bluuebunny/crossref_metadata_2025 huggingface dataset:
Data linkage of routinely collected qualitative health data: Using qualitative Patient Reported Experience Measures to understand the impact of digital hospitals on patients
Authors: Engstrom Teyl , Sullivan Clair , Thompson Shirley , Daly Jacqueline , Pole Jason D
Published: September 2024

ObjectiveData linkage and secondary use of routinely collected quantitative health data is ubiquitous. In recent years, the volume and breadth of routinely collected qualitative health data has grown. These data sources provide rich narrative information that could enable a broader understanding of healthcare challenges at scale, however linkage and secondary use of this qualitative health information is not common. This study explores the potential of linkage and secondary use of qualitative patient reported experience measure (PREM) data to understand the impact of digital hospitals on patients. 
ApproachIn Queensland, Australia, PREM surveys are distributed to most public hospital patient. Patient responses will be linked to the hospital and ward attended; qualitative comments will be extracted from two large hospitals: a digital hospital and non-digital hospital. Comments will be compared between the hospitals, focusing on factors which relate to experience of a digital hospital, either directly (e.g. computerised workstations), or indirectly (e.g. communication). 
Results & ConclusionsCurrently under ethics review – one challenge identified is that deidentification of free-text qualitative data at this scale is not feasible. Ethics committees may not have experience with this type of study and may require education on using qualitative health data at scale. 
ImplicationsLinkage and secondary use of routinely collected qualitative PREMs data has the potential to reduce participant burden in research, by utilising existing data sources to answer research questions. It can also broaden the scope of research by utilising data collected across multiple hospitals or jurisdictions, without significantly increasing the resources required.
Long-term trends in co-occurring medical and psychiatric hospitalizations among children and adolescents in Ontario, Canada.
Authors: Saunders Natasha , Guttmann Astrid , Chiu Maria , Gandhi Sima , Vigod Simone , Kurdyak Paul , Fung Kinwah , Sharpe Isobel , Emerson Scott , Toulany Alene
Published: September 2024

BackgroundPsychiatric conditions are common amongst hospitalized children. Co-occurring psychiatric conditions for medical hospitalizations contribute to length of stay, costs, and readmissions. We sought to measure trends over 20 years in pediatric hospitalizations for co-occurring medical and psychiatric conditions and compare with those without psychiatric comorbidity, overall and in free-standing children’s hospitals. 
MethodsWe identified all 3- to 17-year-olds hospitalized in Ontario, Canada between April 1, 2003 and March 31, 2022. Using health record discharge diagnoses, hospitalizations were assigned to 1 of 4 groups: 1) medical-diagnosis-only, 2) psychiatric-diagnosis-only, 3) primary medical diagnosis with psychiatric comorbidity, and 4) primary psychiatric diagnosis with medical comorbidity. Hospitalization trends for 1) all hospitals, and 2) free-standing children’s hospitals were described and compared.
ResultsFrom 2003 to 2022, medical-diagnosis-only hospitalizations declined 39% (41,909 to 25,486 hospitalizations), psychiatric-diagnosis-only hospitalizations increased 96% (3227 to 6337), medical hospitalizations with psychiatric comorbidity increased 127% (977 to 2221) and psychiatric hospitalizations with medical comorbidity increased 100% (2051 to 4096). Among pediatric hospitals, medical-diagnosis-only hospitalizations increased 23% (12,430 to 15,318), psychiatric-diagnosis-only hospitalizations increased 420% (271 to 1408), psychiatric hospitalizations with medical comorbidity increased 172% (539 to 1468) and medical hospitalizations with psychiatric comorbidity increased 235% (478 to 1599).
ConclusionsHospitals have experienced large absolute and relative increases in volumes for psychiatric conditions both with and without co-occurring medical conditions, particularly among free-standing children’s hospitals. Healthcare provider training, hospital resourcing, and health system planning must consider how best to accommodate the increasing acute psychiatric care needs of hospitalized children and adolescents.
Comparing health service use before and after transition to a supported housing model for clients who experience severe and persistent mental illness in southwestern Ontario, Canada
Authors: Booth Richard G. , Lam Melody , Forchuk Cheryl , Yang Annie , Shariff Salimah Z.
Published: September 2024

