bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking Data in a Shared Service Environment
Authors: Mirel Lisa , Goldent Cordell , Zybrick Rob , Wang Rui , Tadler Chrystine , Cox Christine
Published: September 2024

Many federal agencies in the U.S. have begun exploring the use of privacy enhancing technologies, such as privacy preserving record linkage (PPRL), to integrate data from disparate sources to support evidence building and high-quality research. Recent legislation, including the Foundations for Evidence-Based Policymaking Act of 2018 and the CHIPS and Science Act of 2022, and recommendations from the Advisory Committee on Data for Evidence Building support the establishment of a shared service environment, namely the National Secure Data Service (NSDS), to facilitate this work. This talk will provide an overview of two NSDS Demonstration projects that utilize PPRL to integrate data covered by different legal provisions. The first project aims to link data between two federal statistical agencies and the objective of the second is to link data from a federal statistical agency and its parent agency. The talk will focus on the development of the required data sharing agreements, legal provisions that needed to be considered, security and privacy measures that had to be addressed, the software and IT infrastructure required, and the distinct PPRL tools utilized for each project. The talk will conclude with a presentation of preliminary linkage results, lessons learned, and a summary of how these projects will inform potential future data sharing efforts between and within agencies through the establishment of a future NSDS.
A governance framework for facilitating cross-agency data sharing
Authors: O'Sullivan Katherine , Lumsden Joanne , Anderson Caroline , Black Corri , Ball William , Wilde Katie
Published: September 2024

Linking data across local authorities and health boards has the potential to reduce inequalities and improve outcomes. However, cross-agency data sharing leads to complexities around data ownership, legal conditions for processing, organisational controls and risk assessments to ensure privacy and confidentiality of subjects whilst facilitating research and service improvements. We share a governance framework for cross-agency data sharing between a local authority and regional health board in Scotland.
A cross-sector Child Neglect working group was established with representation from public sector agencies, the NHS, University researchers and a Trusted Research Environment to support research on children’s mental health prescribing and secondary specialist services provision and linking to the Aberdeen City Council Child Protection Register. Lessons learned were captured throughout the governance, data transfer and data linkage phases.
Communication is the most important driver, with key individuals, deputies and routes of escalation agreed and involved throughout for clarity of roles and expectation setting. Key lessons learned include requiring input from all parties at the project initiation stage, particularly IG teams, including agreements on necessary templates. Knowledge exchange is required between the research team, data owners and data processors to ensure research protocol requirements are correctly understood and data transfer is supported. If possible, internal and/or external validation of data should also be performed before data is linked. 
Cross-agency data sharing is a vital means to understanding and improving outcomes for individuals and populations. Critical to this is establishing an action plan and formalised project process to achieve outcomes.
Healthcare use among people using methamphetamine in Winnipeg, Canada
Authors: Enns Jennifer , Sarkar Joykrishna , Nickel Nathan , Freier Amy , Shimmin Carolyn , Sherzoi Ogai , Goss Aaron , McDougall Chelsey
Published: September 2024

ObjectiveWe examined healthcare use among people using methamphetamine who were connected to a Community Health Centre (CHC) in Winnipeg, Canada. CHCs are primary care clinics designed to provide person-centred, holistic care to people who may be impacted by discrimination and/or oppression.
ApproachFrom population-based administrative health data, we identified people with a record of a methamphetamine-related healthcare system encounter from 2013-2020 (cases) and created a comparison group matched on age, sex, and postal code but with no recorded history of using methamphetamine (controls). We narrowed this population to those who visited a CHC at least once. Then, using negative binomial regression models adjusted for sociodemographic characteristics, we produced rate ratios and 95% confidence intervals for primary care visits, CHC visits, emergency service contacts, emergency department (ED) visits, and hospitalizations in the 5 years after the first recorded methamphetamine use.
ResultsAdjusted rate ratios showed that healthcare use among CHC-connected people using methamphetamine was higher than among CHC-connected people not using methamphetamine: primary care 1.15 (95% CI 1.07-1.23); CHC 1.17 (95% CI 1.01-1.37); emergency services 6.19 (95% CI 5.46-7.02); ED 3.19 (95% CI 2.92-3.48); hospitalization 2.77 (95% CI 2.46-3.10).
Conclusion & ImplicationsBeing connected to a CHC may have facilitated access to other health and social services, but there is still unmet need for high quality, holistic care among people using methamphetamine. This research informs our team’s ongoing efforts to address mental health and addictions concerns across sectors and to promote anti-discriminatory approaches to addictions care in the healthcare system.
Maternal And preGnancy hEalth duriNg elevaTed heAt – MAGENTA: Novel data linkages and methods to understand the impacts of climate change on deprived communities in Wales and London.
Authors: Fry Rich , Owen Rhiannon , Turner Samantha , Mizen Amy , Griffiths Lucy , Hardelid Pia , Thornton Cathy
Published: September 2024

