific community is steadily growing and thriving in an era of heightened interest around all things ‘data’. Indeed, there is great enthusiasm for all initiatives that explore ways of harnessing information systems and multisource data to enhance collective knowledge of health matters so that better decisions can be made by governments, system planners, providers, and patients. Never before have such initiatives attracted more attention.
 It is in this context of heightened interest and relevance around IPDLN and its science that we prepare to convene in Banff, Alberta, Canada for the 5th biennial IPDLN Conference – September 11-14. The conference, to be held at the inspiring Banff Centre (www.banffcentre.ca), is almost sold out, with only limited space remaining for late registrants. A tremendous program has been created through the oversight of Scientific Program co-chairs, Drs. Astrid Guttman and Hude Quan. A compelling roster of plenary lectures from Drs. Diane Watson, Jennifer Walker, and Osmar Zaïane is eagerly anticipated, as are topical panel discussions, an entertaining Science Slam session, and a terrific social program. These sessions will be surrounded by rich scientific oral and poster presentations arising from the more than 450 scientific abstracts submitted for review. We are so pleased to see this vibrant scientific engagement from the IPDLN membership and students, and look forward to hosting all delegates in Banff.
 The Banff conference will also be the venue at which we announce the new Directorship of the IPDLN for the next two years (2019 and 2020). As co-directors, we engaged with a number of individuals and organizations with interest in leading the IPDLN. In the end, two compelling Directorship applications were submitted – one a joint bid from Australia’s Population Health Research Network and the South Australia Northern Territory DataLink, and the other from the US-based Actionable Intelligence for Social Policy. IPDLN members submitted votes on these strong leadership bids through an online voting process, and while the excellence and appeal of both bids was apparent in strong voter support for both, a winning bid has been confirmed, and it will (as mentioned) be announced at the upcoming September conference.
 As we look forward to the Banff meeting with great anticipation, we are compelled to acknowledge the growing IPDLN legacy created by past directors. We are particularly indebted to our immediate predecessor, Dr. David Ford, and his team at Swansea University. Their work in hosting the 2016 IPDLN conference has been an inspiration to us in the planning of this year’s conference, and their crucial and foundational work in creating an IT platform for the IPDLN website, the membership database, and the new International Journal for Population Data Science has brought the IPDLN to a new level of organizational sophistication. Over the last 18 months, our co-directorship teams from the Institute for Clinical Evaluative Sciences in Ontario and the O’Brien Institute for Public Health at the University of Calgary have built on the foundation established by prior directors to update/enhance the IPDLN website and membership database. The IPDLN has more members than ever before representing a greater number of countries, and we have a more formalized governance structure with the creation of an Executive Committee that will include immediate past-Directors in order to better ensure continuity. A new Executive Committee will be elected by the IPDLN membership following the Banff conference.
 The waiting is almost over and IPDLN 2018 is upon us! Our scientific domain has never had the prominence or level of anticipation that we currently see. And the IPDLN has grown in its size, vibrancy and scientific scope. The opportunities for us are boundless, and the timing of our upcoming conference could not be better. We are honoured, with our respective organizations, to have had this opportunity to serve as co-directors over the past two years, and look forward to seeing many of you very soon. For those of you who are unable to travel to Canada’s Rocky Mountains this year, we look forward to connecting with you at a later time in the IPDLN’s continuing upward journey.

Recent trends in the use of linked data in Australia.

Objective The aim of this study was to quantify the use of linked data for health and human services research in Australia since the establishment of the Population Health Research Network (PHRN) in 2009. Methods A systematic literature search was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 checklist to search for all publications involving the use of Australian linked data between 2009-10 and 2016-17. Publications were categorised by subject, data linked and data linkage unit involved. Results In all, 7153 articles were identified from the initial search, and 1208 were included in the final analysis. An increase in the number of publications involving linked data was observed from 2009-10 through to 2015-16. Most articles (82%) featured data linked by at least one PHRN-funded data linkage unit. The research areas of 86% of publications were able to be classified according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision Australian Modification (ICD-10-AM). The number of publications involving cross-sectoral linked data also increased. Conclusions Investment in Australian data linkage infrastructure has seen an increase in the number of research publications involving the use of linked health and human services data. This study identified areas where linked data is commonly used and those where use could be improved. What is known about the topic? Data linkage is a method of bringing together information about individual people, places and events from different sources in a way that protects individual privacy. Individual jurisdictions have reported benefits from research conducted using linked data, including the generation of new knowledge and supporting improvements in the delivery of a wide range of health and human services. There has been significant investment in national data linkage infrastructure in Australia over the past 8 years. To date, there has been no systematic investigation of the effect of this investment on the use of linked population data by the research community. What does this paper add? This paper provides evidence of the increased use of high-quality population-based linked data in research over the 8-year period studied. It demonstrates the application of data linkage across a wide range of health areas and highlights the small but growing number of studies using cross-sectoral data to investigate complex conditions. What are the implications for practitioners? It is important to demonstrate to funders, policy makers, data custodians and researchers the value of robust data linkage capacity as an important national resource. Its use by researchers can bring enormous social and economic benefits by providing a more complete picture of the health and well-being of the community. The range of data collections routinely linked is increasing, as is the pool of researchers experienced in handling and analysing the data. Continued investment in Australia's data linkage infrastructure and the inclusion of other collections including general practice data will augment the use of this infrastructure in expanding the evidence base for policy makers and practitioners.

