Growth of linked hospital data use in Australia: a systematic review

Trajectories of homelessness and association with mental health and substance use disorders among young people transitioning from out-of-home care in Australia

BACKGROUND

Researchers have examined sub-groups that may exist among young people transitioning from out-of-home care (OHC) using various theoretical models. However, this population group has not been examined for trajectories of homelessness risk.

OBJECTIVES

To examine whether different subtypes of homelessness risk exist among young people transitioning from care and whether these trajectories of homelessness are associated with mental health and substance use disorders.

PARTICIPANTS AND SETTING

A retrospective population-based cohort study was conducted from a population of 1018 young people (aged 15-18 years) who transitioned from out-of-home in 2013 to 2014 in the state of Victoria, Australia, with follow-up to 2018.

METHODS

Latent Class Growth Analysis was conducted using linked data from homelessness data collections, child protection, mental health information systems, alcohol and drug use, and youth justice information systems.

RESULTS

Three sub-groups of young people were identified. The 'moving on' group (88 %) had the lowest levels of homelessness, with the slope of this trajectory remaining almost stable. The 'survivors' (7 %) group started off with a high risk of homelessness, followed by a sharp decrease in homelessness risk over time. The 'complex' (5 %) group started off with a low risk of homelessness but faced sharp increases in the risk of homelessness over time.

CONCLUSIONS

Our study demonstrates that subgroups of young people transitioning from care exist with distinct longitudinal trajectories of homelessness, and these classes are associated with different risk factors. Early intervention and different approaches to tackling homelessness should be considered for these three distinct groups before transitioning from care and during the first few years after leaving care.

The use of linked administrative data in Australian randomised controlled trials: A scoping review

BACKGROUND/AIMS

The demand for simplified data collection within trials to increase efficiency and reduce costs has led to broader interest in repurposing routinely collected administrative data for use in clinical trials research. The aim of this scoping review is to describe how and why administrative data have been used in Australian randomised controlled trial conduct and analyses, specifically the advantages and limitations of their use as well as barriers and enablers to accessing administrative data for use alongside randomised controlled trials.

METHODS

Databases were searched to November 2022. Randomised controlled trials were included if they accessed one or more Australian administrative data sets, where some or all trial participants were enrolled in Australia, and where the article was published between January 2000 and November 2022. Titles and abstracts were independently screened by two reviewers, and the full texts of selected studies were assessed against the eligibility criteria by two independent reviewers. Data were extracted from included articles by two reviewers using a data extraction tool.

RESULTS

Forty-one articles from 36 randomised controlled trials were included. Trial characteristics, including the sample size, disease area, population, and intervention, were varied; however, randomised controlled trials most commonly linked to government reimbursed claims data sets, hospital admissions data sets and birth/death registries, and the most common reason for linkage was to ascertain disease outcomes or survival status, and to track health service use. The majority of randomised controlled trials were able to achieve linkage in over 90% of trial participants; however, consent and participant withdrawals were common limitations to participant linkage. Reported advantages were the reliability and accuracy of the data, the ease of long term follow-up, and the use of established data linkage units. Common reported limitations were locating participants who had moved outside the jurisdictional area, missing data where consent was not provided, and unavailability of certain healthcare data.

CONCLUSIONS

As linked administrative data are not intended for research purposes, detailed knowledge of the data sets is required by researchers, and the time delay in receiving the data is viewed as a barrier to its use. The lack of access to primary care data sets is viewed as a barrier to administrative data use; however, work to expand the number of healthcare data sets that can be linked has made it easier for researchers to access and use these data, which may have implications on how randomised controlled trials will be run in future.

The knowledge and reuse practices of researchers utilising government health information assets, Victoria, Australia, 2008-2020

BACKGROUND

Using government health datasets for secondary purposes is widespread; however, little is known on researchers' knowledge and reuse practices within Australia.

OBJECTIVES

To explore researchers' knowledge and experience of governance processes, and their data reuse practices, when using Victorian government health datasets for research between 2008-2020.

METHOD

A cross-sectional quantitative survey was conducted with authors who utilised selected Victorian, Australia, government health datasets for peer-reviewed research published between 2008-2020. Information was collected on researchers': data reuse practices; knowledge of government health information assets; perceptions of data trustworthiness for reuse; and demographic characteristics.