Background and ObjectivesThe health impacts from changing climate, including increasing frequency, severity, and duration of heat are projected to worsen. The MAGENTA study will explore the impact of heat on pregnancy-related outcomes for deprived communities in Wales and London.
ApproachMAGENTA will create linked data cohorts capturing some of the most deprived and diverse communities in Europe to analyse the impact deprivation, ethnicity, heatwaves, and urban heat islands have on pregnancy-related health. A consented data-linked cohort of pregnant women will provide biological samples and undergo direct measurement of themselves and their home environments to understand the heat stress response of pregnant women not acclimatised to heat during their pregnancy. Core to the study is our public involvement strategy which includes pregnant women and women who have recently delivered a baby, co-producing the research and how results are communicated.
ResultsOur electronic cohorts cover >10 years of climate and health data and capture all births in Wales >300,000 and >1.1 million in London.  We will present how the novel data linkages can work in multiple trusted research environments, approaches for sharing methods in geospatial modelling and statistics across the project and preliminary findings from the study.
Findings and ImplicationsThe MAGENTA study will help inform expectant parents, families and policy makers how to prepare for climate change in temperate regions. The comparison between different populations in Wales and London will give insight on where policies and interventions can be generally applied and where they need to be contextually adapted.
Wastewater-Based Surveillance of Substances of Potential Abuse
Authors: Southern Danielle , Ghosh Monty , Harmon Megan , Kuzma Darina , Kormendi Aleshia , Moffett Kayla , Westlund Paul , Hubert Casey , Parkins Michael , Williamson Tyler
Published: September 2024

ObjectiveAmid a drug poisoning epidemic, UCalgary adapted its comprehensive wastewater monitoring program to track illicit drug use. The joint initiative between the academic community and Alberta municipalities aims to provide early warning information on changes in the drug supply to healthcare workers, policymakers, and people with substance use disorders (pwSUD).  
ApproachThe logistic network, first used for SARS-CoV-2 monitoring, has evolved to track 48 substances linked to substance use. These include the parent drugs (e.g., cocaine, methamphetamines, various opiates) and their metabolites. The comprehensive nature of this tracking provides a nuanced understanding of trends. Collected up to 3X-weekly across various locations in Alberta including municipal wastewater treatment plants, entire neighbourhoods, and shelters, the data reveals geographical and temporal patterns in substance use. Findings were cross validated with Alberta’s substance use surveillance system to predict trends in wastewater, correlating with emergency and inpatient admissions and overdose deaths. 
ResultsThe research uncovered noteworthy trends. Intermittent, alarming, spikes in carfentanyl, benzodiazepines, and xylazine in wastewater were observed during periods of elevated Emergency Medical Services (EMS) responses to opioid-related incidents in the year 2023. This correlation underscores the real-world impact of the identified substance trends, emphasizing the urgency for targeted interventions to address the escalating opioid crisis. Further work to create a dashboard with additional data sources has begun. 
ConclusionsTimely data on the dynamic drug supply is crucial in addressing the ongoing drug poisoning crisis. The team is exploring ways to share information with emergency responders, healthcare providers, government officials, and pwSUD.
Healthcare costs at the end-of-life among immigrant and non-immigrant groups in Manitoba, Canada
Authors: Debbarman Shantanu , Witt Julia , Oguzoglu Umut , Urquia Marcelo L.
Published: September 2024

ObjectivesIt is known that healthcare costs tend to increase during the last year of life. Recognizing the importance of efficient resource distribution for end-of-life care, this study compares healthcare costs incurred for migrants and long-term Manitobans and identifies the factors that impact healthcare costs during the last year of life.     
MethodsThis retrospective matched-cohort study used 15 databases linked at the individual-level, including immigration records, medical claims, hospital abstracts, drug prescriptions, emergency department visits, home care, long-term care, vital statistics mortality, housing and employment/income assistance, for those who died between January 2005 and December 2022 in Manitoba. Conditional zero-inflated gamma hurdle (ZIG) and quantile regression models were used.    
ResultsThe average end-of-life healthcare costs for international migrants (2469) and Long-term Manitobans (2362) were CA$44,909 and CA$16,593, respectively. According to the adjusted ZIG model, international migrants had 17% higher costs. Among international migrants, Government Assisted and Blended Visa Office-Referred Refugees (GAR/BVOR) had 36% higher costs than Long-term Manitobans. Additionally, costs were higher for those without a partner (13%), receiving employment/income assistance (30%), having higher comorbidity (309% for 4+ comorbidities vs. 0 comorbidities), death at the hospital (171%), and long-term care (169%). Adjusted Quantile regression analyses revealed that only GAR/BVOR had higher costs across all levels of the cost distribution than long-term Manitobans.  
ConclusionIn the last year of life, international migrants incurred greater healthcare costs than non-immigrants. However, the differences with non-immigrants varied depending on international migrants’ characteristics.
Co-creating a Data Asset Inventory for Equity-Oriented Research
Authors: Stirling Morgan , Freier Amy , Nickel Nathan
Published: September 2024

