bluuebunny/crossref_metadata_2025 huggingface dataset:
Lived Experience Co-Production Within the Alleviate Pain Data Hub
Authors: Milligan Gordon , Cole Christian , Fisher Judith , Chuter Antony , Beggs Jillian , Smith Blair , Colvin Lesley , Long Susan
Published: September 2024

ObjectiveTo build an effective Pain data hub that benefits the public, people with chronic pain, and researchers.  Alleviate is the Advanced Pain Discovery Platform (APDP) Data Hub. The aim is to make pain data Findable, Accessible, Interoperable, Reusable (FAIR) while raising awareness of chronic pain to improve the lives of people living with pain.
ApproachAlleviate has two lived experience leads plus an Advisory Group (AG) of people with lived experience (PWLE) of chronic pain representing an online reference group of ~400 people. The leads have been involved throughout the project since inception and design, and chair regular project meetings to ensure all voices are heard equally. They lead the development of engagement materials, highlighting the importance of pain research to those with lived experience.
This co-production ensures the project to stay focussed on what matters to those living with chronic pain.
ResultsAlleviate has developed an inclusive environment for PWLE to be actively involved in decision-making and progression of the project. Together we have co-produced videos, static informational material, social media content and developed a new collaboration with an international pain charity to run a UK-wide pain survey.
ConclusionsThis co-production model has allowed us to generate impactful outputs and opportunities, raising awareness of Alleviate and pain research.
ImplicationsProviding an inclusive space in the heart of an academic project for PWLE has given additional focus for researchers and provided ownership to the public in activities that directly affect them.
Using administrative early-years education data to identify children at risk of persistent absenteeism
Authors: Wood Megan , Gunning Lydia , Mon-Williams Mark
Published: September 2024

In a post-pandemic world, school absence is an ever-increasing concern for governments, school leaders, and local authorities worldwide. School absence is associated with poor academic outcomes and long-term illness (physical and mental). Absenteeism increases the risk of financial difficulties in adulthood and involvement in the criminal justice system. As a result, the upstream costs to already overstretched public services are crippling. In England, all children are judged by teachers on their “school readiness” over their first year of formal education. We hypothesised that early childhood problems (i.e., not school ready) might be an antecedent of absenteeism. We tested this by investigating the pre-pandemic association between school readiness and persistent absenteeism using a population-linked dataset. Analyses included 62,598 children aged 5-13 years from the Connected Bradford database (spanning academic years 2012/13-2019/20). Special educational needs (SEN) status, English as an Additional Language status, socioeconomic status, sex, and ethnicity were covariates significantly associated with persistent absenteeism. Children who were not “school ready” had increased odds of being persistently absent later in their education journey after controlling for these covariates. School readiness was associated with even greater odds of being persistently absent over two or more years. These findings show: (i) the potential of using existing administrative data to identify children at risk of disengagement from the education system; (ii) absenteeism reflects stark structural inequities. As the rates of absence is still rising, schools can use these data to flag the children who may benefit from early intervention to keep them engaged in school.
Wastewater-based surveillance for SARS-CoV-2 in Alberta
Authors: Southern Danielle , Hubert Casey , Parkins Michael , Williamson Tyler
Published: September 2024

ObjectiveAlberta's largest research universities collaborated to expand COVID-19 wastewater monitoring throughout the province to regularly provide evidence of SARS-CoV-2 burden in municipalities representing 3.2 million people.   
ApproachSampling was conducted at 26 wastewater treatment plants and facilities across the province. The project quantified SARS-CoV-2 genomic material in wastewater to reveal population-level trends of COVID-19 cases. This inclusive and comprehensive strategy captures everyone who contributes to wastewater, including those not clinically diagnosed. Researchers collected wastewater samples in municipalities three times a week. Additional sentinel monitoring was undertaken in neighbourhoods, hospitals, long-term care facilities, worksites, shelters, and schools. Results were shared on the public COVID Data Tracker website (https://covid-tracker.chi-csm.ca/). Data was additionally linked with hospital outcomes, workforce absenteeism and outbreak information.   
ResultsWastewater-based surveillance (WBS) for SARS-CoV-2 genomic RNA associates very strongly with clinically diagnosed cases and health resource utilization, providing a ≥6-day leading indicator. WBS can effectively be performed across a range of geographic scales (from cities to individual facilities), ensuring actionable data that is relevant to end-users. We have published how outbreaks across a range of high-risk facilities can be monitored and predicted with WBS and can also be used to model COVID-19-associated workforce absenteeism. Emails and website interactions suggested widespread citizen engagement using data for evidence-based decisions. 
ConclusionWBS is a valuable tool for identifying potential outbreaks and tailoring response measures at the policy level and by individual citizens. We've created customizable real-time data-sharing tools catering to both the public (enhanced data transparency) and government (actionable insights).
Race in Integrated Data Systems: Why, Wherefrom, and How
Authors: Steh Stephen , Richter Francisca , Fischer Robert , Ray-Novak Meagan , Henderson Michael
Published: September 2024