Objective and ApproachBeginning in 2018, a provincially-funded custodial housing model in Ontario, Canada transitioned to a supported housing model that allowed more autonomy for clients who experience severe and persistent mental illness (SPMI). The objective of this study was to compare health service use before and after transition to the new Community Homes for Opportunity (CHO) program in southwestern Ontario between 2017 and 2019. Information about clients who transitioned to the CHO program were obtained from the Ontario Ministry of Health and Long-Term Care and linked to health administrative data at ICES. Rates of emergency department (ED) visits, primary care visits, and specialist visits in the one year before and after implementation of the CHO program were compared using conditional Poisson models.
ResultsOf the 368 clients, approximately 40% were female and the mean age was 57 years old. Compared to before the transition, clients had more primary care visits (rate ratio [RR] = 1.21; 95% CI: 1.07-1.37) and specialist visits (RR = 1.33; 95% CI: 1.11-1.60) within the year after transition to the CHO program. There was no significant change in the use of emergency department visits following the transition (RR = 1.20; 95% CI: 0.96-1.50).
ConclusionsSupported housing may be associated with greater use of primary and specialist care for clients who experience SPMI.
ImplicationsThe new supported housing model may encourage clients to use more personalized health care, according to their specific needs. Such personalized support is crucial for clients with complex health care needs.
Research to understand and provide evidence for a generalised approach to data linkage
Authors: Huck Rachel , Cummins Sarah
Published: September 2024

ObjectiveOrdinarily data linkage is approached on a project-by-project basis, tailoring the method to the research need. An increase in demand for data linkage has led to the development of a more efficient strategy, i.e. a generalised approach.  
Through data linkage, a series of indexes representing people, businesses, geography and classifications are created using administrative data. Additional data are linked to the indexes via a general method to collect a common identifier.  
Adopting a generalised approach requires an evidence base to ensure research aims can be met by the methods. This research will provide the evidence needed to underpin the strategy as well as guidance for implementing a generalised approach using an index.  
ApproachThe existing data linkage portfolio provides an opportunity to compare the application of a bespoke to a generalised methodology. Comparisons will collate information on:

Index coverage;
Linkage results and quality including precision and recall estimates;
Analysis of the bias observed within the linked data.

Of particular interest is the linkage of different population sub-groups, particularly those classified as vulnerable or disadvantaged, for example, data for prisoners, refugees, the homeless and third-sector organisations.
ResultsWe will present the findings to date on recommendations for the use of a generalisable method for indexing, by exploring:

Data linkage quality by bespoke methods versus a generalised approach
The coverage strengths/limitations of the indexes
Sub-groups representation in the linked data

Conclusions/Implications Findings will provide evidence for adopting a new data linkage strategy, ensuring the most appropriate data linkage methods and quality assurance have been applied. Therefore, producing accurate and unbiased analysis to form the evidence base for policy decisions.
Training and capacity building: Developing a support framework for researchers using administrative data
Authors: Oliver Emily , Mir Saba , Gordon Emma
Published: September 2024

BackgroundAdvances in data infrastructure and data access legislation supporting the safe use of securely held administrative data have led to increased data being available for research in recent years. While uptake by researchers has increased, opportunities for innovative, impactful research in the public interest outweigh the number of researchers using these data.
Objective To drive up use, Administrative Data Research UK (ADR UK) embarked on the delivery of a Training and Capacity Building Strategy. Its objectives are to raise awareness across disciplines; to support more researchers to use administrative data for the first time; and to keep them using it for more advanced research, using a comprehensive researcher support framework.
Approach By mapping potential users of administrative data across multiple career stages, we identified activities, products and approaches to test. These range from low-cost, high-reach activities to in-depth, targeted approaches, and include sustainable products to ensure longevity.
ResultsTesting and evaluation of these varied approaches has enabled us to understand more about administrative data users and their needs, individually and collectively. They have underlined the need for sustained awareness and development of available data and opportunities, supported by accessible tools and resources to maintain momentum in what can be a frustrating research environment.
Conclusions and ImplicationsThe framework we've created offers scaffolding from which to hang multiple approaches to drive up the use of administrative data. Communities and networks play an important role in supporting users in this niche area of study across different sectors and disciplines, and in creating a sustainable future for research in this field.
The hidden impact of alcohol on young victims: an analysis of police-related alcohol offences resulting in hospitalisation
Authors: Sims Scott
Published: September 2024

BackgroundAlcohol-related harm (ARH) remains a significant public health concern, particularly affecting young individuals who are disproportionately impacted. This study focuses on the often-overlooked impact of alcohol on young victims involved in alcohol-related police incidents resulting in hospitalisation. While existing research often centres on the drinker, this study explores the characteristics of both offenders and victims, analysing offence types and investigating the under-ascertainment of ARH in hospital records.
MethodsOur research, conducted as a retrospective longitudinal study in Western Australia, utilises linked data from hospital admissions, emergency department (ED) presentations, and police incident records. The study includes 22,747 individuals aged 12–24 involved in alcohol-related police incidents between 2004 and 2015. 
ResultsFemale victims were 10 times more likely than males to be involved in alcohol-related police incidents, while women had a 2 times higher likelihood of undiagnosed alcohol-related hospital admissions than men. Aboriginal people were overrepresented as both offenders and victims. ED presentations and hospital admissions were prevalent, with head injuries being the most common outcome. Notably, 71% of victims hospitalised did not receive an ARH diagnosis.
Conclusions A noticeable gap exists between hospital admissions associated with alcohol-related incidents and cases officially classified as ARH in the hospital system. This difference points to a more significant issue of substantial under-ascertainment or insufficient identification of ARH than previously acknowledged. Our study emphasises the need for targeted interventions, collaborative efforts between health and justice agencies, and ongoing research to address the hidden impact of alcohol on young victims.
Linking for Impact: Enhancing Linked Data Infrastructure to Meet Clinical Trials Sector Needs
Authors: Miller Kate , Flack Felicity
Published: September 2024

