bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of dementia among people experiencing homelessness in Ontario, Canada: a population-based comparative analysis
Authors: Booth Richard , Forchuk Cheryl , Dasgupta Monidipa , Shariff Salimah
Published: September 2024

BackgroundCognitive decline in people experiencing homelessness (PEH) is an increasingly recognized issue. We compared the prevalence of dementia among PEH to housed individuals in the general population and those living in low-income neighborhoods. 
ApproachA population-based cross-sectional comparative analysis using linked healthcare administrative data from Ontario, Canada. We included individuals ≥45 years on January 1, 2019 who visited hospital-based ambulatory care (eg, emergency department), were hospitalized, or visited a Community Health Centre in 2019; and identified PEH if they had one or more healthcare records with an indication of homelessness or unstable housing. Prevalence of dementia was ascertained using a validated case definition for Alzheimer’s disease and related dementia. Poisson models were used to generate estimates of prevalence.  
Findings12,863 PEH, 475,544 low-income comparators, and 2,273,068 general population comparators were assembled. Among these groups, dementia prevalence was 68.7, 62.6, and 51.0 per 1,000, respectively. Descriptively, prevalence ratios between PEH and the comparator groups were highest within the ages of 55-64 and 65-74 in both sexes, ranging from 2.98 to 5.00. After adjusting for age, sex, geographical location of residence, and health conditions associated with dementia, prevalence of dementia among PEH was found to be 1.71 (95% CI: 1.60–1.82) and 1.90 (1.79–2.03) times greater than the low-income and general population comparators, respectively.  
InterpretationPEH experience high burden of dementia compared to housed populations in Ontario. Findings suggest that PEH may experience dementia at younger ages and may benefit from the development of proactive screening and housing interventions.
Factors influencing young people’s transitions from child to adult mental health services in Wales
Authors: Roberts Louisa , Wood Sophie , Wilkins David , Shelton Katherine
Published: September 2024

ObjectivesThis presentation provides an overview of young peoples’ transitions from child to adult mental health services in Wales. Transitions are unstable times where need for support can be greatest, yet many young adults fail to qualify for ongoing specialist support. Young people with social care needs and/or living in poverty face an increased likelihood of mental ill health. These underlying factors of disadvantage are modifiable and can be considered ‘solution linked variables’ (O’Campo and Dunn, 2011) of particular relevance in public health policy development.  
ApproachThis study positions intersectionality theory within a quantitative, secondary data methodology. Descriptive statistics and logistic regression models were used to elicit how social care need, deprivation, mental health diagnoses, gender and ethnicity might interact to influence likelihood of transition from child to adult mental health services. Sequence analyses developed pathway typologies from varying patterns of mental health service access. 
ResultsNovel findings reflecting the interactional influences of differing social care need and area levels of deprivation on child to adult mental health service transitions will be presented alongside results controlling for gender, ethnicity and mental health diagnoses. The value of mapping typologies of mental health service use will be discussed in relation to the findings.
ConclusionsInterim findings suggest greatly increased mental health service use and differing patterns of access for young people with social care needs and/or living in the most deprived areas as they transition to adulthood. The implications for service development and delivery in times of unprecedented demand are explored.
Ethnoracial disparities in childhood growth trajectories in Brazil: a longitudinal nationwide study of four million children
Authors: Benes Matos da Silva Helena , Freitas de Mello e Silva Juliana , Ribeiro‑Silva Rita de Cássia , Chis Ster Irina , Rebouças Poliana , Goes Emanuelle , Ichihara Maria Yury , Ferreira Andrêa , M. Pescarini Julia , Leovigildo Fiaccone Rosemeire , S. Paixão Enny , L. Barreto Maurício , De Araujo Almeida Bethania
Published: September 2024

Growth is an important marker of child health and development. It is related to aspects such as social-economic conditions, being affected by social inequalities. Race is a social construct that functions as an essential tool of racism. It creates social hierarchy, resulting in segregation, different quality and access to health care, and unequal distributions of social determinants on health. Understanding the effects of ethno-racial inequalities on growth trajectories is essential to improve children development and well-being. In the study we investigated child growth according to maternal ethno-racial group using a nationwide Brazilian database. Data were obtained via linkage of the CIDACS Birth Cohort and the Brazilian Food the Nutrition Surveillance System. It included 4,090,271 children under 5 years old, born at term, followed-up between 2008 and 2017. We used mixed-effects model to estimate both original and standardized forms of length/height and weight trajectories. Results pointed out to growth differences among the racial groups, concerning both markers. Children born to Indigenous mothers presented the most critical situation, followed by those born to Parda, Asian-descent, and Black mothers. The strengthening of policies aimed at protecting Indigenous children should be urgently undertaken to address systematic ethno-racial health inequalities. Additionally, these findings may help policymakers to achieve the United Nation’s 2030 Sustainable Development Goals (eradication of hunger and all forms of malnutrition).
Healthcare contact days for people with stage IV non-small cell lung cancer (NSCLC) in Ontario: A population-based study
Authors: Nguyen Paul , Gupta Arjun , Booth Christopher , Hanna Timothy
Published: September 2024