Integrated administrative data systems (IADs) are a powerful resource to implement research and analysis for social policy. While IADs may capture racial identity data from multiple administrative sources, there is no agreed upon criteria for whether and how to synthesize this information in a way that (1) produces knowledge to advance racial equity, while (2) underscoring race as a social construct. This study leverages a county-level IAD to test and analyze an event-table design to represent racial identity that, when informed with historical and community knowledge, may meet both of the aforementioned goals.
We illustrate this approach applied to the development of a registry of youth experiencing homelessness, as captured by linked administrative data from vital records, homeless service agencies, schools, food support programs, and other systems. The event table design includes race identity for each person in the registry across all systems included. We develop criteria to inform the hierarchy of one source over another when there are discrepancies in race identity across systems, and when categories for this variable differ across administrative systems. We provide historical and social context behind potential discrepancies and discuss approaches to missing data. Furthermore, we highlight the value of including qualitative knowledge from agency data managers, users, and those represented in the data to inform the synthesis of information around race. Finally, we illustrate how this approach can guide research analysis and contextualize results, thus enhancing the research process and advancing racial equity with IADs.
Pregnant People-Infant Linkage for Surveillance
Authors: Hassan Amro , Hamilton Andrew , Sital Shelly
Published: September 2024

Objectives and ApproachAs maternal mortality and morbidity continue to progress, better data is needed to comprehensively understand the problem, especially in   underserved populations who are differentially impacted. Surveillance in safety-net populations is complicated by care fragmentation  and interoperability challenges between primary care and hospital settings. . AllianceChicago (AC), a health center-controlled network, supports a common data infrastructure across a set of Federally Qualified Health Centers (FQHCs) in Chicago that is further linked to a distributed query infrastructure connecting Chicago’s major health systems known as CAPriCORN.  
Leveraging electronic health record (EHR) data collected by the AC and CAPriCORN consortium, the objective of this surveillance effort was to connect infant data with maternal data while protecting privacy. We developed a deterministic matching algorithm that utilized multiple approaches and technologies for Pregnant People-Infant (PPI) pair identification. The linkage process involved a five-step method in which each step is recorded within the linkage database and the confidence interval is calculated.
ResultsPreliminary analyses are ongoing. Through each step of the linkage process, the confidence interval increased with the increase of matching nodes, highlighting its accumulative accuracy. The result demonstrates the feasibility of linking maternal and baby healthcare characteristics using a range of clinical and demographic variables captured in pseudonymized hospital and ambulatory data.
Conclusions and ImplicationsOur approach improves the capacity of EHR data for surveillance while protecting patient privacy and preserving data confidentiality. Triangulating outcomes recorded in different settings can help improve data quality for research and surveillance.
Patterns of antidepressant use among older adults in Northern Ireland: An administrative data study.
Authors: Redican Enya , McDowell Ronald , Rosato Michael , Murphy Jamie , Leavey Gerard
Published: September 2024