BackgroundAustralia possesses valuable population health data, yet its potential for advancing medical product development remains largely untapped. Transformative growth in the use of linked data in clinical trials will support Australia’s therapeutic development sector to be more responsive in the development of new therapeutics and the monitoring and surveillance of their safety and effectiveness.
MethodsWe conducted interviews with clinical trialists and data linkage experts to understand the current state and awareness of linked data within the clinical trials sector, identify existing pain points in the linkage process, and explore opportunities for improving visibility and access for the clinical trials sector.  Researchers represented all stages of the medical product development pipeline and had a diverse range of experience with linked data.
ResultsInterviews revealed numerous barriers hindering the clinical trials sector from effectively using linked data, limiting its impact. Barriers included a lack of awareness, the complexity of the application and approval process, and lengthy delays in accessing data.
Participants readily recognised several ways that linkage of real-world data could be applied to their work in clinical trials, with pre-recruitment data, measurements of primary and secondary endpoints, and health economic analysis being the most consistently noted use cases.
ConclusionTo optimise the use of linked data to support clinical trials and medical product development in Australia, increased awareness among the therapeutic development sector regarding available real-world data and its potential is needed urgently. Lowering the barriers to accessing linked data will enhance health services and patient outcomes across Australia.
Measuring error in the Demographic Index – steps towards a future population statistics system in England and Wales
Authors: Archer Rosalind , Diyasena Peshali , Grant Emma
Published: September 2024

ObjectiveWe are developing methods to measure the quality of the Demographic Index at a National Statistics Institute. The Demographic Index is the foundational dataset for a future, transformed, population statistics system for England and Wales. It clusters records for individuals across many years of health, education, and tax data, and assigns them a unique ID. 
Previous research has helped us to conceptualise three types of error in the Demographic Index: clustering error, coverage error, and data measurement error. We are currently working on estimating one type of clustering error, whereby records for two individuals are mistakenly assigned the same ID (“false positive clusters”).
ApproachPrevious work has allowed us to identify variables associated with false positive clusters. We are now working on a stratification method, whereby each ID in the Demographic Index is scored according to how likely it is to contain this error. We plan to measure uncertainty using bootstrapping. 
Results and ConclusionsThis work is ongoing, and we hope to obtain results by summer 2024.
ImplicationsIt is vital for us to understand and measure error in the Demographic Index because this is necessary for measuring error in any statistics derived from the Index. And it is crucial that population statistics made by any future system should have measures of error. Assuming that our work shows promise, we will continue by measuring other types of error, and by creating use cases to test how these measures can be fed forward into secondary analyses (e.g. population estimation).
Disability Benefit Reform and Benefit Outcomes: A Re-examination of the Introduction of the UK Personal Independence Payment Using Linked Population Data
Authors: Miller Ana-Corina , McVicar Duncan , Rowland Neil , Jahanshahi Babak
Published: September 2024

ObjectivesMany countries face the problem of how to provide support for additional costs faced by disabled people while restricting disability benefit program growth given tight public finances. In 2013, the UK reformed its main additional costs disability benefit with this objective, changing both medical screening and payment rates with the introduction of the Personal Independence Payment (PIP). This study uses newly available linked administrative population data to examine the impact of this major reform on disability benefit receipt. 
ApproachWe use the newly available 2011CBI dataset, which links Census records to microdata on benefit receipt for the population of England and Wales from 2011-2015. Difference-in-difference and synthetic control methods are used to estimate the reform impact on the probability of flowing onto disability benefits, exploiting the structure of the roll-out of PIP’s introduction across English regions. 
ResultsIntroducing PIP led to a sharp fall in the probability of disability benefit onflow, with tentative evidence of a partial reversal in the following year. Further analysis is required to quantify the extent to which this reflects well-known administrative delays in processing applications as opposed to a step change in the probability of claims being successful. 
ConclusionsThis study is the first to present linked administrative population data estimates of the benefit recipiency effects of the introduction of PIP. In doing so it both contributes to the wider international literature on disability benefit reform and provides an early research application of a significant new administrative dataset for England and Wales.
Mapping UK Pain Datasets to the OMOP Common Data Model: Lessons Learned
Authors: Milligan Gordon , Masood Erum , Quinlan Phil , Cox Sam , Giles Tom , Mendez Villalon Armando , Cole Christian
Published: September 2024