BackgroundData asset inventories (DAI) are invaluable resources providing high-level information about datasets, including name, region, purpose, scope, and contents. An effective DAI improves understanding about what data exists, how they can be used, and where they may be limited. Strategies for integrating principles of inclusion, diversity, equity, and accessibility (IDEA) into DAIs are not widely available, which inhibits efforts to improve existing data infrastructure’s capacity for equity-oriented research.
ApproachHealth Data Research Network Canada (HDRN) is a pan-Canadian network that works collaboratively to enable innovative multi-regional research that can improve health and health equity. Central to HDRN’s mandate is strengthening researcher capacity to apply IDEA principles within their research. Within this scope of work, we convened a multi-disciplinary team of computer scientists, data experts, and IDEA specialists to build a DAI of Canadian health and social data using de-stigmatizing language. Through discussion the team identified key data categories and co-created definitions. Data sets were annotated accordingly.
ResultsDiscussions highlighted disciplinary differences in understandings of IDEA and its relevance to DAIs. Overcoming these differences required IDEA specialists to be both subject matter experts and advocates. Project delays occurred due to the additional time needed for education. Productive conflict resulted in consensus-building to establish respectful and inclusive terms to describe data.
DiscussionEmbedding IDEA within health data infrastructure requires a lens that may not be associated with one’s training. Developing that lens within a project is possible but requires additional time and effort. These components must be factored into project planning.
Individual, household, and socio-economic predictors of COVID-19 testing and vaccination outcomes: a whole population linked data analysis
Authors: Satherley Nicole , Sporle Andrew
Published: September 2024

ObjectiveThe COVID-19 pandemic has exposed numerous social inequities in health outcomes across nations, despite early warnings of their potential. Poorer outcomes for ethnic minorities, and to a lesser extent Indigenous peoples, have been widely reported, and may be explained in part by household conditions and poorer socio-economic circumstances. This study aimed to identify the effects of diverse individual and social conditions on COVID-19 outcomes within the New Zealand population.
MethodWe conducted a whole population analysis of the association between individual (e.g. ethnicity, disability status), household (e.g. household composition), and socio-economic (e.g. crowding, housing quality, income) factors and four COVID-19 health outcomes – infection, hospitalisation, mortality, and vaccination status. We constructed variables of interest from linked administrative data in New Zealand’s Integrated Data Infrastructure, and examined associations within the 2018 Census usually resident population (analysis Ns = 518,571 - 3,216,696).
ResultsAnalyses showed that Māori (the Indigenous people of New Zealand) and Pacific peoples, an ethnic minority, experienced worse outcomes than other New Zealanders across all COVID-19 outcomes. These ethnic group differences were persistent, yet reduced, when accounting for household and socio-economic variables. Factors including disability status, high housing mobility, poor quality housing, and household crowding were also widely predictive of worse outcomes.
ConclusionEthnic inequity in a range of COVID-19 outcomes is present in a country where the overall impacts of the pandemic were relatively limited. Individual, household, and socio-economic factors are associated with diverse COVID-19 outcomes, and policy amenable factors may help explain the presence of ethnic inequities.
Early life child protection contacts and developmental risk at age five: a whole-of-population cohort study of 479,413 children in two Australian states.
Authors: Falster Kathleen , Pilkington Rhiannon , Ahmed Tasnia , Montgomerie Alicia , Hanly Mark , Newton BJ , Brownell Marni , Edwards Ben , Lingam Raghu , Shakeshaft Anthony , Cretikos Michelle , Stewart Jessica , Hawkins Katherine , McLean Kitty , Lynch John
Published: September 2024

IntroductionChildren who experience maltreatment have worse health and development outcomes than other children. Early prevention relies on opportunities to respond to system contacts that reliably indicate the population burden of children’s future developmental risk. 
Objectives and ApproachWe quantified the population burden of developmental vulnerability at age five by the type, timing, and frequency of child protection contacts before school, among children in two Australian states. We used linked whole-population births, child protection and Australian Early Development Census (AEDC) data (2009-2018 cycles) in New South Wales (NSW) and South Australia (SA). 
Results56,650/398,702 (14%) NSW and 12,617/80,731 (16%) SA children had ≥1 child protection contacts before school. The risk of developmental vulnerability on ≥1 domains was lowest in the no child protection group (NSW, 17-18%; SA, 19%), with higher risks in the child protection report (NSW, 28-29%; SA, 32-35%) through to the OOHC (NSW, 35-38%; SA, 39-50%) groups, with a similar pattern for the risk of medically diagnosed conditions. Children with only one child protection report before school had a higher developmental risk than the no child protection group (NSW, 34% versus 21%; SA, 42% versus 24%).
Conclusions/ImplicationsEven a single child protection report in the first 2000 days of children’s lives was a robust indicator of developmental risk at age five, with higher developmental risks among children with more serious child protection contacts before school. Child protection reports represent an under-utilised asset to inform early universal and targeted support from health, human and early education services.
Understanding health data social licence: An international comparison of community attitudes towards health data use across Canada and Australia
Authors: Burt Julia , Miller Kate , Flack Felicity
Published: September 2024