RESULTS

When researchers used government health datasets, 45% linked their data, 45% found the data access process easy and 27% found it difficult. Government-curated datasets were significantly more difficult to access compared to other-agency curated datasets (p = 0.009). Many respondents received their data in less than six months (58%), in aggregated or de-identified form (76%). Most reported performing their own data validation checks (70%). To assist in data reuse, almost 71% of researchers utilised (or created) contextual documentation, 69% a data dictionary, and 62% limitations documentation. Almost 20% of respondents were not aware if data quality information existed for the dataset they had accessed. Researchers reported data was managed by custodians with rigorous confidentiality/privacy processes (94%) and good data quality processes (76%), yet half lacked knowledge of what these processes entailed. Many respondents (78%) were unaware if dataset owners had obtained consent from the dataset subjects for research applications of the data.

CONCLUSION

Confidentiality/privacy processes and quality control activities undertaken by data custodians were well-regarded. Many respondents included data linkage to additional government datasets in their research. Ease of data access was variable. Some documentation types were well provided and used, but improvement is required for the provision of data quality statements and limitations documentation. Provision of information on participants' informed consent in a dataset is required.

The burdensome logistics of data linkage in Australia - the example of a national registry for congenital heart disease

Objective Data linkage is a very powerful research tool in epidemiology, however, establishing this can be a lengthy and intensive process. This paper reports on the complex landscape of conducting data linkage projects in Australia. Methods We reviewed the processes, required documentation, and applications required to conduct multi-jurisdictional data linkage across Australia, in 2023. Results Obtaining the necessary approvals to conduct linkage will likely take nearly 2 years (estimated 730 days, including 605 days from initial submission to obtaining all ethical approvals and an estimated further 125 days for the issuance of unexpected additionally required approvals). Ethical review for linkage projects ranged from 51 to 128 days from submission to ethical approval, and applications consisted of 9-25 documents. Conclusions Major obstacles to conducting multi-jurisdictional data linkage included the complexity of the process, and substantial time and financial costs. The process was characterised by inefficiencies at several levels, reduplication, and a lack of any key accountabilities for timely performance of processes. Data linkage is an invaluable resource for epidemiological research. Further streamlining, establishing accountability, and greater collaboration between jurisdictions is needed to ensure data linkage is both accessible and feasible to researchers.

Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium

In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.

Why and how we can use data linkage in oral health research: a narrative review

OBJECTIVES

Poor oral health, impacting health and wellbeing across the life-course, is a costly and wicked problem. Data (or record) linkage is the linking of different sets of data (often administrative data gathered for non-research purposes) that are matched to an individual and may include records such as medical data, housing information and sociodemographic information. It often uses population-level data or 'big data'. Data linkage provides the opportunity to analyse complex associations from different sources for total populations. The aim of the paper is to explore data linkage, how it is important for oral health research and what promise it holds for the future.

METHODS

This is a narrative review of an approach (data linkage) in oral health research.

RESULTS

Data linkage may be a powerful method for bringing together various population datasets. It has been used to explore a wide variety of topics with many varied datasets. It has substantial current and potential application in oral health research.

CONCLUSIONS

Use of population data linkage is increasing in oral health research where the approach has been very useful in exploring the complexity of oral health. It offers promise for exploring many new areas in the field.

Improving Cohort-Hospital Matching Accuracy through Standardization and Validation of Participant Identifiable Information

Linking very large, consented birth cohorts to birthing hospitals clinical data could elucidate the lifecourse outcomes of health care and exposures during the pregnancy, birth and newborn periods. Unfortunately, cohort personally identifiable information (PII) often does not include unique identifier numbers, presenting matching challenges. To develop optimized cohort matching to birthing hospital clinical records, this pilot drew on a one-year (December 2020-December 2021) cohort for a single Australian birthing hospital participating in the whole-of-state Generation Victoria (GenV) study. For 1819 consented mother-baby pairs and 58 additional babies (whose mothers were not themselves participating), we tested the accuracy and effort of various approaches to matching. We selected demographic variables drawn from names, DOB, sex, telephone, address (and birth order for multiple births). After variable standardization and validation, accuracy rose from 10% to 99% using a deterministic-rule-based approach in 10 steps. Using cohort-specific modifications of the Australian Statistical Linkage Key (SLK-581), it took only 3 steps to reach 97% (SLK-5881) and 98% (SLK-5881.1) accuracy. We conclude that our SLK-5881 process could safely and efficiently achieve high accuracy at the population level for future birth cohort-birth hospital matching in the absence of unique identifier numbers.