ObjectiveChronic Pain is defined as pain lasting for three months or longer and a report by the British Pain Society in 2016 found that 28 million adults live with this condition. Chronic pain research is problematic as it is poorly represented in health data and often in silos. Alleviate is the Advanced Pain Discovery Platform (APDP) Data Hub which is removing barriers to access to data.
ApproachThe aim for Alleviate is to transform pain data sets within the UK to be Findable, Accessible, Interoperable and Reusable (FAIR) and be more discoverable for researchers via Health Data Research UK’s Cohort Discovery Tool. The tool enables identification of potential cohorts in real-time from datasets Alleviate provides. The onboarding requires datasets to be transformed to the open and widely used Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).
ResultsWe collaboratively developed CaRROT tools and used our mapping expertise to transform datasets to OMOP-CDM. The tools have improved efficient mapping of clinical and research data, covering ~10 million individuals’ records. Subsequently we learned valuable lessons on how to accurately and consistently map across data sets to support federated discovery. We also identified a lack of standard vocabulary representations for pain specific data.
ConclusionsMapping data to OMOP is not straightforward. Attention to detail is required to ensure that consistent mapping decisions are made to maximise data reusability and interoperability.
ImplicationsIn sharing the lessons learned of mapping datasets to OMOP we aim to help improve interoperability of disparate data sources.
The role of emergency department crowding on the implementation of efficiency strategies to improve care for adult patients presenting with chest pain.
Authors: Rowe Brian , Yang Esther , Doran Shandra , Graham Michelle , Van Diepen Sean , Raizman Josh , Tsui Albert
Published: September 2024

IntroductionThis study evaluated the operational and clinical outcomes for patients presenting to an emergency department (ED) with chest pain using a 2-hour high-sensitivity troponin T (hs-TnT) protocol compared to an existing 3-hour hs-TnI protocol.
MethodsThis retrospective cohort study used eight population-based linked health administrative datasets for adult patients presenting to a Canadian urban ED with chest pain over a two-year period. The primary outcome was ED length of stay (LOS). Secondary outcomes included health outcomes within 30 days.
ResultsOverall, 5426 patients were included; 2879 and 2547 in the hs-TnI group and hs-TnT groups, respectively. The cohorts were similar: the median age was 58 years, 55% male, and comorbidities matched. Delays in physician initial assessment (PIA; +54 min; 95% CI: 42.2-65.8) and patients leaving without being seen increased (7% vs 12.5%; P < 0.0001) due to worsening overcrowding. The median ED LOS increased from 448 to 481 minutes after hs-TnT implementation (median difference = 33.0; 95% CI: 19.9 to 46.1), although time to second tests decreased by 54 minutes. At 30 days, there were no differences in readmission or death before and after the intervention.
ConclusionImplementation of a 2-hour hs-TnT protocol resulted in mixed outcomes: increased PIA and ED LOS, yet faster time to second test. The journey through the ED for patients with chest pain is complex and affected by issues beyond the assay type and the timing of repeat Tn measurements. ED overcrowding needs to be addressed for efficiency to be realized in this setting.
Enhancing population-level research among people who inject drugs: a validation and retrospective cohort study using health administrative data in Ontario, Canada
Authors: Greenwald Zoë R , Feld Jordan J , Werb Dan , Austin Peter C , Drover Samantha , Fridman Daniel , Bayoumi Ahmed , Gomes Tara , Kendall Claire E , Lapointe-Shaw Lauren , Scheim Ayden I , Bartlett Sofia R , Benchimol Eric I , Bouck Zachary , Greenaway Christina , Janjua Naveed Z , Leece Pamela , Wong William WL , Sander Beate , Kwong Jeffrey C
Published: September 2024

ObjectiveHealth administrative data can support population-level research among people who inject drugs (PWID), however these data sources remain underutilized due to the difficulty in identifying drug use in routinely collected data. We validated case-ascertainment algorithms to identify PWID and tested their application in a hepatitis C (HCV) cohort in Ontario, Canada. 
ApproachWe conducted a validation study using reference standard cohorts of PWID recruited via community-based studies and population controls linked to health administrative data in Ontario, Canada (1992-2020). Tested case-ascertainment algorithms included combinations of hospitalizations/emergency department (ED) visits for drug use/poisoning, physician visits for drug use, opioid agonist treatment (OAT), or injecting-related infections. Sensitivity and specificity were estimated for lifetime history and recent injecting (past 1-5 years). We applied a high-performing algorithm among all Ontarians with laboratory-confirmed HCV between 1999-2018, to identify a sub-cohort of PWID with HCV. 
ResultsAn algorithm including ≥1 hospitalization/ED visit or ≥1 physician visit for drug use or ≥1 OAT record had high accuracy for identifying IDU history (91.6% sensitivity, 94.2% specificity) and recent IDU (using 3 years lookback: 80.4% sensitivity, 99% specificity). When applied to a provincial cohort of 112,947 Ontarians diagnosed with HCV, this algorithm estimated 46% (N=52,248) had a history of IDU, of whom 52% (N=27,246) had an indication of recent IDU (within the past 3 years).  
ConclusionThe methods developed in this study can enhance the capacity of population-level health research among people who inject drugs and support applied public health interventions towards hepatitis C elimination.
A population-based repeated cross-sectional study using administrative health data to examine the impact of the COVID-19 pandemic on mental wellness in citizens of the Métis Nation of Ontario
Authors: Lyons B. Casey , Stewart Andrea , Obiekwe Rochelle
Published: September 2024

