bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Logistic Regression to Estimate the False Positive Rate in The IDI (SoLinks)
Authors: Lin Anna , Song Soon , Wang Nancy 
Published: December 2020

IntroductionStats NZ’s Integrated Data Infrastructure (IDI) is a linked longitudinal database combining administrative and survey data. Previously, false positive linkages (FP) in the IDI were assessed by clerical review of a sample of linked records, which was time consuming and subject to inconsistency.
Objectives and ApproachA modelled approach, ‘SoLinks’ has been developed in order to automate the FP estimation process for the IDI. It uses a logistic regression model to calculate the probability that a given link is a true match. The model is based on the agreement types defined for four key linking variables – first name, last name, sex, and date of birth. Exemptions have been given to some specific types of links that we believe to be high quality true matches. The training data used to estimate the model parameters was based on the outcomes of the clerical review process over several years.
ResultsWe have compared the FP rates estimated through clerical review to the ones estimated through the SoLinks model. Some SoLinks estimates fall outside the 95% confidence intervals of the clerically reviewed ones. This may be the result of the pre-defined probabilities for the specific types of links are too high.
ConclusionThe automation of FP checking has saved analyst time and resource. The modelled FP estimates have been more stable across time than the previous clerical reviews. As this model estimates the probability of a true match at the individual link level, we may provide this probability to researchers so that they can calculate linked quality indicators for their research populations.
Comparison of Time-Varying and Landmark Analysis Methods in Estimating the Association Between Medication Adherence and Outcomes: A Heart Failure Cohort
Authors: Qin Xiwen Simon , Knuiman Matthew W , Hung Joseph , Briffa Tom , Teng Tiew-Hwa Katherine , Sanfilippo Frank M 
Published: December 2020

IntroductionMedication adherence is associated with a reduction of adverse outcomes in heart failure (HF). However, this association is complex to estimate accurately because adherence (exposure) can vary during the follow-up period. Adherence can be estimated as a fixed exposure to predict outcomes, and this is known as a landmark analysis. In contrast, adherence can also be estimated as a dynamic exposure which varies over time in the follow-up period. This is known as a time-varying analysis and is expected to be the more precise method.
Objectives and ApproachWe compared these two methods in a HF cohort. We identified a population-based cohort of 3619 heart failure patients, aged 65-84 years hospitalised in Western Australia from 2003-2007 and who survived to 1-year post-discharge (landmark date). Adherence to renin-angiotensin system inhibitors (RASI) and β-blockers was calculated using proportion of days covered (PDC) expressed either as a fixed time exposure (in landmark analysis) or a varying exposure (in time-dependent analysis). The latter was updated every 30 days after the landmark date. Cox regression models were used to investigate the association between adherence and all-cause death at 1- and 3-years post-landmark date.
ResultsFor 1-year outcomes, hazard ratios (HR) for every 10% increase in PDC were similar between models from landmark analyses (RASI adherence: 0.93, 0.90-0.97; β-blocker adherence: 0.96, 0.92-1.0) and time-dependent analyses (RASI adherence: 0.94, 0.91-0.97; β-blockers adherence: 0.95, 0.92 -0.99). However, 95% confidence intervals estimated from time-dependent models were narrower than those from landmark analyses. HRs were slightly closer to the null when estimated from time-dependent models. A similar pattern was seen with 3-year outcomes.
Conclusion / ImplicationsTime-dependent analysis of adherence-outcome associations results in more precise estimates of hazard ratios. Estimates of HRs from landmark analysis models were similar but usually lower than those from time-dependent models.
One-Year Readmission and Emergency Department Presentation After an Epilepsy-Related Admission in People with Intellectual Disability: A Registry-Linkage Study
Authors: Liao Peiwen 
Published: December 2020