The impact of the Population Health Research Network on linked data research capacity in Australia

ABSTRACTObjectivesIn 2009 Australian governments and academic institutions made a substantial investment to establish the Population Health Research Network (PHRN), a distributed research infrastructure network which provides Australian researchers with state-of-the-art data linkage facilities and services. The infrastructure operates on a collaborative, national, non-exclusive basis and enables Australian researchers to address key national and global challenges.
 We have conducted a review of the PHRN’s progress over the last 6 years in achieving its objectives of:1. increasing the data linkage research capacity in Australia2. enabling research in national priority areas.
 ApproachProgress with achieving the first objective was measured by comparing the data linkage facilities and services available in Australia in 2008-09 with those available in 2014-15. The following categories of services and facilities were used in the analysis:
 
 Linkage facilities
 Application, access and storage facilities
 Information, training and education
 
 Changes in usage of the data linkage infrastructure over the period 2008-09 to 2014-15 were measured.
 The second objective was achieved by using bibliometrics to assess academic impact, in the form of citations, of peer-reviewed publications which arose from use of the PHRN infrastructure. The topics of all of the publications were compared to health priority areas to determine the extent to which the infrastructure has been used to inform national priorities.
 ResultsThere has been a significant expansion of the data linkage facilities from a small number of jurisdictional data linkage units to a distributed network of data linkage units servicing researchers in every state and territory. A cross-jurisdictional data linkage capability has also been established as well as a national online data application system, a secure remote access laboratory and a secure file transfer system. A variety of information, training and education has been provided to stakeholders. The expansion of the facilities and services has seen usage of data linkage units triple since 2011-12.
 The number of peer-reviewed publications resulting from the use of the PHRN infrastructure has increased every year since 2011-12. There were 111 publications in 2014-15. Areas of high burden of disease in Australia, cancer, cardiovascular and endocrine diseases are highly represented in the publications.
 ConclusionThere has been a significant increase in data linkage research infrastructure in Australia from 2008-09 to 2014-15. This has resulted in an increase in both the number of research projects conducted using linked data and the number of related peer-reviewed publications.

The effect of cross-jurisdictional linked hospital and death data on estimating risk-adjusted grouped hospital standardised mortality ratios in Australia

ABSTRACT
 ObjectivesThe Population Health Research Network (PHRN) was established to increase data linkage capacity in Australia. A proof of concept study investigating cross border hospital use and hospital mortality was undertaken to demonstrate the effectiveness of increased data linkage capacity in supporting nationally significant health research. The objective of this study was to evaluate whether cross-jurisdictional linkage of hospital and death records across Australian states could refine estimation of Hospital Standardised Mortality Ratios (HSMRs).
 ApproachIn Australia, administrative hospital and death data are collected by individual state governments. The newly established Centre for Data Linkage created a cross-jurisdictional linkage key that brought together hospital and death records belonging to individuals across four Australian states over a five year period (1st July 2004 – 30th June 2009). Hospital inpatient records from public, psychiatric and private hospitals and private day surgery centres were provided by New South Wales, Western Australia and Queensland. South Australia provided public hospital inpatient records only. The linked data underwent extensive cleaning and standardisation to improve the validity of interstate comparisons.
 The final cohort comprised 7.7 million hospital patients. In-hospital deaths and deaths within 30 days of hospital discharge from the four state jurisdictions were used to estimate the SMR of hospital groups defined by geography and type of hospital (grouped HSMR) under three record linkage scenarios; 1) cross-jurisdictional person-level linkage, 2) within-jurisdictional (state-based) person-level linkage and 3) unlinked records. All public and private hospitals in New South Wales, Queensland, Western Australia and public hospitals in South Australia were included in this study. Death registrations from all four states were obtained from state-based registries of births, deaths and marriages.
 Results Cross-jurisdictional linkage identified 11,116 cross-border hospital transfers of which 170 resulted in a cross-border in-hospital death. An additional 496 cross-border deaths occurred within 30 day of hospital discharge. The inclusion of cross-jurisdictional person-level links to unlinked hospital records reduced the coefficient of variation amongst the grouped HSMRs from 0.19 to 0.15; the inclusion of 30 day deaths reduced the coefficient of variation further to 0.11. There were minor changes in grouped HSMRs between cross-jurisdictional and within-jurisdictional linkages, although the impact of cross-jurisdictional linkage increased when restricted to geographic regions with high cross-border hospital use such as the New South Wales and Queensland border area.
 ConclusionCross-jurisdictional data linkage modified estimates of grouped HSMRs, particularly for hospitals groups that were likely to receive a high proportion of cross-border users.