ObjectiveOver recent decades, there has been a noticeable increase in the prescription of antidepressant medications, particularly among older adults. This study examines the relationship between health outcomes and patterns of antidepressant use among older adults in Northern Ireland (NI). 
ApproachParticipants included all (General Practitioner) GP-registered hospital patients aged fifty-five years and above on 01/01/2010 (n =395,872). Administrative data linkage included demographic information (age, sex; urbanicity); data on antidepressant use from the NI Enhanced Prescribing Database (EPD); and hospital patient admissions/discharges. Repeated measures latent class analysis (RMLCA) identified patterns of antidepressant use (2010 to 2020) in relation to the association between these patterns and health-related outcomes in 2021. 
ResultsRMLCA identified four latent classes : long-term antidepressant use (17.4%); decreasing antidepressant use (7.1%); increasing antidepressant use (8.4%); no-antidepressant use (67.1%). Those in the long-term  and increasing antidepressant use’ classes had the highest average number of hospital visits and recorded chronic conditions in 2021. 
ConclusionFindings show that two distinct subgroups (comprising 26% of the hospital population) were disproportionately impacted by increased antidepressant prescription rates. Because of their increased likelihood of experiencing higher ill-health, these people are crucial targets for additional psychosocial support. 
ImplicationsAnalyses of this kind emphasize the importance of widening access to administrative data, enabling researchers to identify and examine at-risk groups allowing more targeted policymaking to better address their needs.
Data for this project was provided by the HSC Honest Broker Service; any views or opinions presented are solely those of the author.
Estimating natural history of a treatment-eligible type 2 diabetes mellitus population in Scotland using linked primary and secondary care data: Scottish Diabetes Research Network - National Diabetes Dataset
Authors: Wei Lili , Butterly Elaine , Hanlon Peter , Haghpanahan Houra , Lindsay Robert , Adler Amanda I , Blackbourn Luke A K , Dias Sofia , Hughes Katherine , McGurnaghan Stuart , Petrie John , Sattar Naveed , Tomlinson Laurie A , Welton Nicky , Wild Sarah , Lewsey Jim , McAllister David
Published: September 2024

Healthcare commissioners and those making reimbursement decisions require data on the “natural history” of diseases to estimate quantities such as life expectancy and quality of life. However, such data are commonly acquired from unrepresentative sources like trial placebo arms or case series. We used Scottish Diabetes Research Network-National Diabetes Dataset to characterise life expectancy for people with type 2 diabetes mellitus (T2DM).
Data from >99% of people with diabetes in Scotland are available from primary and secondary care (including from clinical investigations) and can be linked to hospital admission and death records for research purposes. As part of an MRC-funded (MR/T017112/1) systematic review and modelling study (PROSPERO registration CRD42020184174) building on work funded by the Chief Scientific Office for Scotland (CSO HIPS_17_26), we used these linked data to define a treatment-eligible population for three drug classes — SGLT-2 inhibitors, GLP-1 agonists, and DPP-4 inhibitors. Fitting a Gompertz model, we estimated life expectancy for this ‘treatment-eligible’ group.
The treatment-eligible population, compared to the entire Scottish T2DM population, was younger (63.8 (12.1) vs. 66.7 (12.7) year-old), with larger proportions of men (60.6% vs. 56.2%), higher HbA1c levels (67.4 (13.1) vs. 60.2 (15.1) mmol/L), larger proportions prescribed metformin (69.2% vs 55.2%) and higher life expectancy at age 65 (in women 21 vs 19 years and in men 20 vs 18 years).
Using linked data to define and characterise treatment-eligible populations is feasible and may impact decision models. These findings will be useful to those making resourcing decisions and future economic analyses.
Cardiovascular disease surveillance using electronic medical records: a scoping study
Authors: Riazi Kiarash , Virani Adam , Aujla Eshnaa , Pan Jie , Lee Seungwon , Martin Elliot A. , Quan Hude , Li Na
Published: September 2024

ObjectiveCardiovascular diseases (CVD) are the leading cause of mortality and morbidity worldwide. Traditionally, disease surveillance relies on data from surveys, registries, and administrative databases. As medical records undergo global digitization, electronic medical records (EMRs) are emerging as a crucial reservoir of real-world data. However, the extent EMRs are used in CVD surveillance is unknown. We are conducting a scoping review to assess the current state and effectiveness of EMR-based CVD surveillance worldwide.
ApproachFollowing the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews, we searched MEDLINE and EMBASE bibliographic databases to capture studies on prevalence, incidence, and trend measurements of CVDs using EMRs. Assessed factors include CVD types, modelling methodologies, data linkages, advantages, disadvantages, challenges, and solutions. Due to the qualitative nature of the review, collected data will be narratively synthesized to present overall perspectives.
ResultsOur search algorithm yielded 11,979 citations, of which 5,886 abstracts were selected for screening, in progress at the time of this submission. The interim results indicate that most eligible reports came from the USA (49%), followed by the UK (13%), China (6%), Spain (4%) and Canada (3%). The most common diseases were coronary artery diseases (29%), followed by hypertension (26%), stroke (21%), and heart failure (15%).
ConclusionsSurveillance of CVD is crucial for prevention and health policy development. While EMRs can be a data source for surveillance, such potential has yet to be fully realized.
ImplicationsThis study will inform existing research challenges and future opportunities of EMR-based CVD surveillance.
Understanding the fatal burden of COVID-19 in residential aged care homes in Australia: Using linked data to generate evidence
Authors: Welsh Jennifer , Joshy Grace , Freeman-Robinson Rachel , Biddle Nicholas , Banks Emily , Schlegel Clement , Jordan Kayla , Gould Phillip , Kelly Paul , Korda Rosemary
Published: September 2024