BackgroundSurvival is limited with advanced NSCLC, and frequent healthcare visits can become all-consuming. We investigated patterns of contact days—days with any in-person healthcare contact as a measure of potential time toxicity—in a population-based sample. 
MethodsWe created a population-based, retrospective cohort with health administrative data from Ontario, Canada, of adults with stage IV NSCLC in 2014-2017, dying 2014-2019. The primary outcome was contact days assessed from diagnosis to death. We stratified analyses by receipt, type and lines of systemic therapy administered. We plotted and fitted with cubic splines the weekly percentage of contact days to obtain trajectories over the disease course. 
ResultsWe identified 5,785 stage IV NSCLC patients. The median (interquartile range [IQR]) survival was 108 days (49-426), and median percentage of contact days was 33.3%. Patients receiving systemic treatment had longer median survival (261 [152-420] vs. 66 [34-130] days) and lower median percentage of contact days (22.2% vs. 40.9%). Overall and for subgroups (systemic therapy vs. not; type and lines of therapy), trajectories followed a U-shaped distribution, with highest rates immediately following diagnosis and prior to death. The difference between the maximal peak and trough was greater in patients who received systemic therapy (peak 34.8% vs. trough 15.9%, ""deeper U"") vs. not (39.5% vs. 27.6%, ""shallower U""). 
ConclusionStage IV NSCLC patients spent a significant proportion of days alive with healthcare contact. These data serve as a call to recognize patient time burdens, improve care efficiency, and better support patients during periods of high burden.
Applying Newly Identified Financially Focused Home Care Quality and Performance Indicators In Alberta's $23.5B/annum Health System - Preliminary Findings
Authors: Jajszczok Max , Quan Hude , Eastwood Catherine A , Lu Mingshan , Cunningham Ceara
Published: September 2024

Through a multi-phased mixed-method research program including an international scoping review and a modified-Delphi panel with expert policy/academic/operational representatives from across Canada, three health-system, financially focused quality and performance home care indicators were identified.  
This presentation will provide preliminary results of the application of the three financial indicators on overall health-system measures, system utilization and population outcomes within the province of Alberta.  The time-period covered is the last five years data leading up to the start of the deceleration of the covid-19 global pandemic.  
Based on provincial annual financial reporting, baseline 2016/17 fiscal year home care expenditures were $585K, this rose to significantly to $716M for fiscal year 2019/20, with the most significant increase (13%) occurred between the 2017/18 and 2018/19 years.  Prior to 2016/17 home care expenditures increased at a rate less than 3%.  These significant home care investments increased the percent of the overall expenditures in Alberta from 3.94 to 4.6%.   Furthermore, the average annual expenditures per home care client rose from $5,417 to $6,112.  
During this same time-period, numerous health-system indicators shifted to more favorable positions, with notable decreases in acute care days prior to death, number of those waiting in hospital for LTC, and preventing/delaying the need for LTC overall.  
Based on comparisons of home care investments on the overall health-system and key health-system performance indicators focused on measuring system efficiencies, preliminary examinations suggest that significant home care focused investments in Alberta significantly improved health-system performance, efficiencies, and overall outcomes for the population.
Linking trial data to ICES: incorporating a prompt in a research ethics protocol submission platform in Southwestern Ontario
Authors: FitzGerald Theresa , Garg Amit , Basile Erika
Published: September 2024

IntroductionThe linkage of trial data with large administrative databases can enable long-term passive follow-up of participants at a significantly lower cost than direct participant follow-up in a study. Nonetheless, many researchers are unaware of this opportunity and/or the regulatory requirements to facilitate linkage.
ApproachIn 2017, Western University Canada’s Office of Human Research Ethics (OHRE) incorporated a prompt into its online protocol submission platform, asking researchers if they have considered linking their trial data with ICES. ICES is a not-for-profit research and analytics institute in Ontario, Canada with a repository of over 100 data holdings comprised of record-level, coded and linkable health and health-related data. If a researcher selects ‘yes’ to this prompt, they are provided with additional information about ICES, identifiers required for linkage, and language to be included in letters of consent.
ResultsThe incorporation of a prompt into the ethics protocol submission platform allowed the OHRE to identify protocols interested in linking trial data with ICES. Over the past 5 years, an average of 2.6% of protocols submitted to the Health Sciences Research Ethics Board included an intent to link data with ICES. The OHRE verified that these protocols had carefully considered regulatory requirements, which helped to streamline the ethical, privacy, and legal processes required for linkage.
ConclusionIncorporating a prompt into ethics protocol submission platforms can help to streamline regulatory processes and promote awareness about opportunities to link trial data with large administrative databases.
Creating an intergenerational cohort of mothers and their children using administrative data from health, education and social care in England (ECHILD)
Authors: Feng Q , Gilbert Ruth , Ireland Georgina , Harron Katie
Published: September 2024