Mastering Linked Datasets: The Future of Emergency Health Care Research

Objectives: The aim of this work is to describe routine integration of prehospital emergency health records into a health master linkage file, delivering ongoing access to integrated patient treatment and outcome information for ambulance-attended patients in Queensland.Methods: The Queensland Ambulance Service (QAS) data are integrated monthly into the Queensland Health Master Linkage File (MLF) using a linkage algorithm that relies on probabilistic matches in combination with deterministic rules based on patient demographic details, date, time and facility identifiers. Each ambulance record is assigned an enduring linkage key (unique patient identifier) and further processing determines whether each record matches with a corresponding hospital emergency department, admission or death registry record. In this study, all QAS electronic ambulance report form (eARF) records from October 2016 to December 2018 where at least 1 key linkage variable was present (n = 1,771,734) were integrated into the MLF.Results: The majority of records (n = 1,456,502; 82.2%) were for transported patients, and 90.1% (n = 1,312,176) of these transports were to public hospital facilities. Of these transport records, 93.9% (n = 1,231,951) matched to emergency department (ED) records and 59.3% (n = 864,394) also linked to admitted patient records. Of ambulance non-transport records integrated into the MLF, 23.6% (n = 74,311) matched with ED records.Conclusion: This study demonstrates robust linkage methods, quality assurance processes and high linkage rates of data across the continuum of care (prehospital/emergency department/admitted patient/death) in Queensland. The resulting infrastructure provides a high-quality linked dataset that facilitates complex research and analysis to inform critical functions such as quality improvement, system evaluation and design.

A Comprehensive Systematic Review of Data Linkage Publications on Diabetes in Australia

Aims

Our study aimed to identify the common themes, knowledge gaps and to evaluate the quality of data linkage research on diabetes in Australia.

Methods

This systematic review was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (the PRISMA Statement). Six biomedical databases and the Australian Population Health Research Network (PHRN) website were searched. A narrative synthesis was conducted to comprehensively identify the common themes and knowledge gaps. The guidelines for studies involving data linkage were used to appraise methodological quality of included studies.

Results

After screening and hand-searching, 118 studies were included in the final analysis. Data linkage publications confirmed negative health outcomes in people with diabetes, reported risk factors for diabetes and its complications, and found an inverse association between primary care use and hospitalization. Linked data were used to validate data sources and diabetes instruments. There were limited publications investigating healthcare expenditure and adverse drug reactions (ADRs) in people with diabetes. Regarding methodological assessment, important information about the linkage performed was under-reported in included studies.

Conclusions

In the future, more up to date data linkage research addressing costs of diabetes and its complications in a contemporary Australian setting, as well as research assessing ADRs of recently approved antidiabetic medications, are required.

Challenges and opportunities for using population health data to investigate cancer survivors' quality of life in Australia

There is a recognised need for reported national data that inform health policy, health professions, and consumers about the wellbeing of Australians with cancer and other chronic conditions. International initiatives have demonstrated the viability and benefits of utilising population-based cancer registries to monitor the prevalence and trajectory of health-related quality of life (HRQOL) outcomes among people with cancer. Establishing a similar level of monitoring in Australia would require timely access to health data collected by publicly funded, population-based cancer registries, and the capacity to link this information across jurisdictions. Combining information from different sources via data linkage is an efficient and cost-effective way to maximise how data are used to inform population health and policy development. However, linking health datasets has historically been highly restricted, resource-intensive, and costly in Australia due to complex and outdated legislative requirements, duplicative approval processes, and differing policy frameworks in each state and territory. This has resulted in significant research waste due to underutilisation of existing data, duplication of research efforts and resources, and data not being translated into decision-making. Recognising these challenges, from 2015 to 2017 the Productivity Commission investigated options for improving data availability and use in Australia, considering factors such as privacy, security, and intellectual property. The inquiry report recommended significant reforms for Australian legislation, including the creation of a data sharing and release structure to improve access to data for research and policy development purposes. This paper discusses (1) opportunities in HRQOL research enabled by data linkage, (2) barriers to data access and use in Australia and the implications for waste in HRQOL research, and (3) proposed legislative reforms for improving data availability and use in Australia.