ObjectiveResearch has found general but conditional support for health data being used for public benefit. The term “social licence” describes which uses of health data the public supports and under what conditions. Here, we aim to compare two approaches to understanding community attitudes towards health data use, and how social licence may differ, between Canadian and Australian populations.
ApproachFactors that affect community support for health data use include the specific population, the type(s) of data, and the engagement approach used. In Canada, facilitated dialogues were held to explore whether (i) there were uses of health data that diverse members of the public all supported and (ii) there was consensus on essential requirements for health data social licence.
In Australia, national surveys and citizens’ juries were conducted to better understand (i) attitudes towards private sector data use and (ii) the ethical, legal and social implications of using general practice data in research.
ResultsDespite the different approaches taken, many conditions for social licence were similar across Canadian and Australian participants. Both groups agreed on conditions for health data social licence related to equity, governance, privacy and transparency. However, there was a stark contrast between levels of support for private sector data use, personal control and consent.  
ConclusionThis comparative exercise contributes valuable insights into the ongoing dialogue surrounding community attitudes towards health data use. Continued research monitoring health data social licence across populations is imperative for public trust while gaining full benefits from health data use in research.
Using newly linked hospital and population data to identify opportunities to reduce harms from sedative-hypnotic prescribing at population scale
Authors: Roberts Surain B , Imrit Mohammad A , Ismail Marwa F , Shen Trong , Soong Christine , Liu Barbara , Mak Denise YF , Kushnir Vladyslav , Rosella Laura C , Razak Fahad , Verma Amol A
Published: September 2024

Objective and ApproachSedative-hypnotic medications are associated with harms such as delirium and falls, and may be overprescribed in hospitals. Measuring potentially inappropriate in-hospital sedative-hypnotic prescriptions requires distinguishing new initiations from pre-hospital prescriptions, but pre-hospital medications may not be captured in hospital data. To quantify physician- and hospital-level variation in sedative-hypnotic prescribing, we use linked data between GEMINI (which includes EMR data from >1.8 million admissions across 30 hospitals, approximately 60% of medical inpatient beds in Ontario) and ICES (which houses administrative healthcare databases, including outpatient prescriptions for adults ≥65 years). We will validate whether data in hospital clinical notes or pharmacy records can reliably identify pre-hospital prescriptions.
ResultsUsing provincial health insurance number, 98.1% of GEMINI records could successfully be linked deterministically to ICES. Our exploratory sedative-hypnotic cohort included 90,806 general medicine patients treated by 437 physicians from 17 hospitals across Ontario from 2021-2022. Median age was 72 years and 48.7% were female. The proportion of patients receiving a new sedative-hypnotic prescription varied markedly across hospitals (median 0.21, range 0.04-0.41) and across physicians within hospitals (median within-hospital difference between lowest and highest prescriber: 0.18, range of within-hospital differences 0.07-0.67). Validation of new rather than continued prescriptions is underway. Full results will be ready for presentation at the conference.
ConclusionSedative-hypnotic prescribing is common and highly variable in hospitals across Ontario, indicating an opportunity to improve patient safety.
Implications Based on these analyses, the province of Ontario has made reducing in-hospital sedative-hypnotic prescribing a provincial priority for 2023-2024.
Minor Ailments and Pharmacist Management in Ontario, Canada: Attachment and Primary Care
Authors: Dolovich Lisa , Nguyen Paul , Aziz Yasmin Abdul , Tadrous Mina , Avilla Ernie , Mathers Annalise , Frymire Eliot , Glazier Rick , Premji Kamila , Jaakkimainen Liisa , Kiran Tara , Roberts Lynn , Green Michael E
Published: September 2024

Minor ailments (MA) are health conditions that can be managed with minimal prescribed treatment and/or self-care strategies. In Ontario, Canada, pharmacists were given authority to deliver service for thirteen MAs on January 1, 2023, with an additional six MAs on October 1, 2023. This study aims to identify patterns of MA service provision and describe characteristics of recipients of MA services.
A cross-sectional analysis of linked health administrative data, including pharmacist billing for MA services, patient demographics, and physician and hospital billing data, was conducted. Delivery of MA services prescribed in Ontario from January 1 to December 31, 2023 were analyzed with key demographics (age, sex, income, new arrival status, comorbidity), health care utilization (ED, hospitalization) and primary care attachment.
In 2023, 547,673 (3.6%) Ontario residents received at least one MA service, with the top 5 services being urinary tract infections (199,282), conjunctivitis (153,021), herpes labialis (46,659), allergic rhinitis (41,521), and dermatitis (39,365). Compared to all Ontario residents, the MA service recipients were more likely to be people with a higher rate of ED visits (41.7% vs. 32.4%), comorbidities (17.5% vs. 9.7%), higher incomes (highest income quintile, 23.1% vs. 20.1%; lowest income quintile, 16.5% vs. 19.4%), and hospitalizations (23.6% vs. 17.6%), and less likely to be newcomers to Ontario (8.7% vs. 13.1%). They were more likely to be attached to a primary care provider (91.3% vs. 84.7%).
This study provides insight into early users of this program, and sheds light on those with systemic vulnerabilities and equity deserving groups.
Recommended Minimum Elements for Transparent Reporting of Multi-Jurisdiction Algorithm Feasibility Studies
Authors: Hamm Naomi , Bartholomew Sharon , Zhao Yinshan , Peterson Sandra , Al-Azazi Saeed , McGrail Kimberlyn , Lix Lisa
Published: September 2024