ObjectiveMaternal physical, psychological, and social risk factors extend beyond impacting maternal wellbeing to significantly influence their children. Sibling dynamics also play a crucial role in individual development, health and wellbeing. We established a national intergenerational cohort of mothers and their children using administrative health, education and social care data in England (ECHILD).
ApproachWe extracted 14.5 million baby records from hospital records for births between 1997-2022 and linked 13.6 million (94.1%) of these to delivery records of 8.0 million mothers using a validated probabilistic algorithm. We then identified clusters of mothers with only-children and mothers with sibling-children by identifying livebirths linked to the same mother.
ResultsThe cohort captures 87.7% of all livebirths in England and includes mothers aged up to 37 and their children. We identified 4,086,648 mother-only-child clusters and 3,957,856 mother-sibling-children clusters. Compared with only-children, children with siblings were more likely to live in more deprived areas and have younger mothers, but were less likely to be overdue births (>=42 weeks gestation), or to have very low birth weight (<1500g). Among the mother-sibling-children clusters, sibship sizes varied between 2-15, with a mean of 2.4 children per mother. The median birth interval was 3.0 years.
Conclusions and ImplicationsThis national cohort of 8 million mothers and their children (including 4.1 million mother-only-child and 4.0 million mother-sibling-children clusters) linked to hospital, education and social care data is an important resource for investigating the effects of maternal exposures, sibling dynamics and their interplay on individual development, health and wellbeing.
Pragmatic Clinical Trials, Linkages and Agreements: Interjurisdictional Collaboration on Pragmatic Clinical Trials
Authors: Bakal Jeff , Youngson Erik , Garrison Scott
Published: September 2024

The randomized clinical trial framework has proven to be a robust way of evaluating and comparing medications and procedures for many years. The promise of measured and unmeasured balance and equipoise through randomization remains very appealing.  Emerging challenges for trialists have been diminishing returns in terms of effect sizes as treatments become more effective and the ever-growing costs associated with the operation of clinical trials.
The costs and operational overhead limit the ability of publicly funded trials to operate at a sufficiently robust level. Recently we have been working to engage clinicians and patients in pragmatic clinical trials which in part leverage routinely collected health system data to both provide an unbiased and effective means of obtaining high quality data for recruiting, randomization and outcomes.
As these trials have expanded between provincial jurisdictions, we have had to look for creative solutions to assembling and sharing data in order to reach the trial goals.  This presentation will examine some of the technical and logistical challenges that we have faced, how they have been addressed and the path forward for clinical trials.
Occupation exposure to coal dust and vulnerability to Influenza: Scottish miners and the 1918 Influenza Pandemic.
Authors: Dibben Chris , Williamson Lee , Reid Alice , Garrett Eilidh , Christen Peter , Nanayakkara Charini
Published: September 2024

ObjectiveThere has been little work on the high level of mortality, noted that the time, in coal mining areas during the 1918 Influenza pandemic. Increased risk during viral infection from exposure to particulates (eg cigarette smoke, air pollution) has been studied. 
ApproachWe use the historic administrative data for Scotland, 1900 to 1930, with standardised codes for occupation and cause of death, and a pseudo household design and Quasi Poisson models, where the spouses of miners are their controls, to test whether miners (aged 20 to 50) were more at risk of death during the main waves of the 1918 pandemic than a matched population. Secondly, we repeat the analysis for Labourers to test if [1] Sex or [2] hard labour and for clerks, if [3] Pulmonary Tuberculosis might explain the effect.
ResultsWe find that miners compared to their spouses were significantly more likely to die during all waves of the pandemic but considerably more so during the Autumn wave (RR 4.7). This difference was even greater for younger miners (20 to 35) (RR 7.6). In contrast labourers and clerks had a much lower and often non-significant comparative risk of death during all waves than their spouses. This was true even for those aged 20-35.
ConclusionsMale coal miners appear to have been at much higher risk of death compared to matched populations. 
ImplicationsWorkers with exposure to airborne particulates should be a priority for public health planning during periods of high virus infections.
A single parameter method for secure privacy preserving record linkage
Authors: Christen Peter , Ziyad Sumayya , Vidanage Anushka , Nanayakkara Charini , Schnell Rainer
Published: September 2024