Cost, profile, and postoperative resource use for surgically managed acute hand and wrist injuries with emergency department presentation

STUDY DESIGN

Retrospective cost-of-illness study.

INTRODUCTION

Injuries to the hand and wrist are common. Most uncomplicated and stable upper extremity injuries recover with conservative management; however, some require surgical intervention. The economic burden on the health care system from such injuries can be considerable.

PURPOSE OF THE STUDY

To estimate the economic implications of surgically managed acute hand and wrist injuries at one urban health care network.

METHODS

Using 33 primary diagnosis ICD-10 codes involving the hand and wrist, 453 consecutive patients from 2014 to 2015 electronic billing records who attended the study setting emergency department and received consequent surgical intervention and outpatient follow-up were identified. Electronic medical records were reviewed to extract demographic data. Costs were calculated from resource use in the emergency department, inpatient, and outpatient settings. Results are presented by demographics, injury type, mechanism of injury, and patient pathway.

RESULTS

Two hundred and twenty-six individuals (n 1⁄4 264 surgeries) were included. The total cost of all injuries was $1,204,606. The median cost per injury for non-compensable cases (n = 191) was $4508 [IQR $3993-$6172] and $5057 [IQR $3957-$6730] for compensable cases (n = 35). The median number of postoperative appointments with a surgeon was 2.00 (IQR 1.00-3.00) for both compensable and non-compensable cases. The number of hand therapy appointments for non-compensable cases and compensable cases was 4 [IQR 2-6] and 2 [IQR 1-3], respectively.

DISCUSSION

Findings of this investigation highlight opportunities for health promotion strategies for reducing avoidable injuries and present considerations for reducing cost burden by addressing high fail to attend (FTA) appointment rates.

CONCLUSION

Surgically managed hand and wrist injuries contribute to a significant financial burden on the health care system. Further research using stringent data collection methods are required to establish epidemiological data and national estimates of cost burden.

Measuring the economic impact of hospital-acquired complications on an acute health service

Objective This study determined the economic impact of 16 'high-priority' hospital-acquired complications (HACs), as defined by the Australian Commission on Safety and Quality in Health Care, from the perspective of an individual Australian health service. Methods A retrospective cohort study was performed using a deidentified patient dataset containing 93056 in-patient separations in Northern Health (Victoria, Australia) from 1 July 2016 to 30 June 2017. Two log-linked generalised linear regression models were used to obtain additional costs and additional length of stay (LOS) for 16 different HACs, with the main outcome measures being the additional cost and LOS for all 16 HACs. Results In all, 1700 separations involving HACs (1.83%) were identified. The most common HAC was health care-associated infections. Most HACs were associated with a statistically significant risk of increased cost (15/16 HACs) and LOS (11/16 HACs). HACs involving falls resulting in fracture or other intracranial injury were associated with the highest additional cost (A$17173). The biggest increase in additional LOS was unplanned admissions to the intensive care unit (5.42 days). Conclusions This study shows the economic impact of HACs from the perspective of an individual health service. The methodology used demonstrates how other health services could determine safety priorities corresponding to their own casemix. What is known about the topic? HACs are a major issue in Australian health care; however, their effect on cost and LOS at the individual health service level is not well quantified. What does this paper add? Additional cost and LOS implications for 16 high-priority HACs have been quantified within an Australian health service. There is substantial variation in terms of the number of HACs and the economic impact of each HAC. What are the implications for practitioners? This study provides a template for other health services to assess the economic impact of HACs corresponding to their own casemix and to inform targeted patient safety programs.

Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review

INTRODUCTION

Over the past decade there has been a marked growth in the use of linked population administrative data for child protection research. This is the first systematic review of studies to report on research design and statistical methods used where population-based administrative data is integrated with longitudinal data in child protection settings.

METHODS

The systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. The electronic databases Medline (Ovid), PsycINFO, Embase, ERIC, and CINAHL were systematically searched in November 2019 to identify all the relevant studies. The protocol for this review was registered and published with Open Science Framework (Registration DOI: 10.17605/OSF.IO/96PX8).

RESULTS

The review identified 30 studies reporting on child maltreatment, mental health, drug and alcohol abuse and education. The quality of almost all studies was strong, however the studies rated poorly on the reporting of data linkage methods. The statistical analysis methods described failed to take into account mediating factors which may have an indirect effect on the outcomes of interest and there was lack of utilisation of multi-level analysis.

CONCLUSION

We recommend reporting of data linkage processes through following recommended and standardised data linkage processes, which can be achieved through greater co-ordination among data providers and researchers.

Investigating inequities in cardiovascular care and outcomes for Queensland Aboriginal and Torres Strait Islander people: protocol for a hospital-based retrospective cohort data linkage project

INTRODUCTION

Cardiovascular disease (CVD) represents a significant burden of disease for Aboriginal and Torres Strait Islander people, a population that continues to experience a lower life expectancy than other Australians. The aim of the Better Cardiac Care Data Linkage project is to describe patient care pathways and to identify disparities in care and health outcomes between Aboriginal and Torres Strait Islander people and other Queensland residents diagnosed with CVD in the state of Queensland.

METHODS

This is a population-based retrospective cohort study using linked regional, state and national health and administrative data collections to describe disparities in CVD healthcare in primary and secondary prevention settings and during hospitalisation. The CVD cohort will be identified from the Queensland Hospital Admitted Patient Data Collection for admissions that occurred between 1 July 2010 and 31 June 2016 and will include relevant International Classification of Disease codes for ischaemic heart disease, congestive heart failure, stroke, acute rheumatic fever and rheumatic heart disease. Person-level data will be linked by Data Linkage Queensland and the Australian Institute of Health and Welfare (AIHW) in accordance with ethical and public health approvals to describe the patient journey prior to, during and post the hospital admission.

ANALYSIS

This project will focus largely on descriptive epidemiological measures and multivariate analysis of clinical care standards and outcomes for Aboriginal and Torres Strait Islander people compared with other Queenslanders, including identification of risk factors for suboptimal care and change over time. Variation in care pathways and patient outcomes will be compared by Indigenous status, sex, age group, remoteness of residence, year of index hospitalisation and socioeconomic status. Cox models for time-to-event data and mixed models or generalised estimating equations for longitudinal data will be used to measure change over time where temporal effects exist.

ETHICS AND DISSEMINATION

Ethical approval has been granted by Human Research Ethics Committees of the Prince Charles Hospital (HREC/15/QPCH/289) and the AIHW (EO2016-1-233). The Northern Territory Department of Health and Menzies School of Health Research have also provided reciprocal ethical approval of the project (HREC 2019-3490). The deidentified results will be summarised in a report and shared with investigators, advisory groups, Queensland Health and key stakeholders. Findings will be disseminated through workshops, conferences and will be published in peer-reviewed journals.

Patient-specific record linkage between emergency department and hospital admission data for a cohort of people who inject drugs: methodological considerations for frequent presenters

Background

People who inject drugs (PWID) have been identified as frequent users of emergency department (ED) and hospital inpatient services. The specific challenges of record linkage in cohorts with numerous administrative health records occurring in close proximity are not well understood. Here, we present a method for patient-specific record linkage of ED and hospital admission data for a cohort of PWID.

Methods

Data from 688 PWID were linked to two state-wide administrative health databases identifying all ED visits and hospital admissions for the cohort between January 2008 and June 2013. We linked patient-specific ED and hospital admissions data, using administrative date-time timestamps and pre-specified linkage criteria, to identify hospital admissions stemming from ED presentations for a given individual. The ability of standalone databases to identify linked ED visits or hospital admissions was examined.