BackgroundResearch and surveillance using routinely collected health data rely on algorithms to ascertain disease cases or health measures. Where algorithm validation studies are not possible due to lack of a reference standard, algorithm feasibility studies can be used to create and assess algorithms for use in more than one population or jurisdiction. Publication of the methods used to conduct feasibility studies is critical for transparency and reproducibility. Existing guidelines applicable to feasibility studies, including the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) and REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statements, may benefit from additional elements to capture aspects particular to multi-jurisdiction algorithm feasibility studies and ensure full reproducibility. 
MethodsA subcommittee of members from Health Data Research Network (HDRN) Canada’s Algorithms and Harmonized Data Working Group (AHD-WG) reviewed items within the STROBE and RECORD guidelines and compared these to published feasibility studies. Items not contained within STROBE or RECORD but recommended to ensure transparent reporting of feasibility studies were identified. The AHD-WG reviewed and approved these additional recommended elements.
ResultsEleven additional recommended elements were identified: one element for the title and abstract, one in the introduction, five in the methods, and four in the results sections. Elements primarily addressed reporting jurisdictional data variabilities, data harmonization methods, and algorithm implementation.
SignificanceImplementation of these recommended elements, alongside the RECORD guidelines, is intended to encourage consistent publication of methods that support reproducibility, as well as increase comparability and international collaborations.
Injury Assessment of Pedestrians, Bicyclists, and Motorcyclists Utilizing Linkage of Police-Reported Crash Data to EMS Data in Michigan
Authors: Bowman Patrick , Flannagan Carol , Leslie Andrew , Spradlin Helen
Published: September 2024

In Michigan, police crash reports are the primary source of data on traffic crashes. Though many aspects are very reliable, some details are difficult to observe or require subjective judgement. Injury severity, which is central to the road safety issue, unfortunately falls into the second category. The KABCO injury scale used by law enforcement classifies injuries as “possible,” “suspected minor,” and “suspected serious” which may not correspond to determinations made by medical professionals. EMS records can provide a means to improve crash injury data using medical evaluations, but these records are not linked to the police reports.
This project explores the linkage of police crash reports and EMS records using both Michigan data sources from 2018 to 2021. Given the association between severity of injuries and person type, three crash subsets with high injury risk were the focus: pedestrians, bicyclists, and motorcyclists. Collectively, these person types represent 25.1% of the police reported fatalities and suspected serious injuries in Michigan in 2022 despite being only 1.2% of the crashing population. 
Person-level records for pedestrians, bicyclists, and motorcyclists were identified and divided into three separate datasets for each data source. EMS data events were restricted cases believed to be associated with traffic crashes using ICD-10 injury codes. Personal identifiers were not provided, so probabilistic linkage was used to link person crash records to EMS records. Event date, location, ambulance ID, and person demographic variables were utilized. Linkage rates and injury severity agreement was computed to assess differences between the two datasets.
Prevalence and characteristics of people with a high body mass index across the kidney disease spectrum: a population-based cohort study
Authors: Sahi Gurleen , Reid Jennifer , Chiu Michael , Moist Louise , Naylor Kyla , Stranges Saverio , Omer Kamel , Vinson Amanda , Madill Janet , Clemens Kristin K
Published: September 2024

The prevalence of obesity is growing globally and has major health implications, particularly for those with chronic kidney disease (CKD). People with obesity have a higher risk of CKD progression and face barriers to transplantation. Studies on the epidemiology and outcomes of obesity in the Canadian CKD population are lacking.
This population-based cohort study included adults aged 18 and over with a hospital encounter in London, Ontario, Canada from 2010 to 2019 where height and weight were recorded. They were stratified into CKD stages 1-5 (by estimated glomerular filtration rate (eGFR)), dialysis or renal transplant status and by body mass index (BMI) using Canada Obesity Guidelines. Outcomes included prevalence of BMIs by CKD stage, and CKD progression and transplant outcomes across BMI classes.
Our cohort included 198,151 patients. The prevalence of BMI ≥30 kg/m2 grew as eGFR declined (i.e., 37% in stage 1, 41.5% in stage 3b, 40.9% in stage 4) but fell in end-stages (i.e., 37.4% in Stage 5, 38.8% in dialysis, 38.5% in transplant recipients). CKD progression and kidney failure appeared more frequent in those with a BMI ≥30 kg/m2. In a smaller sample, we noted that end-stage patients with a BMI ≥30 kg/m2 were less frequently transplanted, but experienced post-transplant complications less often.
This study revealed that high BMI is a prevalent issue in the Canadian CKD population and may influence kidney outcomes and transplant candidacy. This data will help inform clinical trials to create and study weight loss interventions for those with CKD and obesity.
Do children receiving care and support have higher rates of school exclusion than their peers?
Authors: Hodges Helen
Published: September 2024