ObjectiveLinking data on people who experience drug overdoses can provide new insights and opportunities for intervention. However, because public health data infrastructure in the United States (US) is often siloed, linkage activities can require incentivization and support. In 2023, we began funding 20 states to conduct overdose-related data linkage. We sought to understand baseline capacity in funded states.
ApproachData linkages in this project focus on two areas: 1) linking fatal and nonfatal overdose data and 2) linking fatal or nonfatal overdose data to prescription drug monitoring program (PDMP), criminal justice, or social determinants of health (SDOH) data. We report opportunities identified during implementation regarding states’ capacity to perform the required linkages as well as needs for additional training and technical assistance.  
ResultsOf 20 funded states, 11 (55%) reported some previous experience linking fatal and nonfatal overdose data; 10 (50%) have linked PDMP data, while only 3 (15%) have linked SDOH data and 2 (10%) criminal justice data. Jurisdictional needs included: training on data linkage methods, including developing and validating linkage algorithms; overcoming administrative barriers to data sharing, such as data use agreements; and developing standardized approaches to characterizing events of interest in diverse data sources. States valued sharing strategies and experiences with each other.
Conclusions/ImplicationsAdditional capacity building is needed for states to successfully link and utilize overdose-related data. We are actively collaborating with state partners to facilitate peer-to-peer knowledge exchange to develop successful linkage programs.
Linkage for risk-sensitive environments: Australian examples of privacy-preserving record linkage using Bloom filters
Authors: Ferrante Anna , Brown Adrian , Randall Sean , Boyd James
Published: September 2024

Introduction Organisations are increasingly aware of the risks and responsibilities of handling personally identifying information (PII). These factors not only influence internal data management practices but also impact on data linkage arrangements with other parties. Some linkage environments are particularly sensitive to the release or use of PII. Advances in privacy-preserving record linkage methods such as PPRL-using-Bloom make it possible to undertake highly accurate data linkage without release or disclosure of PII. Such methods play a role in enabling data linkage in risk-sensitive environments. 
Objectives and ApproachWe present and describe several Australian case studies where the PPRL-using-Bloom method has been used to enable data linkage between organisations. We report on the defining elements of each case, the associated risks and solutions, as well as quality and performance issues. We also reflect on challenges and opportunities for future improvement.
ResultsAustralian use cases utilising privacy preserving linkage (PPRL-using-Bloom) include projects linking state-based datasets to Commonwealth datasets, some linking primary care data to state-based secondary healthcare data, and others linking healthcare data to non-health datasets such as police and criminal justice datasets.
Conclusion / ImplicationsMethods such as PPRL-using-Bloom play a critical role in enabling data linkage in highly risk-sensitive environments. However, in an ever evolving world where risks and requirements are constantly changing, linkage methodologies and technologies must remain adaptable to meet evolving demands.
Residential mobility and receipt of measles, mumps and rubella vaccination: analysis of linked primary care electronic health records in a disadvantaged London region
Authors: Firman Nicola , North Laura , Marszalek Milena , Wilk Marta , Gutierrez Ana , Johnson Rhodri , Griffiths Lucy , Fry Rich , Dezateux Carol
Published: September 2024

ObjectiveCoverage for the measles, mumps and rubella (MMR) vaccination in north-east London (NEL) is the lowest in the United Kingdom. It has been hypothesised that children who move home frequently are less likely to receive vaccinations. We examined the association between number of addresses in the first two years of life, and receipt of MMR vaccination by age two.
ApproachWe derived households by pseudonymously linking the addresses of 178,028 children registered with a NEL general practitioner (GP) on their second birthday (2015-2021). We included 135,221 (76.0%) children (51.0% male) after excluding 42,807 with invalid household characteristics at age 24 months. The outcome was MMR vaccination by 24 months. Residential mobility was categorised by number of addresses (1, 2, ≥3) between earliest GP-registration and vaccination date/second birthday. We calculated the percentage receiving MMR by residential mobility and estimated adjusted odds (aOR; 95% confidence intervals [CI]) for MMR receipt.
Results105,392 (77.9%) children received MMR by age two, and 26,652 (19.7%) had more than one address. Receipt of MMR decreased with increasing residential mobility: 80.9% (95% CI: 80.6,81.1), 66.5% (65.9,67.1), and 58.6% (56.2,60.9) for children with one, two, or three or more addresses respectively. Children with multiple addresses were less likely to receive MMR by age two: aOR: 0.53 (0.51,0.55); 0.36 (0.32,0.40) for 2 and ≥3 addresses respectively.
Conclusions Uptake of MMR vaccine by two years of age is lower in children with multiple addresses. Further research is needed to identify actionable opportunities to improve MMR uptake in mobile populations.
Variation in 10 year birth trajectories of mothers involved in family court care proceedings and their peers in England.
Authors: Gilbert Ruth , Ireland Georgina , Jay Matthew , Wijlaars Linda
Published: September 2024