ObjectivesData linkage is the process of matching records that refer to the same entities (often people) across databases. In applications such as health research or government services, the databases to be linked are often sensitive and cannot be shared between organisations. Privacy-preserving record linkage (PPRL) aims to overcome this challenge by facilitating the comparison of encoded or encrypted records without having to share sensitive data. Most existing PPRL techniques are based on heuristics and they have limitations in the privacy protection they offer, such as being vulnerable to certain cryptanalysis attacks. Furthermore, existing PPRL methods have multiple parameters, which, if not set properly by the user, can result in sub-optimal linkage quality and reduced privacy protection.
ApproachWe present a novel PPRL method that uses random reference q-gram sets to generate bit-arrays that represent sensitive values. Our method has a single parameter to be set by the user that trades scalability with linkage quality and privacy protection. All other parameters are either data-driven or have strong bounds based on this user parameter.
ResultsWe conceptually analyse our method and conduct experiments on multiple databases. The results demonstrate that our method provides high linkage quality and strong privacy protection while being scalable to link very large databases.
ConclusionOur novel PPRL method provides high linkage quality, scalability, and improved privacy protection compared to existing PPRL methods such as Bloom filter encoding. A major advantage of our method is that it requires a single parameter to be set by the user.
Trends in incidence of self-harm, neurodevelopmental and mental health conditions among university students compared to the general population: a nationwide electronic data linkage study in Wales.
Authors: Rouquette Olivier , Lee Sze Chim , Smith Jo , Del Pozo Banos Marcos , John Ann
Published: September 2024

Objective and ApproachThey are growing concerns that self-harm and mental health conditions are increasing in university students. This may reflect widening access to higher education, existing population trends or stressors associated with this setting. We linked real-world data from the Higher Education Statistics Agency between 2012-2018 with primary and secondary healthcare records. Students were undergraduates aged 18 to 24 years at university entry. Non-students were pseudo-randomly selected based on an equivalent age distribution. We used regression approach to examine characteristics of students and non-students and their risks of self-harm and mental health conditions before and during university.    
ResultsThis e-cohort study included 96,760 students and 151,795 non-students. Being male, self-harm and mental-health conditions recorded before university entry, and higher deprivation levels resulted in lower odds of entering university and higher odds of dropout. Risks of self-harm, Autistic Spectrum Disorder (ASD), depression, anxiety, drug misuse, and schizophrenia were lower for students. Risks of self-harm, ASD, ADHD, depression, alcohol misuse and schizophrenia were increasing more in students over time. Older students experienced higher risk of self-harm and mental-health conditions. Younger students were more at risk of alcohol misuse than non-students.
ConclusionsMental health conditions in students are common, diverse and they influence their academic outcomes. University students have mental health needs and trajectories that differ from those of the general population.
ImplicationsThe diversity and complexity of students’ needs require integrated person-centred stepped care approach within universities including triage, access to well-being support, counselling, and referral pathways to mental health services.
Algorithmic Identification of Multiple Sclerosis in the SAIL databank
Authors: Middleton Rod , Nicholas Richard , Tallantyre Emma , Witts James , Marrie Ruth Ann , Craig Elaine , Knowles Sarah , Pearson Owen , Harding Katherine , Kreft Karim , Hawken Jonathon , Ingram Gillian , Morgan Bethan , Robertson Neil
Published: September 2024

BackgroundMultiple Sclerosis (MS) is a challenging disease to identify within large repositories of healthcare data. Diagnosis can be protracted requiring many modalities that may not form part of the repository data collection. Accurate case finding would have multiple applications for studying epidemiology.
AimDevelop a case finding algorithm within the Secure Anonymised Information Linkage (SAIL) Databank that can reliably elicit Multiple Sclerosis.
MethodUtilising a cross sectional cohort study we used multiple datasets within SAIL; General Practice, Inpatient, Outpatient and Office of National Statistics to develop our case finding algorithm based on the coding nomenclatures and timing within these datasets. The results of this algorithm were then tested against two patient data sets: The UK MS Register (n=836), consisting of mostly self confirmed disease and a clinical cohort from South West Wales (n=713).
ResultsFrom 4,757,428 records, the algorithm identified 6,194 cases of MS within Wales on 31st December 2020 (prevalence 221.65 [95%CI 216.17–227.24] per 100,000). Case finding sensitivity and specificity was 96.8% and 99.9% for the clinically validated population-based cohort and sensitivity was 96.7% from the self-declared registry population.
ConclusionWe successfully identified MS cases within Wales and verified this within two independent data sets.
Improving transparency and quality assurance: Operationalising semi-automated data provenance tracking in a Trusted Research Environment
Authors: O'Sullivan Katherine , Markovic Milan , Dymiter Jaroslaw , Martin Adrian , Odo Chinasa , Rowlands Helen , Ciocarlan Ana , Wilde Katie , Casey Arlene
Published: September 2024