Results

There were 3459 ED visits and 1877 hospital admissions identified during the study period. Thirty-four percent of ED visits were linked to hospital admissions. Most links had hospital admission timestamps in-between or identical to their ED visit timestamps (n = 1035, 87%). Allowing 24-h between ED visits and hospital admissions captured more linked records, but increased manual inspection requirements. In linked records (n = 1190), the ED ‘departure status’ variable correctly reflected subsequent hospital admission in only 68% of cases. The hospital ‘admission type’ variable was non-specific in identifying if a preceding ED visit had occurred.

Conclusions

Linking ED visits with subsequent hospital admissions in PWID requires access to date and time variables for accurate temporal sorting, especially for same-day presentations. Selecting time-windows to capture linked records requires discretion. Researchers risk under-ascertainment of hospital admissions if using ED data alone.

Linking administrative data sets of inpatient infectious diseases diagnoses in far North Queensland: a cohort profile

PURPOSE

To design a linked hospital database using administrative and clinical information to describe associations that predict infectious diseases outcomes, including long-term mortality.

PARTICIPANTS

A retrospective cohort of Townsville Hospital inpatients discharged with an International Classification of Diseases and Related Health Problems 10th Revision Australian Modification code for an infectious disease between 1 January 2006 and 31 December 2016 was assembled. This used linked anonymised data from: hospital administrative sources, diagnostic pathology, pharmacy dispensing, public health and the National Death Registry. A Created Study ID was used as the central identifier to provide associations between the cohort patients and the subsets of granular data which were processed into a relational database. A web-based interface was constructed to allow data extraction and evaluation to be performed using editable Structured Query Language.

FINDINGS TO DATE

The database has linked information on 41 367 patients with 378 487 admissions and 1 869 239 diagnostic/procedure codes. Scripts used to create the database contents generated over 24 000 000 database rows from the supplied data. Nearly 15% of the cohort was identified as Aboriginal or Torres Strait Islanders. Invasive staphylococcal, pneumococcal and Group A streptococcal infections and influenza were common in this cohort. The most common comorbidities were smoking (43.95%), diabetes (24.73%), chronic renal disease (17.93%), cancer (16.45%) and chronic pulmonary disease (12.42%). Mortality over the 11-year period was 20%.

FUTURE PLANS

This complex relational database reutilising hospital information describes a cohort from a single tropical Australian hospital of inpatients with infectious diseases. In future analyses, we plan to explore analyses of risks, clinical outcomes, healthcare costs and antimicrobial side effects in site and organism specific infections.

Population Data Centre Profile - The Western Australian Data Linkage Branch

Established in 1995, the Western Australian Data Linkage Branch (DLB) is Australia's longest running data linkage agency. The Western Australian Data Linkage System (WADLS) employs an enduring linkage model spanning over 60 data collections supported by internally developed and supported software and IT infrastructure. DLB has delivered, and continues to deliver, a range of significant data linkage innovations, many of which have been adopted elsewhere. A current restructure within the Western Australian Department of Health (which we will refer to as the Department of Health) will provide an improved funding model geared toward addressing issues with staff retention, capacity and customer service, as well as fostering improvements to data management, governance and availability. Research using linked data provided by DLB has been used in over 800 projects resulting in over 2350 publications and outcomes for policy development, service delivery and public health. Demand continues to grow for data linkage services and with the Department of Health's bolstered commitment to resourcing, DLB looks forward to a future for data linkage in Western Australia that is sustainable, high quality, efficient, and safe.

Using general practice clinical information system data for research: the case in Australia

General practice is often a patient’s first point of contact with the health system and the gateway to specialist services. In Australia, different aspects of the health system are managed by the Commonwealth Government and individual state / territory governments. Although there is a long history of research using administrative data in Australia, this split in the management and funding of services has hindered whole-system research. Additionally, the administrative data typically available for research are often collected for reimbursement purposes and lack clinical information.

General practices collect a range of patient information including diagnoses, medications prescribed, results of pathology tests ordered and so on. Practices are increasingly using clinical information systems and data extraction tools to make use of this information. This paper describes approaches used on several research projects to access clinical, as opposed to administrative, general practice data which to date has seen little use as a resource for research.