IntroductionIntellectual disability (ID) is a neurodevelopmental condition that affects approximately 1-2% of the population, and epilepsy is a common comorbidity in people with ID. Although hospital admission for epilepsy is also common, little is known about the impact of ID on healthcare use following an epilepsy admission.
Objectives and ApproachUsing linked administrative health datasets that included hospital admissions and disability service data, we aimed to examine whether the presence of ID led to greater or lesser use of healthcare services following an epilepsy admission, as represented by all-cause unplanned readmissions and emergency department (ED) presentations. Comparing the rate of readmissions and ED presentations within 30, 90 and 365 days of the first epilepsy admission during the study period, the effect of ID was assessed using Poisson regression.
ResultsA total of 18,987 patients had an epilepsy admission between 2005 and 2014, and of these, 3,256 (17.1%) had ID. Compared to patients without ID, patients with ID had a higher risk of unplanned readmissions within each follow-up period (adjusted incidence rate ratio (IRR) with 95% CI: 30 days: 1.48 (1.34, 1.65); 90 days: 1.42 (1.31, 1.54); 365 days: 1.49 (1.40, 1.59)). Differences were also found in the reasons for readmission, including more readmissions for neurological disorders. Similarly, the ED presentation risk was elevated in patients with ID (adjusted IRR: 30 days: 1.34 (1.23, 1.46); 90 days: 1.33 (1.24, 1.42); 365 days: 1.38 (1.30, 1.46)).
Conclusion / ImplicationsIn patients with epilepsy, the presence of ID appears to increase the chance of a readmission or ED presentation following a hospital admission for epilepsy, with the reasons for readmission also potentially different. This suggests the potential for improvements in post-admission screening and management.
A Linked Data Analysis Exploring the Real-World Burden and Hospital-Related Cost of Sarcoma in Western Australia: 1982 – 2016
Authors: Wright Cameron , Halkett Georgia , Carey Smith Richard , Moorin Rachael 
Published: December 2020

IntroductionBecause sarcomas are a rare group of malignancies, centralised referral and management improves outcomes. To plan centralised care, an understanding of disease burden is essential. Epidemiological studies on sarcoma from Australia are lacking, as previous studies have focused on a sarcoma type (e.g. soft tissue) or anatomical sites. As notification of all cancer diagnoses is required in Western Australia (WA), routinely collected data provides a platform to improve understanding of the sarcoma burden and associated cost.
Objectives and ApproachThis study aimed to determine incidence, prevalence, relative survival and cost of cancer-related hospitalisation for sarcoma in WA. Routinely linked cancer registry, hospital morbidity and death registration data from 1982 to 2016 were used. All new sarcoma cases among WA residents were included, using the Information Network on Rare Cancers (RARECARENet) definitions. To provide a reference point, comparisons were made with female breast, colorectal, prostate and lung cancers.
ResultsThe age-standardised incidence and prevalence of STS increased over time, while bone sarcoma remained more stable. For 2012-16, the combined sarcoma crude annual incidence was 7.3 per 100,000, with the majority of these soft tissue sarcoma (STS, incidence of 5.9 per 100,000). Five-year relative survival for the period 2012-16 for STS was 65% for STS, while five-year relative survival was 71% for bone sarcoma. This was higher than lung cancer, but lower than breast, colorectal and prostate cancer. Cancer-related hospitalisations cost an estimated $(Australian) 29.1 million over the period.
Conclusion / ImplicationsThe analysis of health service use showed sarcoma had a lower mean episode of cancer-related hospitalisation compared to the reference cancers in 2016, but the mean cost per prevalent person was higher for sarcoma than for female breast, colorectal and prostate cancer. STS incidence increased over time in WA, with an increasing proportion of people diagnosed aged ≥65 years.
Housing Insecurity Over Time: Exploratory Analysis of Repeat Housing-Service Use Within A Single Local Government Area in Wales
Authors: Thomas Ian , Mackie Peter 
Published: December 2020