AimTo quantify the impact of the pandemic on fatal burden of disease among those living in residential aged care homes (RACH) in Australia.
MethodsUsing Residential Aged Care data linked to Death Registrations (Jan 2016 to 11 Aug 2022), we estimated years of life lost per person-year (YLL/py) among people living in RACH. Additional linkage of notifications data from the state of Victoria enabled comparisons of average survival times between notified COVID-19 cases and matched non-cases living in RACH using COVID-19.
ResultsCOVID-19 deaths were low in 2020 and 2021 (610 and 260 deaths, respectively) but increased in 2022 (3230 deaths). Years of life lost due to COVID-19 was low in 2020 and 2021 (1.2% and 0.5% of the total YLL/py, respectively) but increased substantially in 2022 (8.3% of the total YLL/py). However, there was little evidence that YLLs/py overall increased in the pandemic (range: 0.87 to 0.93 in 2016-2019 and 0.85 to 0.88 in 2020-2022). Results describing differences in survival between notified COVID-19 cases and non-cases are forthcoming.
ConclusionWe observed no substantial increase in overall fatal burden of disease among the RACH population during the pandemic period. While COVID-19 case numbers increased in 2022 relative to 2020-2021, this was offset with better survival among cases over time, reflecting, at least in part, decreasing disease severity, high uptake of COVID-19 vaccines and antiviral medications.
Evidence from an Applied Health Research Question (AHRQ): Describing Bundled Care Use in Ontario among Individuals with Total Joint Arthroplasty from fiscal year 2018-2021.
Authors: Golding Haley , Churchill Katie , Levy Charissa , Plumptre Lesley
Published: September 2024

ObjectiveTo describe clinical pathways and use of the bundled care funding model, where a patient’s treatment and payment is assigned to a group of providers, among individuals who underwent a total joint arthroplasty (TJA) in Ontario. The request for this work was submitted by the Rehabilitative Care Alliance through the Applied Health Research Question (AHRQ) program. 
ApproachAdults with TJA from April 1st 2018 to March 31st 2022 were included. Demographics, surgical characteristics, inclusion in bundled care, and use of health services were defined using administrative health data. Results were stratified by location of surgery (bilateral or unilateral hip, knee, or shoulder TJA). 
ResultsAmong 152,135 individuals with TJA during the study period, 71,996 individuals (47.3%) received services through a bundled care approach. Rate of bundled care use was highest among individuals with unilateral knee TJA (52.5% in bundled care), and the lowest among individuals with shoulder TJA (13.4% in bundled care). In fiscal year 2018, 33% of TJA patients used bundled care, in fiscal year 2019, over 50% of TJA patients used bundled care and 55% of TJA patients used bundled care by 2021. Most individuals used bundled care following an inpatient surgery (88.9% of individuals following a unilateral knee TJA) as opposed to a same day surgery (11.1% with a unilateral knee TJA).
ConclusionThe purpose of bundled care service delivery is to provide integrated healthcare delivery and therefore improved patient experience and outcomes. Understanding bundled care use may improve healthcare planning and assessment of health services.
A Geospatial Study of Opioid Overdose Risk in Diverse Regions
Authors: Fernando Hashan , Spannaus Adam , Kapadia Anuj
Published: September 2024