This information was accessed in three ways. The first was by working directly with practices to access clinical and management data to support research. The second involved accessing general practice data through collaboration with Primary Health Networks, recently established in Australia to increase the efficiency and effectiveness of health services for patients. The third was via NPS MedicineWise’s MedicineInsight program, which collects data from consenting practices across Australia and makes these data available to researchers.

We describe each approach including data access requirements and the advantages and challenges of each method. All approaches provide the opportunity to better understand data previously unavailable for research in Australia. The challenge of linking general practice data to other sources, currently being explored for general practice data, is discussed.

Finally, we describe some general practice data collections used for research internationally and how these compare to collections available in Australia.

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.

Personal health information in research: Perceived risk, trustworthiness and opinions from patients attending a tertiary healthcare facility

BACKGROUND

Personal health information is a valuable resource to the advancement of research. In order to achieve a comprehensive reform of data infrastructure in Australia, both public engagement and building social trust is vital. In light of this, we conducted a study to explore the opinions, perceived risks and trustworthiness regarding the use of personal health information for research, in a sample of the public attending a tertiary healthcare facility.

METHODS

The Consumer Opinions of Research Data Sharing (CORDS) study was a questionnaire-based design with 249 participants who were attending a public tertiary healthcare facility located on the Gold Coast, Australia. The questionnaire was designed to explore opinions and evaluate trust and perceived risk in research that uses personal health information. Concept analysis was used to identify key dimensions of perceived risk.

RESULTS

Overall participants were supportive of research, highly likely to participate and mostly willing to share their personal health information. However, where the perceived risk of data misuse was high and trust in others was low, participants expressed hesitation to share particular types of information. Performance, physical and privacy risks were identified as key dimensions of perceived risk.

CONCLUSION

This study highlights that while participant views on the use of personal health information in research is mostly positive, where there is perceived risk in an environment of low trust, support for research decreases. The three key findings of this research are that willingness to share data is contingent upon: (i) data type; (ii) risk perception; and (iii) trust in who is accessing the data. Understanding which factors play a key role in a person's decision to share their personal health information for research is vital to securing a social license.

Description and cost-analysis of emergency department attendances for hand and wrist injuries

BACKGROUND

Injuries to the hand and wrist are estimated to account for between 10% and 30% of all ED presentations. The economic burden placed on the healthcare system can be extensive and rise sharply with increase in injury severity.

OBJECTIVES

This cost-analysis was performed with the aim of estimating the economic implications of ED attendances for hand and wrist injuries from the perspective of one Australian public health network.

METHODS

Data from two EDs were retrieved from the electronic billing records of one large health network across two financial year periods (2014-2015 and 2015-2016) using ICD-10 codes. All costs that resulted from the treatment of any acute hand or wrist injury across the 2 year period were calculated and are presented by age, sex, injury type and mechanism of injury.

RESULTS

A total of 10 024 individuals presented to the two EDs in the 2 year period, accounting for approximately 5.4% of all presentations. The most common presentations were males (62.2%), people aged 25-34 years (26.9%) and lacerations (31.2%). The total cost in the 2 year study period was $3 959 535.38 ($1 923 852.38 in 2014-2015; $2 035 683.00 in 2015-2016). The mean cost per presentation was $383 (95% CI [$373, $393]) in 2014-2015 and $407 (95% CI [$394, $421]) in 2015-2016.

CONCLUSIONS

Acute hand and wrist injuries contribute to a significant volume of ED presentations each year in one Australian public health network leading to significant expenditure and health resources. Further research into how to best utilise resources and reduce avoidable injuries should be priority areas to reduce the cost of these injuries to the healthcare system and society.

Use of data linkage to improve communicable disease surveillance and control in Australia: existing practices, barriers and enablers

OBJECTIVES

To review the use of data linkage by Australian state and territory communicable disease control units, and to identify barriers to and enablers of data linkage to inform communicable disease surveillance and control activities.

METHODS

Semi-structured telephone interviews were carried out with one key informant from communicable disease control units in all eight Australian states and territories between October 2017 and January 2018.