We present a prototype solution for improving transparency and quality assurance of the data linkage process through a data provenance dashboard designed to assist data analysts, researchers and information governance teams in authenticating and auditing data workflows within a trusted research environment (TRE). Building on prior research (Scheliga, et al., 2022), this work describes our first operationalised prototype tested in a real-world setting.
The prototype development involved four stages: (1) Co-design of interfaces with end users for provenance data collection and visualisation, producing a low-fidelity design; (2) Extension and refinement of the Safe Haven Provenance (SHP) ontology (https://tre-provenance.github.io/SHP-ontology/releases/v0.2/index-en.html); (3) Design and implementation of mechanisms for semi-automated collection of data linkage provenance using the SHP ontology; (4) Implementation and user evaluation of the dashboard.
A participatory design process with data analysts, researchers and information governance teams resulted in a low-fidelity prototype and was validated via public consultations to ensure it met public trust. The resulting prototype dashboard (https://tre-provenance.github.io/) was built as an offline desktop app to match the deployment TRE requirements. The interactive dashboard displays the data linkage information extracted from a knowledge graph described using the SHP ontology (e.g., modifications of datasets, data release) and results of rule-based validation checks (e.g., checking extracted data against researchers' specification). User evaluations confirmed the dashboard would contribute to better quality of data linkage.    
This project demonstrates the next stage in advancing transparency and quality assurance within TREs by semi-automating and systematising data tracking from ingress to egress in a single tool.
AD|ARC (Administrative Data Agri-Research Collection): Comparative analysis of highest educational qualification in Welsh households receiving a farming subsidy with rurality-matched control households, using 2011 UK Census data.
Authors: Addison Katy , Morrison-Rees Sian , Caskie Paul , Crowley Liam , Madden Laura , Scully Sean
Published: September 2024

Objective To investigate highest level of educational attainment in farming households compared to rural non-farming households in Wales.
Approach We used the AD|ARC dataset of households in Wales receiving farming subsidies in 2010.
We included farming households containing at least one member reporting an Agricultural Main Occupation (AMO) and households where all members reported Non-Agricultural Main Occupations (Non-AMO) but farming occurs.
Utilising Census 2011 variables relating to age, gender, education and occupation we conducted comparative analyses of educational attainment within AMO, Non-AMO and non-farming rural households at both an individual and household level. 
ResultsFindings will be presented comparing the educational attainment for AMO individuals with matched individuals within Non-AMO and non-farming rural households. At the household level, we calculated the highest level of education attained within each household and will present results comparing the highest household level of education between each group. We will present detailed results regarding the structure and educational attainment within these households. 
Full results and findings will be presented at the conference but are currently subject to information governance restrictions.
ConclusionOne indicator of resilience amongst farmers and farm households is ability to respond to economic and non-economic pressures by adopting new practices and techniques or reducing reliance on farming via diversification or off-farm employment. As educational attainment is closely correlated to acquisition of skills and is a gateway to employment, understanding relative and absolute levels of attainment is important in identifying need and devising policies which support agricultural and rural communities.
Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies.
Authors: Stannard Sebastian , Berrington Ann , Fraser Simon , Paranjothy Shantini , Hoyle Rebecca , Owen Rhiannon , Akbari Ashley , Shiranirad Mozhdeh , Chiovoloni Roberta , Alwan Nisreen
Published: September 2024

ObjectivesMany studies use a reductionist approach to isolate the influence of one factor in childhood on multimorbidity rather than consider the combined effect of wider determinants. We aimed to explore how potential multiple early-life determinants of multimorbidity can be audited and characterised across three UK cohort studies.
ApproachWe used the 1958 National Child Development Study (NCDS), the 1970 British Cohort Study (BCS70), and the Aberdeen Children of the 1950s Study (ACONF) to identify and categorise early-life variables that fit into 12 previously conceptualised domains of early-life determinants of multimorbidity. A data audit manually assigned variables into the domain they best represented. Principal component analysis (PCA) reduced the dimensionality of the data and structured variables into subgroups. Important PCA components defined as the component that contributed the greatest proportion of the overall variance were identified. 
ResultsSeven domains were characterised by 74 variables in ACONF, ten domains by 143 variables in the NCDS, and twelve domains by 289 variables in the BCS70. PCA analysis reduced the dimensionality of ACONF variables from 74 to 41, from 143 to 73 in the NCDS, and from 289 to 149 in the BCS70. Important PCA components included maternal fertility histories, long-term illnesses, educational ability, ethnicity, housing status and parental-child interactions. 
Conclusions and ImplicationsConceptualising the risk of future multimorbidity as lifecourse domains composed of multiple factors can help challenge the existing understanding of disease aetiology and inform strategies for the prevention of multimorbidity.
Understanding the developmental well-being of children from refugee backgrounds in British Columbia, Canada: A population-level mixed methods approach
Authors: Gadermann Anne , Guhn Martin , Poon Brenda , Janus Magdalena , Edwards Benjamin
Published: September 2024