Over the past two decades fatalities from opioid overdoses (OD) in the United States have increased at an alarming rate, and there exist regional disparities in the number of opioid fatalities within the US. A comprehensive understanding of the underlying factors contributing to this geographic variation remains elusive however. In this study, we consider the Social Vulnerability Index (SVI) census variables and their influence on opioid overdose within diverse geographic regions, each exhibiting different socio-economic factors. To investigate these disparate outcomes, we use Social Vulnerability Index data from the year 2018 alongside mortality data obtained from the CDC WONDER database.
The factors that contribute to opioid OD fatalities can vary from one region to another due to differences in socio-economic characteristics. To investigate these regional differences, we have chosen a set of variables for each region which are relevant to understanding the opioid OD fatalities in three different geographical regions: the Washington D.C metropolitan area, Wyoming, Tennessee. The impact of each factor on the epidemic's propagation varies between these regions however. To identify patterns in socioeconomic factors driving the opioid crisis, we applied methods from topological data analysis to identify potential correlations between social vulnerability factors and the distribution of drug overdose fatalities. In conclusion, our work highlights the importance of the socio-economic factors in understanding the dynamics of the opioid epidemic.
Data governance for ethical usage of linked routine health data in South Africa: balancing privacy and data sharing.
Authors: Mutemaringa Themba , Boulle Andrew , Tiffin Nicki
Published: September 2024

The ability to collate data of healthcare clients from disparate health information systems in the public health system in the Western Cape province of South Africa presents opportunities for improved healthcare outcomes, but it also necessitates the development of systems to address risks related to the potential for data breach and privacy violations.
Here, we describe the data governance infrastructure for the Provincial Health Data Centre (PHDC) in the Western Cape Province of South Africa, which consolidates person-level health data from various sources to support healthcare management and research. We describe how PHDC data governance protects sensitive health data by ensuring compliance with privacy regulations and legislation, and demonstrate the adoption of key pillars of data governance in order to implement policies and procedures that safeguard patient privacy and promote responsible data use. We review downstream impacts of data collation including improved continuity of care, outbreak detection and research support, and how these may be facilitated within the data governance infrastructure.
The presentation highlights the need to balance the potential benefits of routine health data collation and secondary use with managing the risks to privacy and security for healthcare clients, and describes how this is addressed by the PHDC. Future areas to be considered include adoption of Trusted Research Environments (TRE) and the use of synthetic data, as well as identifying effective ways of enforcing data governance policies and monitoring compliance levels.
Evolving the HDRUK Phenotype Library: Phenotype Creation and Editing
Authors: Thayer Daniel S , Scanlon Jack , Elmessary Muhammad A , Zinnorov Artur , Scanlon Ieuan , Coldea Alex , Davies Hannah , Oliveira Carla , Denaxas Spiros , Jefferson Emily , Hemingway Harry
Published: September 2024

ObjectiveThe HDRUK Phenotype Library (phenotypes.healthdatagateway.org) shares definitions used to measure concepts of interest (such as diagnoses or treatments) within health datasets. It already holds more than 1000 phenotypes, with researchers able to contribute their work via an API. We aimed to create a more user-friendly method of contributing to the Library.
ApproachWe designed a phenotype creation workflow enabling users to create and submit new content via web interface. Goals included clarity and ease of use for a broad range of users.
ResultsA home page shows researchers’ own content. Researchers can create new phenotypes using a web form, entering metadata such as name, authors, description, and publications. Code lists are defined via one or more rules, including search terms or referring to another phenotype, or by CSV upload. Users can make their phenotypes accessible to a research group or to all authenticated users, as well as publish content on the web. Publication requests are reviewed to ensure content is complete and appropriate. Editing, with full history and version control, is also supported.
ConclusionsWe implemented and released the new features. We are currently engaging researchers to get feedback and invite content submission.
ImplicationsThe benefit of tools to support research transparency and repeatability is only realized when they are adopted. We hope that a GUI to support phenotype creation will broaden the Library’s user base help it serve as an enabler of higher-quality, more efficient research across the worldwide health data research community.
Our Data, Our Truths, Our Voice: Reclaiming First Nations Data Sovereignty in Manitoba
Authors: Sinclair Stephanie , Waruk Jillian , Morrisieau Taylor , Cochrane Carla , Saulog Ashley
Published: September 2024