RESULTS

Key informants from all Australian states and territories participated in the interview. A variety of existing practices were identified, with few jurisdictions making systematic use of available data linkage infrastructure. Key barriers identified from the review included: a lack of perceived need; system factors; and resources. Existing regulatory tools enable data linkage to enhance communicable disease surveillance and control.

CONCLUSIONS

We identified considerable variation in the use of data linkage to inform communicable disease surveillance and control activities between jurisdictions. We suggest that routinely collected, disparate data are systematically integrated into existing surveillance and response policy cycle to improve communicable disease prevention and control efforts. Implications for public health: Existing gaps in communicable disease surveillance data may affect prevention and control efforts. Data linkage is recognised as a valuable method to close surveillance gaps and should be used to enhance the value of publicly held health data.

CancerCostMod: a model of the healthcare expenditure, patient resource use, and patient co-payment costs for Australian cancer patients

Although cancer survival in general has improved in Australia over the past 30 years, Indigenous Australians, socioeconomically disadvantaged persons, and people living in remote areas still experience poorer health outcomes. This paper aims to describe the development of CancerCostMod, and to present the healthcare expenditure and patient co-payments for the first 12-months post-diagnosis. The base population is a census of all cancer diagnoses (excluding non-melanoma skin cancer) in Queensland, Australia between 1 July 2011 and 30 June 2012 (N = 25,553). Each individual record was linked to their Queensland Health Admitted Patient Data Collection, Emergency Department Information System, Medicare Benefits Schedule, and Pharmaceutical Benefits Scheme records from 1 July 2011 to 30 June 2015. Indigenous status was recorded for 87% of participants in our base population. Multiple imputation was used to assign Indigenous status to records where Indigenous status was missing. This base population was then weighted, using a programmed SAS macro (GREGWT) to be representative of the Australian population. We adopted a national healthcare perspective to estimate the cost of cancer for hospital episodes, ED presentations, primary healthcare, and prescription pharmaceuticals. We also adopted an individual perspective, to estimate the primary healthcare and prescription pharmaceutical patient co-payments. Once weighted, our sample represents approximately 123,900 Australians (1.7% Indigenous Australians). The total healthcare system cost of all cancers during the first 12-months post diagnosis was $4.8 billion, [corrected] and patient co-payments costs were $127 million. After adjusting for sex, age at diagnosis, Indigenous status, rurality, socioeconomic status, and broad cancer type, significant differences in costs were observed for population groups of interest within the first year post-diagnosis. This paper provides a more recent national estimate of the cost of cancer, and addresses current research gaps by highlighting the distribution of healthcare and individual costs by Indigenous status, rurality, and socioeconomic status.

A systematic review on the use of best practices for publishing linked data

Purpose

Data providers have been increasingly publishing content as linked data (LD) on the Web. This process includes guidelines (i.e. good practices) to publish, share, and connect data on the Web. Several people in different areas, for instance, sciences, medicine, governments and so on, use these practices to publish data. The LD community has been proposing many practices to aid the publication of data on the Web. However, discovering these practices is a costly and time-consuming task, considering the practices that are produced by the literature. Moreover, the community still lacks a comprehensive understanding of how these practices are used for publishing LD. Thus, the purpose of this paper is to investigate and better understand how best practices support the publication of LD as well as identifying to what extent they have been applied to this field.

Design/methodology/approach

The authors conducted a systematic literature review to identify the primary studies that propose best practices to address the publication of LD, following a predefined review protocol. The authors then identified the motivations for recommending best practices for publishing LD and looked for evidence of the benefits of using such practices. The authors also examined the data formats and areas addressed by the studies as well as the institutions that have been publishing LD.

Findings

In summary, the main findings of this work are: there is empirical evidence of the benefits of using best practices for publishing LD, especially for defining standard practices, integrability and uniformity of LD; most of the studies used RDF as data format; there are many areas interested in dissemination data in a connected way; and there is a great variety of institutions that have published data on the Web.

Originality/value

The results presented in this systematic review can be very useful to the semantic web and LD community, since it gathers pieces of evidence from the primary studies included in the review, forming a body of knowledge regarding the use best practices for publishing LD pointing out interesting opportunities for future research.

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.