Objectives and ApproachThis study utilized an explanatory sequential mixed methods approach to investigate the developmental well-being of children from refugee backgrounds in British Columbia (BC), Canada. Objective 1 (quantitative) leveraged population-level, government administrative data individually linked to a province-wide, routinely collected, teacher-reported measure of children’s development in kindergarten (the Early Development Instrument; EDI) to examine developmental outcomes across five domains for children identified as first-generation refugees (N=770), first-generation immigrants (N=7875), and non-migrants (N=199,186). In Objective 2 (qualitative), the population-level EDI results were brought to focus groups with BC educators and settlement workers (N=7) who work closely with children from refugee backgrounds to further corroborate, expand, and elaborate on the findings.
ResultsA series of multiple linear regression models; adjusted for age, sex, and English Language Learner status showed that first-generation refugee status was significantly predictive of lower EDI scores in the areas of language & cognitive development, communication & generation knowledge, social competence, emotional maturity, and physical health & well-being. Focus group results corroborated the quantitative findings, added critical complexity/context (e.g., impacts of trauma), and identified important policy-oriented levers (e.g., early, accessible assessments and supports).
ConclusionsThe study provided an understanding of the population-level developmental well-being of children from refugee backgrounds in BC, framed by rich, contextualized, and actionable knowledge from focus groups.
ImplicationsShowcasing the combined breadth and depth of using a mixed methods approach, how we can best support the developmental challenges and build upon the strengths of children from refugee backgrounds will be discussed.
Special educational needs provision in primary education and its impact on unauthorised absence in children born with Cleft Lip and Palate: a population level study using linked health and education data
Authors: Nguyen Vincent , Lewis Kate , Dearden Lorraine , De Stavola Bianca
Published: September 2024

IntroductionWithout accounting for the underlying need for Special Educational Needs (SEN) provision, pupils with SEN in England have been shown to have higher rates of unauthorised absences.  
Objectives and ApproachOur objective was to understand the impact of SEN provision on unauthorised absences in children with an expected need for SEN, those born with Cleft Lip and/or Palate. We used linked health and educational records to investigate the relationship between three categories of SEN provision (No Provision versus SEN Support versus Education and Healthcare Plan (EHCP)) and unauthorised absences.  We aimed to causally estimate the incident rate ratio (IRR) of SEN Support vs No Provision and EHCP vs SEN support on unauthorised absences between years one and six of primary education. Combining sociodemographic, educational and clinical variables from linked data, we used propensity-score based methods to adjust for non-randomised assignment to these categories of treatment. 
ConclusionsBetween academic years 2009 to 2019, we found common support between comparison groups No provision (n = 4350) and SEN support (n = 2009) only for children with Cleft lip and palate and only reported on these comparisons.  Unadjusted estimates demonstrate a 22% increase in absences in children with SEN support over No Support (IRR: 1.22 95%CI: 1.10-1.34). Reweighting for need using data from linked health and education records demonstrated a 14% reduction in unauthorised absences (IRR: 0.86 95%CI: 0.76-0.97). 
ImplicationContrary to prior findings, by carefully matching on detailed linked health and education characteristics, we find SEN provision reduces unauthorised absences
Federated Data Linkage in Practice
Authors: Edwards Michael , Lee Alexandra , Thompson Simon
Published: September 2024

In recent years, great strides have been made towards the deployment of federated systems for data research, including exploring federated trusted research environments (TREs). These federated TREs allow data analysts to securely use data within multiple institutions with minimal overheads while preserving information governance. However, due to the sensitive nature of data utilised in data linkage pipelines, especially within privacy-preserving applications, the real-world deployment of federated data linkage is in its early stages.  
There are several challenges to overcome with privacy-preserving federated linkage, including securely and efficiently sharing information that enables the identification of record similarities. Another key consideration is the resilience of the federated linkage ecosystem to information being added or removed as data providers move in and out of the initiative, as changes in the record set can cause intermediary links to be destroyed or created. Within non-federated linkage, a spine dataset such as a national census can provide an anchor on which incoming datasets can be linked. In federated linkage this may not explicitly be the case, especially if providers are globally dispersed or such a broad spine does not exist for the use case, and so there may be critical datasets within the overall system.
We present a discussion over the real-world challenges to federated linkage on population-scale applications, including approaches which allow privacy-preserving linkage across multiple TREs and handling information governance requirements. We also explore the impact of the collaborative nature of federated linkage, looking at how quality and record links are affected in practice.
Improving and re-developing the Clerical Resolution Online Widget (CROW): open-source software for clerical review
Authors: O'Dair Hannah , Cummins Sarah , Ashia Ira , Huck Rachel
Published: September 2024

ObjectivesClerical review is an integral part of linkage and is fundamental to quality assurance. CROW is a low dependency, adaptable, clerical matching tool that has been deployed across 40 linkage projects. Due to limitations of the interface, with the initial version (including the limited ability to view large clusters); this project sought to re-develop the tool as a flask application.  
ApproachOur approach was to transform the existing CROW desktop application into a Flask (web based) application. Flask was chosen because it is a flexible web framework that enabled the development of a more dynamic interface, as well as better integration with the infrastructure of secure environments. We also engaged with accessibility experts to ensure the inclusivity of our product. Once the development was completed, testing was carried out by a range of users and stakeholders, to identify further issues and bugs for resolution.  
ResultsThe successful redevelopment of CROW into a Flask application improved functionality, usability, parametrisation, and accessibility of the tool. Feedback from users indicates that because of using CROW, the clerical matching experience has improved vastly. Users reported that CROW increased accessibility, reducing eye strain and fatigue. CROW also increases efficiency and leads to better decision making.  
ConclusionThe successful redevelopment of CROW is a significant improvement to the clerical review process for data linkage projects.   
ImplicationsCROW is open-source and low dependency so could be adapted to work in most environments. Therefore, it could be adapted and used by the wider data linkage community.
Looking beyond the neonatal: what does administrative data tell us about the preschool health and developmental outcomes of children exposed to opioids in utero?
Authors: Marryat Louise , Robertson-Albertyn Senga , Boardman James P , McFadden Alison , Whittaker Anne
Published: September 2024

