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

[This corrects the article DOI: 10.1371/journal.pone.0249088.].

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.

Linkage of the Avon Longitudinal Study of Parents and Children (ALSPAC) to Avon & Somerset Police regional police records.

This data note describes a new resource for crime-related research: the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to regional police records. The police data were provided by Avon & Somerset Police (A&SP), whose area of responsibility contains the ALSPAC recruitment area. In total, ALSPAC had permission to link to crime records for 12,662 of the 'study children' (now adults, who were born in the early 1990s).  The linkage took place in two stages: Stage 1 involved the ALSPAC Data Linkage Team establishing the linkage using personal identifiers common to both the ALSPAC participant database and A&SP records using deterministic and probabilistic methods. Stage 2 involved A&SP extracting attribute data on the matched individuals, removing personal identifiers and securely sharing the de-identified records with ALSPAC. The police data extraction took place in July 2021, when the participants were in their late 20s/early 30s. This data note contains details on the resulting linked police records available. In brief, electronic police records were available from 2007 onwards. In total, 1757 participants (14%) linked to at least one police record for a charge, offence 'taken into consideration', caution, or another out of court disposal. Linked participants had a total of 6413 records relating to 6283 offences. Almost three quarters of the linked participants were male. The most common offence types were violence against the person (22% of records), drug offences (19%), theft (17%) and public order offences (11%). This data note also details important issues that researchers using the local police data should be aware of, including the importance of defining an appropriate denominator, completeness, and biases affecting police records.

Relationship between residential aged care facility characteristics and breaches of the Australian aged care regulatory standards: non-compliance notices and sanctions.

OBJECTIVES: To examine the relationship between structural characteristics of Australian residential aged care facilities (RACFs) and breaches of the aged care quality standards. METHODS: Facility-level analysis of audits, sanctions and non-compliance notices of all accredited Australian RACFs between 2015/16 and 2018/19. Structural factors of interest included RACF size, remoteness, ownership type and jurisdiction. Two government data sources were joined. Each outcome was analysed to calculate time trends, unadjusted rates and relative risks. RESULTS: Non-compliance notices were imposed on 369 RACFs (13%) and 83 sanctions on 75 RACFs (3%). Compared with New South Wales (NSW), non-compliance notices were less likely in Victoria, Queensland and the Northern Territory (NT), more likely in South Australia (SA), and comparable in Western Australia (WA), Tasmania and the Australian Capital Territory (ACT). RACFs with more than 100 beds and RACFs located in remote and outer regional areas (vs. major cities) also increased the likelihood of non-compliance notices. Compared with NSW, sanctions were less likely in Victoria, Queensland, NT and WA and comparable in SA, Tasmania and ACT. Additionally, the likelihood of sanctions was higher for RACFs with more than 40 beds. For both non-compliance notices and sanctions, no significant relationship was found with RACF ownership type. CONCLUSIONS: We partially confirmed other Australian findings about the relationship between RACF structural characteristics and regulatory sanctions and reported new findings about non-compliance notices. Routine and standardised public reporting of RACF performance is needed to build trust that Australia's latest aged care reforms have led to sustained quality improvements.

Australian arm of the International Spinal Cord Injury (Aus-InSCI) community survey: 1. population-based design, methodology and cohort profile.

STUDY DESIGN: Cross-sectional survey. OBJECTIVES: To describe design and methods of Australian arm of International Spinal Cord Injury (Aus-InSCI) community survey, reporting on participation rates, potential non-response bias and cohort characteristics. SETTING: Survey of community-dwelling people with SCI at least 12 months post-injury, recruited between March 2018 and January 2019, from state-wide SCI services, a government insurance agency and not-for-profit consumer organisations across four Australian states. METHODS: The Aus-InSCI survey combined data for people with SCI from nine custodians, using secure data-linkage processes, to create a population-based, anonymised dataset. The Aus-InSCI questionnaire comprised 193 questions. Eligibility, response status and participation rates were calculated. Descriptive statistics depict participant characteristics. Logistic regression models were developed for probability of participation, and inverse probability weights generated to assess potential non-response bias. RESULTS: 1579 adults with SCI were recruited, a cooperation rate of 29.4%. Participants were predominantly male (73%), with 50% married. Mean age was 57 years (range 19-94) and average time post-injury 17 years (range 1-73). Paraplegia (61%) and incomplete lesions (68%) were most common. Males were more likely than females to have traumatic injuries (p < 0.0001) and complete lesions (p = 0.0002), and younger age-groups were more likely to have traumatic injuries and tetraplegia (p < 0.0001). Potential non-response bias evaluated using selected outcomes was found to be negligible in the Aus-InSCI cohort. CONCLUSIONS: The Aus-InSCI survey made efforts to maximise coverage, avoid recruitment bias and address non-response bias. The distributed, linked and coded (re-identifiable at each custodian level) 'virtual quasi-registry' data model supports systematic cross-sectional and longitudinal research.