Data linkage capabilities in Australia: practical issues identified by a Population Health Research Network ‘Proof of Concept project’

Objective:To describe the practical issues that need to be overcome to conduct national data linkage projects in Australia and propose recommendations to improve efficiency. Methods:Review of the processes, documentation and applications required to conduct national data linkage in Australia. Results:The establishment of state and national data linkage centres in Australia has placed Australia at the forefront of research linking health‐related administrative data collections. However, improvements are needed to reduce the clerical burden on researchers, simplify the process of obtaining ethics approval, improve data accessibility, and thus improve the efficiency of data linkage research. Conclusions:While a sound state and national data linkage infrastructure is in place, the current complexity, duplication and lack of cohesion undermines any attempts to conduct research involving national record linkage in a timely manner. Implications:Data linkage applications and Human Research Ethics Committee approval processes need to be streamlined and duplication removed, in order to reduce the administrative and financial burden on researchers if national data linkage research is to be viable.

Technical challenges of providing record linkage services for research

BackgroundRecord linkage techniques are widely used to enable health researchers to gain event based longitudinal information for entire populations. The task of record linkage is increasingly being undertaken by specialised linkage units (SLUs). In addition to the complexity of undertaking probabilistic record linkage, these units face additional technical challenges in providing record linkage ‘as a service’ for research. The extent of this functionality, and approaches to solving these issues, has had little focus in the record linkage literature. Few, if any, of the record linkage packages or systems currently used by SLUs include the full range of functions required.MethodsThis paper identifies and discusses some of the functions that are required or undertaken by SLUs in the provision of record linkage services. These include managing routine, on-going linkage; storing and handling changing data; handling different linkage scenarios; accommodating ever increasing datasets. Automated linkage processes are one way of ensuring consistency of results and scalability of service.ResultsAlternative solutions to some of these challenges are presented. By maintaining a full history of links, and storing pairwise information, many of the challenges around handling ‘open’ records, and providing automated managed extractions are solved. A number of these solutions were implemented as part of the development of the National Linkage System (NLS) by the Centre for Data Linkage (part of the Population Health Research Network) in Australia.ConclusionsThe demand for, and complexity of, linkage services is growing. This presents as a challenge to SLUs as they seek to service the varying needs of dozens of research projects annually. Linkage units need to be both flexible and scalable to meet this demand. It is hoped the solutions presented here can help mitigate these difficulties.

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.

Can administrative data provide insights into the mental health of Indigenous Queenslanders?

The Australian Government has provided $20 million to establish the Population Health Research Network (PHRN), with representation from all States and Territories to facilitate population health research through data linkage. Health LinQ is part of the Queensland node involving four Queensland universities, Queensland Health and the Australian e-Health Research Centre. This paper reviews the potential for using administrative databases to study the mental health experience of Indigenous Queenslanders. Researchers can define cohorts for study within the administrative data or link them to their own data. Robust protocols preserve confidentiality so that researchers only receive anonymized data. Indigenous status can be defined either through place of residence or through the recording of Indigenous status in datasets such as the Queensland Hospital Admitted Patient Data Collection. Available data include hospital morbidity, mental health data and mortality. Indigenous status is correctly identified in about 89% of cases with variation by definition used. Administrative data provide researchers and decision makers with accessible, cost-effective information without the intrusion and cost of additional data collection. These techniques are especially useful in studying regional, rural and remote populations where access may be difficult.

Privacy and the use of health data for research

We reviewed resources for researchers interested in privacy issues surrounding secondary use of health data for research. These included applicable privacy regulations and available information on privacy perception in Australia. The review is timely because the current Australian Population Health Research Network infrastructure investments are likely to attract new researchers to the field. We used Australian federal, state and territory regulations and programs, polls and surveys, public speeches and academic literature, and some international resources. We identify four themes (de-identification, consent, bias and participation) emerging as areas of concern from the review, and discuss issues relevant to these themes. We provide arguments that excessive privacy regulation has a negative effect on public health research. There is little evidence of privacy complaints or breaches in health research, but significant concerns about consent and de-identification appear to persist in the community. New researchers need to take account of privacy regulation and may wish to take account of privacy perception when designing study and consent processes.