IntroductionIn their 2019 homelessness strategy, Welsh Government make the commitment for a Wales where homelessness is a rare experience, and if it does occur is brief and non-recurrent. However, measuring repeated homelessness/housing issues (or ‘non-recurrence’) has thus far not been possible in Wales, with only aggregate data collected nationally on interactions between people and local government housing-services. Drawing on recently available individual level data from a single local government area in Wales, we set out to explore repeated use of housing/homelessness services.
Objectives and ApproachThe sample used in this analysis relates to approximately 6,000 individuals who sought assistance from Swansea local government housing-service during a four-year period, from January 2012 to December 2015. In order to group people with similar epeated interactions with the housing service, we use analyses that firstly aggregate the total time spent interacting with the service and over how many distinct periods (Cluster analysis), and secondly explore patterns in sequences of month-by-month service use histories (Sequence Analysis).
ResultsWe describe the patterns of repeat housing-service use identified through the Cluster Analysis and the Sequence Analysis, and the characteristics of each group. We also directly compare the ‘time-aggregating’ and ‘time-patterned’ based approaches to classifying people, in order to illustrate the differences that methodology can bring to our conceptualisation of repeat housing service use.
Conclusion / ImplicationsThe findings from this study have the potential to inform Wales’ move away from aggregate to individual level national homelessness data collection, by illustrating how individual level data can be used to provide new insights into homelessness. Exploring different conceptualisations of repeated housing-service use can also inform future developments in the measurement of repeat housing problems, and therefore monitor progress in achieving a Wales where homelessness is rare, brief, and non-recurrent.
Shared Priorities, Data and Reporting: Improving Access to Mental Health, Addictions and Home Care Services
Authors: Morris Kathleen , Diverty Brent , Damiano Natalie 
Published: December 2020

IntroductionAround the world, the need for mental health, addictions and home care services is growing. Government commitment and collective efforts to bridge data gaps, develop indicators and publicly report results are key elements in Canada’s efforts to improve access.
Objectives and ApproachThis symposium will demonstrate how a coalition of stakeholders united to use real-world data to measure progress and drive change. Each presentation highlights a different aspect of the project with participant interaction, aiming for the Canadian context to spark knowledge exchange across sectors and countries:

Presentation 1 - Coalitions and consensus (10 min.): processes and engagement for successful collaboration between governments, providers, measurement experts and people with lived experiences to select and develop indicators

Facilitated Q&A (5 min.)

Presentation 2 - Standards and data infrastructure (10 min.): new standards to enhance data comparability and strengthened data infrastructure to support measurement and reporting

Facilitated Q&A (5 min.)

Presentation 3 - Indicator development (10 min.): the indicator development cycle, methodological approaches using linked and partial data, and development strategies for new concepts

Facilitated Q&A (5 min.)

Presentation 4 - Public reporting and policy impact (10 min.): describes how public reporting supports sustained commitments and energizes change using targeted tools and messages

Facilitated Q&A (15 min.)

ResultsPublic reporting began in 2019, with 3 new indicators released annually over 4 years. Initial reporting provides a baseline to track improvements, and a starting point for health system planners to learn from peers across Canada. The indicators have been a catalyst to fill important data gaps in emergency and home care services.
Conclusion / ImplicationsThrough shared priorities, coalitions and linked data, information gaps are being filled to drive advancements in access to mental health and addictions services, and home care. Lessons learned in Canada can be adapted internationally to galvanize needed improvements in these sectors.
Application of A Framework to Guide Policy on Healthcare Resource Allocation Decisions to Data Linkage Projects
Authors: Olver Ian 
Published: December 2020