The Children, Young People and Education Committee recently held an inquiry to scrutinise the Welsh Government’s progress in delivering its Programme for Government Commitment to ‘explore radical reform of current services for children looked after and care leavers’. A key observation highlighted in their report was that there was a lack of robust data collected about various aspects of the care system. Notably it was highlighted that there is a lack of data collected about permanent exclusions and suspensions from school amongst children looked after in out of home care (CLA). This study was therefore designed to fill this evidence gap.
Using anonymised linked administrative data held in SAIL Databank to identify those receiving care and support (CRCS) from their local authority, rates of permanent exclusion and suspension have been determined for the different groups within the CRCS cohort (CLA, those on the child protection register (CPR) and those receiving support who are neither CLA nor CPR) which have then been compared to their peers without this experience. Factors such as phase of education, setting, free school meal entitlement, having additional learning needs, age and gender have also been considered along with the reason for the suspension or exclusion.
In drawing comparisons with peers, an intersectional approach was adopted to identify disparity.  It is hoped that findings from this student study will stimulate debate and contribute towards the development of changes in Welsh policy.
Probabilistic Record Linkage for Families (PRLF): A Discussion of the Development and Validation of this Open-Source Linkage Tool
Authors: Prindle John , Suthar Himal , Putnam-Hornstein Emily , Foust Regan
Published: September 2024

Linking administrative records across programs can yield person-centered information, including client characteristics, public service trajectories, and outcomes and help to answer policy-related questions. Several solutions are available for undertaking record linkage, producing linkage keys for merging data sources for positively matched pairs of records. In this session, we will demonstrate a new application of the Python RecordLinkage package to family-based record linkages with machine learning algorithms for probability scoring, which we call probabilistic record linkage for families (PRLF). First, we will demonstrate the utility of PRLF with a simulation of administrative records and assess linkage accuracy with variations in match rates and data degradation. Second, we will compare generalized linear model estimates across three record linkage solutions (PRLF, ChoiceMaker, and Link Plus). Findings from the simulation study indicate linkage accuracy is largely influenced by degradation (e.g., missing data fields, erroneous or incomplete values) compared to the proportion of simulated matches between datasets. Results from the methods comparison using real world data indicate that all three solutions, when optimized, provide similar results for researchers. We discuss the strengths of our process, such as the use of ensemble methods, to improve match accuracy. We then will identify caveats of record linkage in the context of administrative data. The tool was developed in Python to allow for researchers to work with open-source software and adjust the basic workflow to fit their linkage needs. We will identify several partnerships where this collaboration has worked successfully and empower attendees with access to this useful tool.
Investigating associations between the natural environment and COVID-19
Authors: Thwaites Oliver , Mizen Amy , Lyons Ronan , Owen Rhiannon , Wheeler Benedict , Fry Richard
Published: September 2024

BackgroundThe natural environment offers a plethora of health benefits and may mitigate the risk of contracting SARS-CoV-2. However, they are also sites where interpersonal contact is frequent, amplifying the risk of transmission. Previous research has typically focused on green space or a measure of greenness. Greenness is often associated with fewer COVID-19 infections, whereas associations with green space are mixed. Very few studies have investigated blue spaces. To our knowledge, no studies have investigated associations between greenness, green space, and blue space with COVID-19 for a national population.
Objectives & ApproachWe aimed to investigate the impacts of exposure to the natural environment on the likelihood of testing positive for COVID-19 in small areas across Great Britain. We derived several measures of green space, greenness and blue space using data from Ordnance Survey and the Google Earth Engine. These measures were linked to the COVID-19 Infection Survey in a Trusted Research Environment. We used mixed-effects logistic regression to account for the multiple tests taken by each participant, adding a random effect for participant ID. We fit univariate models for each predictor and multivariate models for each environmental exposure, adjusting for sex, age, ethnicity, household occupancy, rurality, population density and deprivation.
ResultsThe survey contained test results from a random and representative sample of over 500,000 participants. Approximately 11 million tests were taken by the cohort across three years.
Conclusions & Implications The results of this study will inform planning for the next pandemic.
Identifying substance misuse related foetal anomaly cases in routinely collected data
Authors: Farr Ian , Evans Hywel , Ohaeri Columbus , Phillips Ryan , Oluwasuji Olabambo , Dixon Josh , Bailey Grace , Smith Josie
Published: September 2024