BackgroundIndigenous data sovereignty applies to the collection, ownership, and application of data about Indigenous peoples, lands, and resources. 
ObjectivesTo support and expand Manitoba First Nations (FNs) data sovereignty by strengthening capacity and policies related to the ownership, repatriation, and governance of FNs health data. 
ApproachIn March of 2022, the Chiefs of the 63 First Nations in Manitoba adopted a resolution to mandate FNHSSM to implement the First Nations Data Governance Strategy. FNHSSM Data Sovereignty Team has conducted extensive engagement with FNs (including youth, Knowledge Keepers, urban members, 2SLGBTQIA+ members, health directors, and more) to identify current priorities for data collection, research, policy, and training. Basic analysis was done to determine the frequency with which each theme and sub-theme were discussed. 
ResultsBased on the engagement sessions themes that refer to traditional FNs cultural practices and knowledge represented a major priority for all groups, including the integration of strength-based indicators of wellbeing. Overall, FNs have reinforced the urgent need to exert ownership over community health data under the principles of data sovereignty. The health directors top three themes include: (1) data repatriation, (2) governance, ethics, and privacy and, (3) mental health, substance use, violence and poverty. 
ConclusionsThrough engagement, we have identified data needs (including access, training, policies), data topics (health priorities, traditional practices), and data uses (advocacy, repatriation, research) that are unique to FNs in Manitoba. Our team is working in collaboration with FNs to gain greater control over their data, enhance their data analysis capabilities, and ensure the protection of privacy and culture. 
ImplicationsOperationalizing data sovereignty will support evidence-based decision making, research capacity, governance, and ultimately, self-determination.
Exploring methods for generating synthetic data in Scotland to improve access to public sector data for research
Authors: Grieve Aileen , Cooke O'Dowd Nora
Published: September 2024

Objective and ApproachWe are working to improve the economic, social and environmental wellbeing in Scotland by enabling access to and linkage of public-sector data for research in the public good. Our objective was to examine how synthetic data can support this aim by allowing researchers to test approaches and write code while awaiting the necessary permissions to use the real data. We have explored generating synthetic data from metadata and from actual data. 
ResultsThrough engagement, researchers expressed interest in low fidelity data, which minimises privacy and information governance risks. We have created low fidelity data from information provided by data controllers in publicly-available data dictionaries. We have also created more high-fidelity data based on actual data, using the synthpop tool. We are carrying out further work to engage with data controllers about the level of fidelity that is acceptable to them, as well as the information that needs to be included in the data dictionary to meet this in an automated way, and how we will share datasets with researchers.  A key part of these considerations is the ability to link synthetic datasets and the impact that has on the fidelity of the data.  
Conclusions and ImplicationsWe will share our approaches, the limitations we have found in using metadata to create synthetic data, difficulties encountered in using the synthpop tool, engagement we have had from controllers and researchers, and the proposed way forward for synthetic data in Scotland.
RELEASE: Preliminary results from a novel data-linkage study into mental health and substance use service utilisation by people released from Scottish prisons
Authors: Savinc Jan , Kjellgren Richard , Connell Catriona , Hunt Kate
Published: September 2024

ObjectivesPeople released from prison are at increased risk of dying by suicide, drug overdose, and illnesses related to drugs and alcohol. International literature demonstrates patterns in health service access that imply service accessibility may be insufficient to meet the mental health and substance use needs of this population. This study aims to compare the use of health services for mental health and substance use between people released from Scottish prisons and the general population, using national Scottish data for the first time.
ApproachRetrospective observational cohort study, comparing all individuals released from Scottish Prison in 2015 (n=8,917), and a random general population sample (n=42,455), matched on age, sex, postcode and Scottish Index of Multiple Deprivation (SIMD) deciles. Scottish Prison Service data were linked with community prescriptions, death registrations, inpatient admissions to general and psychiatric hospitals, outpatient contacts, and emergency  care.
ResultsDescriptive summaries of the demographic characteristics of the cohort and bivariate comparisons of service use across different services will be presented, alongside planned approaches using Poisson regression models of service contacts.
ConclusionsThis study advances our understanding of the feasibility of conducting research using national linked data from health and justice services and provides insight into differences in access to mental health and substance use support. 
ImplicationsThis research expands applications of public health approaches and administrative data research in Scotland. It provides crucial evidence to inform interventions that optimise access to appropriate services, to improve the lives of people released from Scottish prisons and to reduce inequalities.
Prevalence of Congenital Anomalies Before and After Implementation of a Novel Wastewater Treatment Technology in Texas: An Augmented Synthetic Control Method Analysis Utilizing Data from a Population-Based Birth Defects Registry
Authors: Schraw Jeremy , Rudolph Kara , Shumate Charles , Gribble Matthew
Published: September 2024