IntroductionData linkage of population data sets often across jurisdictions or linking health data sets or health data with non-health data often involves balancing ethical principles such as privacy with beneficence as represented by the public good. Similar ethical dilemmas occur in health resource allocation decisions. The NHMRC have published a framework to guide policy on health resource allocation decisions that could be applied to ensure the justification of data linkage projects that is defensible as in the interest of the public good.
Objectives and ApproachThe four main conditions for legitimacy of policy decisions about access to healthcare in a democracy with a public health system and limited resources wereexamined for their relevance to decisions about the use of public data and linking data sets.
ResultsPublic policy decisions must be defensible and responsive to the interests of those affected. Decision-makers should articulate their reasoning and recommendations so that citizens can judge them. While the context of policy decisions will differ, their legitimacy depends upon (1) the transparency of the reasoning which should be free from conflicts of interest, the basis for decisions recorded and report widely, (2) the accountability of the decision-makers to the wider community, (3) the testability of the evidence used to inform the decision-making, which usually means that it will stand up to independent review and(4) the inclusive recognition of those the decision affects which often requires that the implications for disadvantaged groups are considered, even if they can’t always be accommodated. These conditions are interrelated but ensure that the good of society in general and not just specific dominant groups are accommodated.
Conclusion / ImplicationsIt these principles are applied to decisions about data linkage projects they have clear applicability in society accepting data linkage projects having balanced the good against the ethical risks involved.
Defining Populations Within Linked Administrative Data
Authors: Wijnberg Duncan 
Published: December 2020

This presentation will outline methods developed by the ABS to define populations within linked administrative data. The methods developed use a combination of both direct and indirect signals (referred to as ‘signs of life’) to infer whether individuals are in a particular population at a given point in time. Data from multiple government sources are used.
IntroductionLinked administrative datasets hold significant potential to unlock new insights and understanding about different populations of interest. A key challenge is to create a research dataset that is properly representative of the population of interest at a given point in time. Without a representative population to serve as the basis of analysis, research outcomes are harder to interpret and compare against those from other populations. This has flow on consequences for any research findings derived from linked admin data.
Objectives and ApproachThis project sought to develop methods to define a representative Australian population from the Multi Agency Data Integration Project (MADIP) data asset. The core of the asset is created through a three-way linkage between Australian Medicare, Social Security and Taxation datasets. Together, these datasets have very high coverage of the Australian population and enable high quality linkage of other datasets into the asset. A ‘signs of life’ approach was used that sought to distinguish a representative population at a given point in time from the MADIP asset.
ResultsAn experimental representative population has been developed from the linkage spine that closely approximates the national age distribution and other breakdowns of the ABS’s Estimated Resident Population.
Conclusion / ImplicationsThis work demonstrates one approach that can be used to derive useful analytical populations from linked datasets with overly exhaustive scopes.
Sepsis within 30 days following elective surgeries in NSW public hospitals, January 2015-December 2017
Authors: Marashi-Pour Sadaf , Watson Diane E 
Published: December 2020

IntroductionPostsurgical sepsis is a common complication, accounting for one-third of all sepsis cases and associated with higher risk of mortality.
Objectives and ApproachThe Bureau of Health Information (BHI) in New South Wales (NSW), Australia produces independent reports and information about the performance of the healthcare system. Our report investigates the rate of sepsis within 30-days following surgery, and explores variation in risk standardised postoperative sepsis across NSW public hospitals. The study cohort and outcome definitions were drawn from existing international patient safety indicators, modified for appropriate use with Australian linked hospital and mortality data to identify patients transferred, or readmitted to any NSW public or private hospital with postoperative sepsis. Fine and Gray competing risks regression models were used to calculate risk-adjusted rates, and funnel plots were used to identify outliers.
ResultsRate of 30-day postoperative sepsis was 0.9% among 66,143 adult elective surgeries that met the inclusion criteria during January 2015 to December 2017. Results showed around 33% of post-operative sepsis were identified as occurring during either a transfer or readmission to hospital. Hospital-level unadjusted rates of postsurgical sepsis ranged from 0% to 2% across more than 80 NSW public hospitals. The majority of hospitals (94%) had postoperative sepsis results lower or no different than expected.
Conclusion/ImplicationsWe explored postoperative sepsis to help understanding of sepsis risk during the follow up period. Results showed a considerable number of postoperative sepsis cases would not have been identified without the use of linked data. Results on hospital risk standardised 30-day postoperative sepsis may prove useful as a screening tool for quality improvement in this area.
Hospital level risk-standardised all-cause readmission and returns to acute care following hospitalisations for eight clinical conditions
Authors: Marashi-Pour Sadaf , Watson Diane E 
Published: December 2020