ObjectiveFamily court (FC) care proceedings decide on removing children from parental care in response to concerns about risks of harm. Courts and social care report frequent births, often after short birth intervals as a key problem among mothers presenting to FCs.
ApproachWe used a cohort of mothers with a first live birth (FLB) between 2007 and 2019 to estimate the cumulative incidence of FC within 10 years and compare birth trajectories with peers.
Results3,118,327 women (15-50 years) had a FLB, of whom 34,062 had FC involvement. Cumulative incidence of FC within 10 years from FLB was 1.3% (95% Confidence Interval [CI]; 1.3-1.3) overall but highest in mothers who were younger (6.7% if <20 years), more deprived (2.5% in most deprived areas) and with morbidity (22.7% with learning or multiple disability, 12.8% with adversity-related injuries or 5.7% with mental health admissions).
If followed for 10 years from FLB, 58.4% (8,889/15,229) of women with FC involvement had ≤2 deliveries, compared to 82.2% otherwise (1,007,365/1,225,163). If <25years at FLB, women involved in FC had more deliveries than their peers (3+ deliveries: 47.8%, 5,853/12,255 vs 29.5%, 123,092/416,904), however, if 25+, they had fewer deliveries if involved in FC (1 delivery: 49.6% 1,475/2,974 vs 39.2% 316,976/808,259).
Conclusions and ImplicationsAt-risk mothers may benefit from early, targeted health and social care interventions to prevent FC involvement. Birth data highlights variation in birth trajectories and dispels the stereotype of women involved in FCs having many children, particularly if older at FLB.
Navigating Data Acquisition and Data Quality Validation of Large Databases: Practical Lessons
Authors: Hudema Nedeene , Hutton Amanda , Sidhu Nirmal , Lu Xinya , Feng Xue
Published: September 2024

ObjectiveHave you ever been frustrated when working to acquire data? Have you experienced the trials and tribulations of readying data? ‘Best laid plans often go awry’. ‘A problem shared is a problem halved’ and we’d like to share our experiences and lessons learned with you.
We are a Canadian provincial organization with over 20 years experience working with large comprehensive data currently in the midst of validation work on newly acquired data. This behind the scenes and sometimes forgotten work can take considerable time, but it is crucial and integral for research.
ApproachData acquisition is complex, particularly when adding new data to existing data files. Many validation steps are vital to ensuring that data used in research are the highest quality possible and limitations are understood. The process began with preparing the agreement and list of new variables to add in 2018 for 4 databases (hospital, drug, physician, emergency), to signatures in 2023, and it is ongoing. While we have a plan to do this work, it requires flexibility and constant updates based on new information learned.
ConclusionInvestigating errors, deciding level of acceptance of errors, managing relationships, and communication are the most critical aspects of the work. Contingency plans are important when it takes longer than expected. Data are never perfect, but a thoughtful approach to validation and documentation of limitations and decisions support using the data appropriately. Also, a kind demeanor, an open mind, and a sense of humour can go a long way!
Does change in area-level deprivation, change health outcomes? A latent class growth analysis of population data.
Authors: Ferry Finola , McDowell Ron , Rosato Michael , Murphy Jamie , Leavey Gerard
Published: September 2024

BackgroundWhile the link between deprivation and health is established, little is known about the association of persistent deprivation or deprivation trajectories over time with adverse health outcomes.
AimTo examine latent class trajectories of area level-deprivation from 2010-2016 and their association with social distress indicators from 2017-2021.
MethodAnalysis was based on linked administrative data (N=1,569,110) from NI GP Registrations Index, emergency department records (2017-21), enhanced prescribing data (2017-21) and biennial area-level deprivation (2010-2016). Latent class growth analysis (LCGA) identified deprivation trajectories between 2010 and 2016; and regression-based models, adjusted for age, sex and urbanicity, examined their association with indicators of individual level distress: occurrence of death, any accident and emergency (A&E) visit, and any psychotropic medication between 2017 and 2021.
ResultsBased on comparison of models and fit statistics, a non-linear LGCA model identified six trajectories: consistently deprived (21.2%); slight improvement (7.1%); substantial improvement (1.2%); consistently average deprivation (31.7%); slight worsening (18.5%); and consistently non-deprived (20.4%). Consistently living in a deprived area was associated with higher likelihood of death, A&E visits and receipt of hypnotics, anxiolytics, and anti-depressants. Compared to consistent deprivation, slight improvement was associated with lower likelihood of death (OR=0.94, CI: 0.91-0.97) and all psychotropic medication in the follow-up period.
ImplicationsFindings indicate that even a slight improvement in deprivation status can have a positive influence on health outcomes. Further population-wide analysis of deprivation trajectories, their determinants and associated health impact will inform targeted interventions that promote social mobility and improved health.
Designing a Data Dashboard for Health Departments and Overdose Fatality Review Teams
Authors: Pisani Marie , Oguss Madeline , Manneh Claire , Mayampurath Anoop , Afshar Majid
Published: September 2024