ObjectiveFoetal Alcohol Syndrome Disorder (FASD) and substance misuse (SM) related foetal anomalies are among the most severe consequences of SM during pregnancy. These are preventable lifelong developmental disorders that affect children’s health, education, and future prospects. Despite the adverse effects of these disorders, epidemiological research in this population remains challenging due to clinical and administrative underreporting. For the first time, SM-related foetal anomaly prevalence in Wales are reported using linked routine data.
ApproachWe combined birth register data with primary and secondary healthcare records to identify infants diagnosed with SM-related foetal anomaly. To compare, we identified mothers referred for SM treatment during pregnancy. The frequency and type of maternal SM-related healthcare interactions preceding birth (within three years prior) were described.
ConclusionsA novel method to identify SM-related foetal anomaly cases using routinely collected data in Wales is provided. The published code to identify mothers and children exposed to SM-related events can also be reused in future projects. When compared with published estimates, cases of SM-related foetal anomaly derived from primary and secondary care diagnoses in Wales are likely underreported, along with the scale of the harm.
ImplicationsWe highlight an unmet need, by counting mothers who were not in SM treatment but had SM-related health events in Wales before giving birth. By further understanding of the risks of SM on unborn children, this body of work provides insight to develop policy and clinical interventions to help future generations. We advocate introducing a SM foetal anomaly database for the UK.
Collecting and incorporating feedback through user research to provide the right information on data linkage processes needed to conduct research.
Authors: Huck Rachel
Published: September 2024

ObjectiveData linkage is increasingly used to generate research-ready datasets to help inform decision makers. Although use of linked data is increasing and accepted as an efficient way to generate new insights, linkage methods and error can have a significant impact on the subsequent analysis and interpretation of the results. Current linkage services overcome this by spending time explaining the linkage to the user. However, as the service demand increases and a generalised approach adopted, ensuring the information is available and understood is a growing challenge. Providing and presenting the information in an accessible way has therefore become a new problem for the data linkage experts.
ApproachUser researchers are working with groups of non-linkage experts using linked data to collate and understand feedback on:

what information researchers expect.
the information researchers find useful.
how researchers interpret and use the linkage information to inform their analysis.

ResultsFindings to date will be presented by exploring how information should be presented and what information researchers are able to interpret and use as part of their analysis.
Conclusions/ImpactFindings will provide guidance as to the information which should be included with a linkage output and the structure most accessible to the research community using linked data. Therefore, the research will help shape how the data linkage service is structured in the future by ensuring researchers can access information they require to interpret linked data and therefore use it appropriately. Ultimately, the feedback will help deliver data linkage services on a large scale.
Evaluating the potential for multi-generational longitudinal research using U.S. Census data from 1850-2020
Authors: Genadek Katie , Alexander Trent
Published: September 2024

Multiple recent linkage efforts have produced longitudinal individual-level data from the censuses of 1850-1940. In addition, within the Census Bureau’s restricted data program, respondents can be linked anonymously between the censuses of 1940, 2000, 2010, and 2020. Researchers are already using parts of these infrastructures together to conduct long-term inter-generational studies. In this paper we describe the various options for accessing, linking, and conducting research that uses both the historical and modern linked data as a centuries-long panel. We assess the sample sizes, representativeness, and cohort coverage of multigenerational panels created with existing linked census resources over the 1850-2020 period.
Development of International Classification of Diseases crosswalks using text analysis methods.
Authors: Sarkar Joykrishna , Lix Lisa
Published: September 2024

ObjectiveTo evaluate the performance of a natural language processing (NLP) method to develop an automated crosswalk between the 9th and 10th revisions of the International Classification of Diseases (ICD) for diagnosis codes in the Charlson comorbidity index (CCI).
ApproachSBERT, an advanced NLP transformer-based model, was used to produce sentence embeddings, numeric vectors that represent the semantic meaning of text, for the labels (i.e., descriptors) of 932 ICD-10-CA (Canadian Adaptation) codes in the CCI (up to six digits). Sentence embeddings were also produced for all ICD-9-CM (Clinical Modification) code labels (15,145). Cosine similarity scores (CSS) were calculated for all possible pairs of ICD-10-CA and ICD-9-CM code labels. CSSs were classified as equivalent (CSS = 1), high (0.8 ≤ CSS < 1), and low (CSS < 0.8). CSS categories for CCI diagnosis codes were compared to an ICD-9-CM to ICD-10-CA crosswalk file manually created by the Canadian Institute of Health Information.  
ResultsOf the 932 CSSs for ICD-10-CA codes in CCI, 84 (9%) were classified as equivalent, 284 (30.5%) were high, and 564 (60.5%) were low. For ICD-10-CA codes with low CSSs, the median was 0.67 (interquartile range 0.14). 
Conclusions and ImplicationsAn ICD-10-CA to ICD-9-CM crosswalk based on NLP had low accuracy for identifying semantically similar diagnosis code labels. The accuracy of this method might be improved by fine-tuning and training on task-specific data. Evaluation of different text analysis-based models would provide guidance for research involving ICD code labels.
Generation Scotland Teenage Recruitment – Creating, evaluating and evolving a study sign-up process in collaboration with study participants and young people
Authors: Flaig Robin , Robertson Sarah , Wood Alex , Kirby Liz , Tatham Rosie , Sudlow Cathie
Published: September 2024