BackgroundThe world is facing an opioid epidemic. Children of women who use opioids in pregnancy are difficult to follow-up over long periods using traditional research methods due to the complexity of their lives. Resultingly, we have little robust evidence on their longer-term outcomes. 
ObjectiveThis study aimed to explore the impact of illicit and prescription opioid exposure in pregnancy on preschool health and developmental outcomes. 
ApproachData identified 6,408 children (born 2009-2019 in Scotland) exposed to opioids through illicit use and/or medication assisted treatment  (MAT), alongside a matched control group (n.19,089). Regression models will examine associations between opioid exposure and key outcomes up to age 5, including the Ages and Stages Questionnaire, accidents and injuries, and chronic health conditions such as asthma, controlling for other risk factors (e.g. alcohol use in pregnancy, gestation).
ResultsEarly results indicated differences in neonatal outcomes, with poorer outcomes for the illicit opioid/MAT cohort in terms of being born early, having lower birthweight, length and head circumference, and being more likely to be removed from their mother prior hospital discharge. Modelling of preschool outcomes is underway and will be finished in June 2024.
ConclusionsHaving proven that we can identify these children in administrative data, this paper will present cutting-edge data on the impact of exposure to illicit and prescription opioids on preschool outcomes. This will provide robust evidence on these impacts, and highlight where additional support might be required for these children from birth to starting school.
Associations between household overcrowding and adult mental illness in an ethnically diverse urban population: cross-sectional study using linked primary care and housing records.
Authors: Wilk Marta , Firman Nicola , Harper Gill , Fry Rich , Griffiths Lucy , Mathur Rohini , Dezateux Carol
Published: September 2024

ObjectiveWe hypothesised that adults living in overcrowded households were more likely to be diagnosed with Serious Mental Illness (SMI) or depression after accounting for individual, household and area-level factors. 
ApproachWe linked primary care records of adults currently registered with all general practices in the north-east London region on 21/03/2021 to housing data using pseudonymised unique property reference numbers (pUPRNs), giving a sample of 762,718 adults in 329,948 households. Primary outcomes were a primary care diagnosis of SMI or depression. Overcrowding was defined as <32.5m2 per person. We estimated the adjusted odds (aOR) and 95% confidence intervals (CI) of SMI or depression when living in an overcrowded household, adjusting for individual (age, sex, ethnic group), household (size, composition), and area (Index of Multiple Deprivation) characteristics. We conducted logistic regression models with robust standard errors in RStudio.
ResultsSMI and depression were diagnosed in 6,492 (0.9%) and 45,053 (5.9%) adults respectively;  584,515 (76.6%) adults lived in overcrowded households.  In univariable analyses, household overcrowding was inversely related to risk of SMI or depression (aOR[CI]: 0.42 [0.39,0.44]; 0.62 [0.61,0.64]). The direction of effect reversed on adjustment for household size, composition, and area-level deprivation: 1.22 [1.12,1.33]; 1.07 [1.04,1.10] for SMI and depression respectively.  
ConclusionsWe found significant associations between SMI and depression and household overcrowding, using a novel method of record linkage to estimate household overcrowding but are not able to establish causality of observed associations in this cross-sectional study.   
ImplicationsMore research is needed to understand how housing conditions affect mental health.
OmniMatch: A Large Language Model-Based Data Linkage Tool
Authors: Xu Xiaowei , Wang Xingqiao , Gunasekaran Vivek , White Jonathan , Mathur Anup
Published: September 2024

Large Language Models, such as OpenAI’s GPT, have demonstrated remarkable success in various applications by generating human-like text. However, a critical question remains: how can we effectively leverage these large language models for data linkage? In response to this challenge, we introduce OmniMatch, a novel data linkage tool designed to address several key issues in data linkage:

Cross-Domain Data Linkage: OmniMatch tackles the complexities of linking data across different domains without retraining or update.
Cross-Lingual Data Linkage: It extends its capabilities to handle data in multiple languages and hybrid languages.
Data Quality Challenges: OmniMatch addresses inconsistent data formats and typical data quality issues, including noise, missing values, typos, and errors.