IntroductionMeasures that assess how healthcare affects health outcomes make an important contribution to efforts to inform local efforts to improve care for patients in NSW.
Objectives and ApproachThe Bureau of Health Information (BHI) in New South Wales, Australia produces independent reports and information about the performance of the healthcare system. Our reports on readmission and returns to acute care following hospitalisation from eight clinical conditions investigated variation across more than 70 NSW public hospitals, with information available for 2000 to 2018.
Readmissions included both returns to acute care from non-acute inpatient settings and readmissions to any public or private hospital within 30-days or 60-days following hospital discharge. Risk standardised readmission ratios (RSRR) were calculated following linkage of admitted patient and mortality data, to also account for competing risk of death. Hospital outliers were identified using funnel plots. A sensitivity analysis explored the effect of residence in an aged care facility.
ResultsIn the most recent period, the unadjusted rate of readmission ranged from 10% for ischaemic stroke to 22% for congestive heart failure with rates remaining relatively stable over time for most of the condition. The proportion of readmissions that were returns to acute care from a non-acute hospitalisation ranged from 2% for chronic obstructive pulmonary disease (COPD) to 42% for hip fracture surgery. Across all eight conditions majority of hospitals had results lower or no different than expected. Number of hospitals with higher than expected readmissions ranged from none for total knee replacement to six for COPD. Taking into account residence in an aged care facility did not impact the results in a meaningful way.
Conclusion/ImplicationsThe RSRR method compares a hospital’s readmissions given its case-mix with an average NSW hospital with the same case-mix. In NSW, this method is a screening tool, identifying areas of excellence and of potential improvement.
Evaluating PPRL Vs Clear Text Linkage with Real-World Data
Authors: Jarrett Michael , Hills Brent , Zhao Yinshan , Brown Adrian , Randall Sean , Boyd James , Ferrante Anna , McGrail Kimberlyn 
Published: December 2020

IntroductionPrivacy-preserving Record Linkage (PPRL) is a record linkage technique that can increase the security of personal information. PPRL uses techniques of either hashing identifiers (where exact matches are required) or Blooming identifiers (where partial matches are of interest before they are provided for linkage.
Objectives and ApproachWe use LinXmart software to evaluate performance of PPRL linkage compared to linkage using clear text identifiers. The test linkage dataset is one that is routinely linked (N=2,672,257) at our linkage centre. The population spine (N=8,440,442) includes a record for every person who has resided in British Columbia, Canada over the past 30 years. Weights were determined using LinXmart’s implementation of the Expectation Maximization (EM) algorithm. For both linkages, accepted links were the highest-weighted candidate link with a weight above the threshold suggested by EM estimation. We compare linkage rates and quality and differences in weight and threshold estimations between clear-text and PPRL linkages
ResultsClear-text and PPRL methods resulted in 97% and 90% linkage rates, respectively. Approximately 67% of records in the linked datasets contained a nominally unique ID. Records with a unique ID linked at higher rates (>99% for both clear-text and PPRL) while the linkage rate for records missing the ID differed substantially (92% /70% for clear-text/PPRL). Comparing PPRL linkage to the clear-text linkage, we obtain F-measures of 0.99 and 0.80 for records with and without the unique ID, respectively.
Conclusion / ImplicationsLinkage performance may be attributable to differences in comparison operators between the two methods. Bloomed fields compared with Dice coefficient allow for partial matching but may not be as sensitive as clear-text string comparisons. Numerical comparisons in PPRL are exact matches while clear-text comparisons allow for more sophisticated matching. Further refinements in PPRL are being explored to improve these results.