Patterns of homelessness and housing instability and the relationship with mental health disorders among young people transitioning from out-of-home care: Retrospective cohort study using linked administrative data.

OBJECTIVES: The study examined the relationship between mental health, homelessness and housing instability among young people aged 15-18 years old who transitioned from out-of-home in 2013 to 2014 in the state of Victoria, Australia with follow-up to 2018. We determined the various mental health disorders and other predictors that were associated with different levels of homelessness risk, including identifying the impact of dual diagnosis of mental health and substance use disorder on homelessness. METHODOLOGY: Using retrospective de-identified linked administrative data from various government departments we identified various dimensions of homelessness which were mapped from the European Topology of Homelessness (ETHOS) framework and associated mental health variables which were determined from the WHO ICD-10 codes. We used ordered logistic regression and Poisson regression analysis to estimate the impact of homelessness and housing instability respectively. RESULTS: A total homelessness prevalence of 60% was determined in the care-leaving population. After adjustment, high risk of homelessness was associated with dual diagnosis of mental health and substance use disorder, intentional self-harm, anxiety, psychotic disorders, assault and maltreatment, history of involvement with the justice system, substance use prior to leaving care, residential and home-based OHC placement and a history of staying in public housing. CONCLUSIONS: There is clearly a need for policy makers and service providers to work together to find effective housing pathways and integrated health services for this heterogeneous group of vulnerable young people with complex health and social needs. Future research should determine longitudinally the bidirectional relationship between mental health disorders and homelessness.

A blinded evaluation of privacy preserving record linkage with Bloom filters.

BACKGROUND: Privacy preserving record linkage (PPRL) methods using Bloom filters have shown promise for use in operational linkage settings. However real-world evaluations are required to confirm their suitability in practice. METHODS: An extract of records from the Western Australian (WA) Hospital Morbidity Data Collection 2011-2015 and WA Death Registrations 2011-2015 were encoded to Bloom filters, and then linked using privacy-preserving methods. Results were compared to a traditional, un-encoded linkage of the same datasets using the same blocking criteria to enable direct investigation of the comparison step. The encoded linkage was carried out in a blinded setting, where there was no access to un-encoded data or a 'truth set'. RESULTS: The PPRL method using Bloom filters provided similar linkage quality to the traditional un-encoded linkage, with 99.3% of 'groupings' identical between privacy preserving and clear-text linkage. CONCLUSION: The Bloom filter method appears suitable for use in situations where clear-text identifiers cannot be provided for linkage.

A comparison of trajectories of offending among people with psychotic disorders, other mental disorders and no mental disorders: Evidence from a whole-of-population birth cohort study.

BACKGROUND: Trajectory analysis has been used to study long-term offending patterns and identify offender subgroups, but few such studies have included people with psychotic disorders (PDs) and these have been restricted to adult offenders. AIMS: To compare offending trajectories among 10-26-year-olds with PDs with those with other mental disorders (OMDs) or none (NMD) and identify associated risk factors. METHODS: This is a record-linkage study of 184,147 people born in Western Australia (WA) 1983-1991, drawing on data from WA mental health information system, WA corrective services and other state-wide registers. Group-based trajectory modelling was used to identify offending trajectories. RESULTS: Four offender groups were identified in each mental health status group: G1-no/negligible offending; G2-early onset, adolescent, desisting by age 18; G3-early onset, low rate, offending into early adulthood; and G4-very early onset, high rate, peaking at age 17, continuing into early adulthood. The PDs group had the lowest proportion of individuals with no or negligible offending histories-84% compared with 88.5% in the OMDs group and 96.6% in the no mental disorder group. Within mental health status offender groups, the PDs group was characterised by early or very early onset offending persisting into adulthood, accounting for 5.4% and 3.7% of the group respectively (OMD: 3.8%, 1.5%; NMD: 1.0%, 0.5%). Gender, indigenous status, substance use problems, childhood abuse and parental offending were generally associated with trajectory group membership, although among those with PDs childhood abuse and parental offending were only significant in the early onset-life-course-persistent group. CONCLUSIONS: While most people with PDs never offend, some are disproportionately vulnerable from a particularly early age. If the offending subgroup is to be helped away from criminal justice involvement, interventions must be considered in childhood.

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.