IntroductionOverdose Fatality Review (OFR) teams within health departments rely on data from multiple isolated sources to study the opioid crisis. Recently, we linked electronic health record data with state agency data to form a regional Substance Misuse Data Commons (SMDC) using privacy-preserving record linkage. Our goal in this study was to use human factors design principles to design a data dashboard for OFR teams using the linked datasets that will overcome current barriers within OFR workflows.
MethodsWe utilized NASA task load surveys, semi-structured interviews, and design sessions with end users to identify data needs for an optimal dashboard design. We assessed current workloads, data collection processes, and desired future state. We subsequently performed iterative design sessions for the generation and evaluation of low-fidelity prototypes. To overcome issues with privacy and security, we used synthetic data in a cloud-based platform to represent the SMDC for simulation. 
ResultsEleven OFR organizers participated. Pre-dashboard surveys on existing workflow showed high mental workload associated with data aggregation and case review, identifying a need for more accessible, comprehensive data. In our low-fidelity dashboard demo with synthetic data, iterative design adjustments were made in data visualization, storyline organizations, and theme-based data aggregation across pre-hospital and hospital data.
ConclusionsWe refined the data dashboard prototype into a high-fidelity version, set for further usability and human factors evaluation. We addressed privacy and security concerns through synthetic data use while the real-world data is maintained in a HIPAA-secure Azure cloud environment with access for approved users.
A novel linked dataset to improve understanding about the health of people in Northern Ireland’s prisons
Authors: Cooper Janine , O’Reilly Dermot , Kelly Trish , Kirk Richard , McGarrigle Stephen , Gray Ruth , Donnelly Michael
Published: September 2024

Objective and ApproachWe describe a collaboration between the Queen’s University Belfast, Administrative Data Research Centre (ADRC) in Northern Ireland (NI) and the NI Healthcare in Prisons Service (HIPS) to develop a novel linked database to assess the health of people in prison in NI. Prison health data were extracted by the HIPS using electronic/manual modes for the period 2012-2021 and transferred to the Honest Broker Service, a trusted research environment, for linkage, de- identification and access to data. Data from prison health records were linked via a unique health identifier to a healthcare population spine, prescriptions data (primary care), hospital admissions data (mental health), income deprivation and mortality data.
ResultsA novel linked dataset has been developed including 16 variables from prison health records for N=14,898 individuals and N=34,213 custodial episodes (individuals may have ≥1 custodial episode during the study period). The entire NI population (healthcare population spine data) will be included as comparator data. Dataset cleaning has commenced for analyses. The study aims are to (i) examine the health/mental health of people in prison in NI, (ii) examine all-cause/drug-related mortality risk after release from prison and (iii) characterise individuals with the greatest mortality risk.
ConclusionsWe discuss the development of a novel linked dataset using prison health records and present results from our research questions about the health of people in prison.
ImplicationsThis work may direct future research and may be used to guide health services policy changes and improve outcomes after prison release.
Outcomes in clinical subgroups of patients with alcohol-related hospitalizations: a population-based retrospective cohort study
Authors: Friesen Erik , Mataruga Andrea , Nickel Nathan , Kurdyak Paul , Bolton James
Published: September 2024

ObjectiveIndividuals who experience alcohol-related hospitalizations are at a high risk of recurrent harm and premature mortality. This project characterized the clinical subgroups of individuals who experience alcohol-related hospitalizations to understand who is at the highest risk of recurrent harm following discharge. 
ApproachPopulation-based retrospective cohort study of individuals with an alcohol-related hospitalization between 2017-2018 in two Canadian provinces (Ontario and Manitoba) using linked provincial health administrative databases. Clinical subgroups were identified with latent class analysis based on the type and frequency of alcohol-related health service use in the two-years preceding the index hospitalization. Associations between subgroup membership, readmission, and mortality in the year following discharge were evaluated using multivariable time-to-event regression. 
ResultsIn cohorts of 4,753 (Manitoba) and 29,290 (Ontario) individuals, seven subgroups were identified. These followed a severity gradient from low-frequency service use for acute intoxication to high-frequency service use for alcoholic liver disease. Individuals in the ‘liver disease’ subgroup had the highest risk of 1-year mortality relative to the rest of the cohort (adjusted hazard ratio [aHR]: 3.83, 95% confidence interval (CI): 2.80-5.24). A small subgroup of individuals with a history of high-frequency alcohol-related health service had the highest hazard of readmission (aHR: 5.09, 95% CI: 4.11-6.31). 
Conclusions and ImplicationsThere are distinct clinical subgroups of individuals who experience alcohol related hospitalizations and individuals with high-frequency health service use and alcohol-related liver disease are at the highest risk of readmission and mortality. These subgroups merit consideration in strategies aimed at reducing the risk of post-discharge harm.
Data linkage in public health research: a scoping review of ethical, legal and societal aspects surrounding administrative data
Authors: Jesus Neves Félix , Lima Barreto Mauricio , Wells Valerie , Silveira Martha , Araújo Almeida Bethânia
Published: September 2024