Our approach customizes an open-source large language model called Llama 2 from Meta. By doing so, we achieve outstanding performance in handling the aforementioned challenges. Notably, OmniMatch offers a specific advantage: it can be installed on-premises, ensuring a safe and trustworthy application without the hallucinations and other vulnerabilities associated with foundational large language models.
We systematically evaluate OmniMatch using diverse datasets from various domains, including products, scientific publications, music, census data, and cross-lingual data. The experimental results demonstrate that OmniMatch is a universally applicable and trustworthy tool for data linkage.
Self-reported Ethnicity Changes over Time: A Population Level Study using Public Voter Databases
Authors: Ziyad Sumayya , Lam Joseph , Christen Peter , Schnell Rainer , Nanayakkara Charini
Published: September 2024

ObjectivesAdministrative databases such as voter registries contain a wealth of information about a large proportion of a population. This is especially true when longitudinal information about individuals is available, such as changes in their names, addresses, or self-reported ethnic attributes. Apparent changes in ethnic attributes might be due to perceptions of majority evaluations of ethnic groups. In this project, we analysed snapshots of a publicly available US voter database from 2015 to 2022, exploring if and how recent presidential elections impacted changes in voters' self-reported ethnic attributes.
 ApproachUsing bi-monthly snapshots of a publicly available US voter database from 2015 to 2022, we generated cohorts by linking active voters during seven twelve-month periods (2015/16 to 2021/22). These seven time periods included one mid-term and two presidential elections, and four control time spans before, between, and after these elections. We compared changes in self-reported ethnic attributes of voters during the times of elections versus the control time periods.
ResultsPreliminary results reveal a substantial change to self-reported ethnic attributes during the periods leading to an election. A majority of such changes are by individuals from a specific ethnic group choosing not to report an ethnicity, an indication of their preference to not disclose ethnicity-related sensitive information.
 ConclusionsWe have shown how a publicly available voter database can be used to explore how self-reported ethnic attributes are modified by individual voters over time, and how the prevalence of such changes is influenced by political events such as presidential elections.
Towards a "Biography" of Population Health Data about Substance Use Disorders: Qualitative Approaches to Communicating Context
Authors: Morgan Jeffrey , Nolan Seonaid , Shoveller Jeannie , McGrail Kim
Published: September 2024

BackgroundUnderstanding contexts of data production is necessary for using data accurately and ethically. “Biographies of data"" have developed as a complement to existing metadata as a way to critically examine and communicate social structures and power dynamics encoded in data. This project is focused on developing a “biography” of diagnostic codes, used to identify substance use disorders (SUD) in population health datasets. People with SUD regularly experience stigma and exclusion, particularly from healthcare settings.
MethodsQualitative semi-structured interviews were conducted in 2024 with ""producers"" and “managers” of administrative data, including physicians and health information professionals, in British Columbia, Canada. The interviews explored processes involved with coding and billing, and the meaning of diagnostic codes from the perspective of those involved. This includes considerations of the population, social, and geographic factors, and implications of coding as inputs to decision-making. Reflexive thematic analysis was used to identify broad themes and report findings.
ResultsAlthough data collection and analysis is ongoing, emerging findings have revealed structural, institutional, and social-level processes that influence coding decisions, as well as potential implications on research, policy making, and knowledge production about SUD.
ConclusionAddressing the complexities of SUD and the overdose crisis will require a variety of data sources and approaches, and linked population health and administrative data will continue to be one important resource. Through better understanding the contexts and processes that inform the production and management of SUD-related population data, we will shed light on the ethical and social implications of their use.
Multiple risks for children of incarcerated mothers: A descriptive study
Authors: Bell Megan , Dawe Sharon , Segal Leonie , Spittal Matthew , Dennison Susan , Kinner Stuart , Preen David , Sims Scott
Published: September 2024

Objectives and ApproachSurvey data suggests that children of incarcerated mothers are exposed to a range of risk factors that can have negative impacts on life-course outcomes. This retrospective cohort study uses a population sample to describe the extent and mix of risk factors to which children of incarcerated mothers are exposed. Administrative data from health, justice, child protective services, births, and deaths were merged for 9,380 children exposed to maternal incarceration and an unexposed comparison group of 22,716 children. Risk ratios and 95% confidence intervals were calculated for birth complications and adverse childhood experiences (ACEs) for children exposed to maternal incarceration compared to those not exposed, adjusted for sociodemographic risk factors. A multiple risk score summed the number of recorded risk factors (0-17) for children with and without maternal incarceration exposure.
ResultsCompared to unexposed children, children of incarcerated mothers had a higher risk of preterm birth, low birthweight, and all ACEs, including a 15-times (95%CI 14.2, 16.3) higher risk of exposure to maternal substance use disorders and 18-times (95%CI 16.8, 20.7) higher risk of placement in out-of-home care. Only 1% of children of incarcerated mothers did not experience any of the included risk factors, compared to 26% of unexposed children (p<0.001).
ConclusionsChildren of incarcerated mothers disproportionately experience multiple risks, especially maltreatment, placement in out-of-home care, and maternal substance use.
ImplicationsThere is a significant public health opportunity to identify and address the needs of children of incarcerated mothers at the points of maternal arrest, sentencing, and incarceration.