ObjectivesGeneration Scotland (GS) is a family-based genetic epidemiology study. Initial recruitment was ~24,000 adult volunteers from across Scotland in 2006-11 with consent for medical record linkage and re-contact. In 2022 we began recruiting another 20,000, with consent extended to administrative records, with age range now 12+.
MethodsPeople join the study and complete a questionnaire online, with postal saliva sample collection for DNA. Initially, the consent process required a parent/guardian to join GS, confirm their 12-15 year-old’s capacity for enduring consent and invite their child to join. After launch, parents and young people fed back that the communication and consent methods had a negative effect on the ability of young people to join GS - impacting their autonomy, as they were unable join GS independently of their parents.
ResultsThe GS Team designed a new sign-up process for 12–15 year-olds that allowed the teenager to sign up first and request that their parent agree they have capacity to consent. Creating this process was done in collaboration with the new GS YPAG. This new sign-up process was launched in September 2023. We also enabled sign-up using a mobile phone number instead of an email address.
ConclusionCo-design of GS recruitment with young people and parents has greatly improved the sign-up process, making GS the first UK longitudinal study where people aged 12-15 can provide enduring consent online with parental confirmation of their capacity. This provides young people with greater ownership over their ability to take part in health research.
Improving reproducibility and validity in measures of chronic disease incidence using large-scale linked data in Australia.
Authors: Mallitt Kylie-Ann , Stephens Jacqueline , Dal Grande Eleonora , Hiyare Amandi , Dickson Michelle , Jaure Allison , Craig Jonathan
Published: September 2024

Objective and ApproachOur study aimed to improve methods for identifying incident chronic kidney disease (CKD), cardiovascular disease (CVD), and diabetes in a young cohort from the Antecedents of Renal Disease in Aboriginal Children (ARDAC) study. We linked 20 state and federal administrative health datasets, including hospital records, Medicare claims, pharmaceutical data, and the National Diabetes Services Scheme (NDSS) data for the first time. This approach facilitated the development of new algorithms for disease detection. Notably, we will make the R code for these algorithms publicly available. 
ResultsThe analysis, involving 3,758 ARDAC study participants, created clinically robust definitions of CKD, CVD, and diabetes (by subtype) in the Australian linked data context; and revealed that all other data sources inaccurately estimated the incidence of diabetes compared to the NDSS data. 
ConclusionsThis key finding illustrates the discrepancy in diabetes incidence estimates and highlights the value of integrating multiple data sources for the investigation of chronic disease. 
ImplicationsHundreds of published studies use data linkage to investigate CVD, CKD, and diabetes in the Australian context. Our novel robust case definitions, and the identified poor estimation of diabetes incidence among young people, underscores the need to critically evaluate linked data sources used to inform health policy and research. By sharing the developed R code, we support ongoing efforts to improve transparency and replicability in health research. Our study refines chronic disease definition methods and contributes to more effective public health strategies, with particular focus on improving outcomes for Indigenous communities.
Providing data analytic services for national knowledge users in a federated system: learnings from two Canadian use cases
Authors: Duchen Raquel , Mondor Luke , Gatley Jodi , Saskin Refik , Bakal Jeff , McDonald Ted , Knight John , Nickel Nathan , Burchill Charles , Youngson Erik , Magalhaes Sandra , Goosen Andrew , Bowen Sonya , Flaten Lisa , Troke Natalie , Warren Christine , Hsu Zoe , Chen Xueyi , Liu Lihui , Wang Yan , Somayaji Chandy , Shen Linyun , Youssef Simon , Magee Sarah , Dutton Daniel
Published: September 2024

Objective and ApproachCanada’s federated health data system along with access pathways geared toward academic research, pose challenges for knowledge Users (KUs) requiring timely, pan-Canadian evidence to inform decisions. To understand challenges and explore solutions, we conducted two use cases for a pan-Canadian health technology assessment organization and a federal agency, using health administrative data at one federal and six provincial data centres. The population-based cohort studies described socio-demographics, comorbidities, treatment patterns, service utilization and costs. One focused on spinal muscular atrophy, a rare disease and the other on dementia, a complex chronic disease. 
ResultsAdministrative challenges included aligning varied ethical review and data access policies/procedures including requiring local and/or academic principal investigators and differing definitions of “research” vs. planning, evaluation, and monitoring. Data-related challenges included differences in structure, timeliness, and completeness across regions resulting in difficulty aligning constructs such as incident cases and episodes of care. Privacy requirements prohibited pooling jurisdictional estimates resulting in “small cells” that couldn’t be shared with KUs.
ConclusionsWe provided analytic outputs from multiple regions, albeit with some differences and gaps, increasing knowledge around both diseases while developing capacity for combined analyses and gaining insight into national possibilities for data access.
ImplicationsAs decision makers must rely on best available information, some data is better than none.  However, to improve data-analytic services for Pan-Canadian KUs, next steps will include improving data harmonization, expanding data assets and filling data gaps, implementing common data models, and exploring options for federated and/or pooled analyses.