ObjectiveThe application of data linkage for scientific research purposes in the public health sphere requires using personal and sensitive data on an individual level while results are analyzed from a population perspective. Considering this, ethical, legal and social issues (ELSI) must be considered. In this sense, our study aims to better understand how ELSI surrounding administrative data linkage use in public health has been addressed in the scientific literature.
ApproachOur scoping review is based on the Joann Briggs Institute Manual for Evidence Synthesis and will be reported according to the Preferred Report Items for Systematic Reviews and Meta-Analyses – Scoping Review Guideline. Two independent authors searched for articles published between January 2013 and December 2023 in the PubMed/MEDLINE, Web of Science, EMBASE and LILACS databases, as well as in Scielo and Google Scholar platforms. Keywords used were related to ‘data linkage’, ‘administrative data’, ‘ELSI’, “public policies’ and ‘public health’ terms. Articles were screened initially by title and abstract, then by full-text read. 
ResultsAfter duplicate removal and articles screening, two independent authors are performing data extraction considering ethical, legal and regulatory basis as well as procedures for data access; data management process including record linkage; type of administrative data linked; data protection strategies; and data subjects rights.
ConsiderationsThis scoping is underway, we intend to have our final results by April to present at the conference, in September.
Implementation of the Frictionless data standard for linked data
Authors: Jarrett Mike
Published: September 2024

Objective and ApproachData linkage centres receive, hold and provision data in a wide variety of formats. Using a consistent, flexible and open metadata standard for data holdings can enable a center to clearly and unambiguously describe their data holdings and facilitate processing pipelines. One such framework is the Frictionless data standard. We present our experience at our data centre implementing this standard for both internal data management and for communication with external data providers and third parties.
ResultsOur team has replaced tool-specific metadata files with standard-compliant files to make our pipelines more modular and less fragile. Since the standard is based on JSON, most programming languages will support reading and writing metadata files and we are not restricted to any software. This work has also made our internal tooling interoperable with that of external partners. We find that the standard is well equipped to handle CSV and other delimited files. Our center uses a mix of file types including fixed-width text files which do not have an explicit specification within the standard, but its extensibility has allowed us to define our own file type while staying within the ecosystem. We have also developed tools to convert JSON metadata files to excel workbooks for a more human-friendly format. 
ConclusionsThe Frictionless data standard can be a powerful tool for data centers in organizing data and building processing pipelines.
ImplicationsAdopting the Frictionless data standard for metadata files has streamlined our internal processes and improved internal and external communication.
SynD: Australian synthetic health data community of practice
Authors: Hachey Ben , Austin Jodie , Boyd James , Engstrom Teyl , Marashi Amir , Morgan Clare , Philip Reji , Pointon Keren , Snewin Meagan , Sullivan Clair , Haines Melanie
Published: September 2024

ObjectivesThe current workflow for health data research in Australia is inefficient. After funding is secured, researchers often face delays of months or years to access the necessary data. Synthetic data could significantly improve the pace and impact of health data research but lacks foundational infrastructure. We aim to develop this infrastructure and support the use of synthetic data to improve data access and research quality across Australia.
ApproachWe held two workshops with Australian groups working on synthetic data. The format included participant updates and invited talks on international approaches to synthetic data and health data research. Workshops collected use cases and stimulated discussion on national collaboration. A facilitator then led thematic analysis to draft a consensus roadmap and terms of reference towards national synthetic data infrastructure.
ResultsWe recruited 18 participants. Participants were cross sectoral: universities (9), research funding bodies (5), state health departments (4). Represented six states and territories: Queensland (6), New South Wales (3), Victoria (3), Western Australia (3), Australian Capital Territory (2), South Australia (1). Gender: women (11), men (7). The roadmap includes stakeholder engagement, a governance framework, and training events.
ConclusionSynD is an Australian community of practice for synthetic health data. Our mission is to unlock the value of health information through synthetic data to advance research, education, innovation and service delivery within the health and care sector. This collaborative effort should ensure a harmonised approach to the safe and effective utilisation of synthetic data to enhance health outcomes across Australia.