Assessing the Risk of Australian Indigenous Sexual Offenders Reoffending: A Review of the Research Literature and Court Decisions.

The assessment of offenders' risk of reoffending, particularly sexual reoffending, is a core activity of forensic mental health practitioners. The purpose of these assessments is to reduce the risk of harm to the public, but they are controversial and become more contentious when Australian practitioners who want to undertake such assessments in an ethically responsible way must use reliable validated instruments, disclose the limitations of their assessment methods, instruments and data to judicial decision-makers and understand how decision-makers might use their reports. The purpose of this systematic literature review was to explore the practices of Australian practitioners and courts in respect of the assessment of Australian Indigenous male sexual offenders' risk of reoffending. We could not identify an instrument that has been developed for the assessment of this population group. Australian courts differ in whether they admit and give weight to practitioners' evidence and opinions based on data obtained with non-validated instruments. We could only identify three possible predictor variables with enough quantitative support to justify including them in an instrument that could be used to assess Indigenous sexual offenders. There is a need for research regarding the validity of the instruments that practitioners use.

Quantifying the societal cost of methamphetamine use to Australia.

Globally, there are increasing concerns about the harms associated with methamphetamine use. This paper i) reports on the results of a cost-of-illness (CoI) study that quantified the social costs associated with methamphetamine use in Australia and, ii) drawing on examples from this study, critically examines the general applicability of CoI studies for the alcohol and other drug field. A prevalence approach was used to estimate costs in 2013/2014, the most recent year for which reasonably comprehensive data were available. The value selected for a statistical life-year in our central estimate was AUD 281,798. Other costs were estimated from diverse sources. Total cost was estimated at AUD 5023.8 million in 2013/14 (range, AUD 2502.3 to AUD 7016.8 million). The greatest cost areas were crime including costs related to policing, courts, corrections and victims of crime (AUD 3244.5 million); followed by premature death (AUD 781.8 million); and, workplace costs (AUD 289.4 million). The social costs of methamphetamine use in Australia in 2013/14 are high, and the identification of crime and premature mortality as the largest cost areas is similar to USA findings and represents important areas for prevention and cost remediation. However, caution is required in interpreting the findings of any CoI study, as there is uncertainty associated with estimates owing to data limitations. Moreover, CoI estimates on their own do not identify which, if any, of the costs are avoidable (with drug substitution being a particular problem) nor do they shed light on the effectiveness of any potential interventions. We also recognise that data limitations prevent some costs from being estimated at all.

Sociodemographic differences in linkage error: an examination of four large-scale datasets.

BACKGROUND: Record linkage is an important tool for epidemiologists and health planners. Record linkage studies will generally contain some level of residual record linkage error, where individual records are either incorrectly marked as belonging to the same individual, or incorrectly marked as belonging to separate individuals. A key question is whether errors in linkage quality are distributed evenly throughout the population, or whether certain subgroups will exhibit higher rates of error. Previous investigations of this issue have typically compared linked and un-linked records, which can conflate bias caused by record linkage error, with bias caused by missing records (data capture errors). METHODS: Four large administrative datasets were individually de-duplicated, with results compared to an available 'gold-standard' benchmark, allowing us to avoid methodological issues with comparing linked and un-linked records. Results were compared by gender, age, geographic remoteness (major cities, regional or remote) and socioeconomic status. RESULTS: Results varied between datasets, and by sociodemographic characteristic. The most consistent findings were worse linkage quality for younger individuals (seen in all four datasets) and worse linkage quality for those living in remote areas (seen in three of four datasets). The linkage quality within sociodemographic categories varied between datasets, with the associations with linkage error reversed across different datasets due to quirks of the specific data collection mechanisms and data sharing practices. CONCLUSIONS: These results suggest caution should be taken both when linking younger individuals and those in remote areas, and when analysing linked data from these subgroups. Further research is required to determine the ramifications of worse linkage quality in these subpopulations on research outcomes.

The Effect of Vasectomy Reversal on Prostate Cancer Risk: International Meta-Analysis of 684,660 Vasectomized Men.

PURPOSE: Evidence of the effect of vasectomy on prostate cancer is conflicting with the issue of detection bias a key criticism. We examined the effect of vasectomy reversal on prostate cancer risk in a cohort of vasectomized men. Evidence of a protective effect would be consistent with a harmful effect of vasectomy on prostate cancer risk while nullifying the issue of detection bias. MATERIALS AND METHODS: Data were sourced from a total of 5 population level linked health databases in Australia, Canada and the United Kingdom. Cox proportional hazards regression analysis was used to compare the risk of prostate cancer in 9,754 men with vasectomy reversal to the risk in 684,660 with vasectomy but no reversal. Data from each jurisdiction were combined in a meta-analysis. RESULTS: The combined analysis showed no protective effect of vasectomy reversal on the incidence of prostate cancer compared to that in men with vasectomy alone (HR 0.92, 95% CI 0.70-1.21). CONCLUSIONS: These results align with those of previous studies showing no evidence of a link between vasectomy and prostate cancer.

Estimating parameters for probabilistic linkage of privacy-preserved datasets.

BACKGROUND: Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. METHODS: Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. RESULTS: Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher than the F-measure using calculated probabilities. Further, the threshold estimation yielded results for F-measure that were only slightly below the highest possible for those probabilities. CONCLUSIONS: The method appears highly accurate across a spectrum of datasets with varying degrees of error. As there are few alternatives for parameter estimation, the approach is a major step towards providing a complete operational approach for probabilistic linkage of privacy-preserved datasets.

Ensuring Privacy When Integrating Patient-Based Datasets: New Methods and Developments in Record Linkage.

In an era where the volume of structured and unstructured digital data has exploded, there has been an enormous growth in the creation of data about individuals that can be used for understanding and treating disease. Joining these records together at an individual level provides a complete picture of a patient's interaction with health services and allows better assessment of patient outcomes and effectiveness of treatment and services. Record linkage techniques provide an efficient and cost-effective method to bring individual records together as patient profiles. These linkage procedures bring their own challenges, especially relating to the protection of privacy. The development and implementation of record linkage systems that do not require the release of personal information can reduce the risks associated with record linkage and overcome legal barriers to data sharing. Current conceptual and experimental privacy-preserving record linkage (PPRL) models show promise in addressing data integration challenges. Enhancing and operationalizing PPRL protocols can help address the dilemma faced by some custodians between using data to improve quality of life and dealing with the ethical, legal, and administrative issues associated with protecting an individual's privacy. These methods can reduce the risk to privacy, as they do not require personally identifying information to be shared. PPRL methods can improve the delivery of record linkage services to the health and broader research community.

Improving the Estimation of Risk-Adjusted Grouped Hospital Standardized Mortality Ratios Using Cross-Jurisdictional Linked Administrative Data: A Retrospective Cohort Study.

BACKGROUND: Hospitals and death registries in Australia are operated under individual state government jurisdictions. Some state borders are located in heavily populated areas or are located near to major capital cities. Mortality indicators for hospital located near state borders may not be estimated accurately if patients are lost as they cross state borders. The aim of this study was to evaluate how cross-jurisdictional linkage of state hospital and death records across state borders may improve estimation of the hospital standardized mortality ratio (HSMR), a tool used in Australia as a hospital performance indicator. METHOD: Retrospective cohort study of 7.7 million hospital patients from July 2004 to June 2009. Inhospital deaths and deaths within 30 days of hospital discharge from four state jurisdictions were used to estimate the standardized mortality ratio of hospital groups defined by geography and type of hospital (grouped HSMR) under three record linkage scenarios, as follows: (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 inhospital death. An additional 496 cross-border deaths occurred within 30 days of hospital discharge. The inclusion of cross-jurisdictional person-level links to unlinked hospital records reduced the coefficient of variation among 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 regions with high cross-border hospital use. CONCLUSION: Cross-jurisdictional linkage modified estimates of grouped HSMRs in hospital groups likely to receive a high proportion of cross-border users. Hospital identifiers will be required to confirm whether individual hospital performance indicators change.

Limited privacy protection and poor sensitivity: Is it time to move on from the statistical linkage key-581?

BACKGROUND: The statistical linkage key (SLK-581) is a common tool for record linkage in Australia, due to its ability to provide some privacy protection. However, newer privacy-preserving approaches may provide greater privacy protection, while allowing high-quality linkage. OBJECTIVE: To evaluate the standard SLK-581, encrypted SLK-581 and a newer privacy-preserving approach using Bloom filters, in terms of both privacy and linkage quality. METHOD: Linkage quality was compared by conducting linkages on Australian health datasets using these three techniques and examining results. Privacy was compared qualitatively in relation to a series of scenarios where privacy breaches may occur. RESULTS: The Bloom filter technique offered greater privacy protection and linkage quality compared to the SLK-based method commonly used in Australia. CONCLUSION: The adoption of new privacy-preserving methods would allow both greater confidence in research results, while significantly improving privacy protection.

A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

BACKGROUND: Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives. OBJECTIVES: The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage. METHODS: In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known. RESULTS: The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601). CONCLUSIONS: This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.