Objective and ApproachDirect potable reuse (DPR) involves adding purified wastewater that has not passed through an environmental buffer into a water distribution system. This technology may address growing demand for water in many population centers, but there are no studies of health outcomes in populations receiving DPR-treated drinking water. Our objective was to determine whether the prevalence of congenital anomalies increased in the period following introduction of DPR-treated water to certain public water systems in Texas. We obtained data on all cases with congenital anomalies regardless of pregnancy outcome during 2003-2017 from the population-based Texas Birth Defects Registry. Maternal demographic and residential data were obtained and a reference population of all livebirths in Texas was identified by linkage to birth and fetal death records. The augmented synthetic control method was used to model county-level changes in prevalence of congenital anomalies (expressed per 10,000 livebirths) after the adoption of DPR by four Texas counties in mid-2013. County-level data on maternal age, education, ethnicity, and rural-urban status were included as covariates. Results: We observed increased prevalence of all congenital anomalies collectively (average treatment effect in the treated [ATT] = 53.6) and congenital heart disease (ATT = 287.3) during the years 2014-2017. Neural tube defects prevalence was unchanged.
ConclusionsWe found evidence that the prevalence of congenital anomalies overall and congenital heart disease specifically increased during the years 2014-2017.
ImplicationsAdditional research into reproductive and developmental outcomes among people in areas supplied with DPR-treated water is warranted to inform water policy decisions.
AD|ARC (Administrative Data | Agricultural Research Collection): Characteristics of farm households participating in agri-environment schemes in Wales, UK.
Authors: Morrison-Rees Sian , Loftus Rachael , Madden Laura , Pryce Freya , Curds Matthew , Caskie Paul
Published: September 2024

Objectives

Describe the sociodemographic and farm business characteristics of farming households in Wales that have agri-environment contracts (voluntarily opting-in) without primary farm subsidies (voluntarily opting-out).
Investigate the sociodemographic and farm business characteristics of farming households in Wales by the number and type of farming subsidies received.

ApproachWe utilised the AD|ARC dataset comprising of Census 2011 variables, linked to agricultural and business variables for all farming households in Wales. 
We analysed variables relating to the individual (e.g. age, gender), household (e.g. household size, structure), farm business (e.g. farm type, diversification activities) and rural payments data (subsidy type, amount paid).
We conducted comparative analyses between three groups of farming households: households engaged in agri-environmental schemes but not primary subsidies, households engaged with both subsidy types, and households claiming primary subsidies only.
ResultsWe will present a detailed description of the sociodemographic and business characteristics of farming households by the number and type of subsidies claimed and engagement with agri-environmental schemes.
Using business, personal, and household characteristics, we will discuss different farming household typologies in relation to participation in agri-environmental schemes, and outline the relationship between farming households and positive environmental action. 
Full findings will be presented at the conference but are currently subject to information governance restrictions.
With an increasing interest in climate change and supporting the natural environment, our findings provide insight into the characteristics of farming households and their relationship to engagement with agri-environmental schemes. Our results will inform policy-makers seeking to support farming and the rural environment.
Identifying a Birth Cohort of Twins from Linked Data – Challenges and Opportunities
Authors: Campbell Alexander Charles , Young Jesse T
Published: September 2024

ObjectiveIn the absence of accurate perinatal records, identifying and differentiating twins in administrative records is difficult because of their similarity; they share surnames, dates of birth, and residences. In administrative databases, events within twin pairs are often incorrectly identified as being from one individual, representing a threat to data accuracy. An inability to identify twins in administrative data precludes applying powerful twin-based causal inference methods to understand health and social well-being.
ApproachWe developed an algorithm using linked administrative birth, perinatal, emergency department, and hospital records in Victoria, Australia from 1 January 1993 to 31 December 2023. We probabilistically linked a sample of 1,434 ‘known’ twin pairs from the Australian Twin Registry to validate the sensitivity of our algorithm. We calculated specificity using a sample of non-twins derived from linked data.
ResultsOur algorithm identified 37,900 twin pairs, 75,800 twin individuals, in the Victorian linked dataset. The accuracy of our ascertainment of twins by key characteristics will be presented and discussed.
ConclusionsThe birth cohort we have generated is one of the largest twin cohorts in the world with unprecedented granularity in longitudinal health and social data.
ImplicationsOur algorithm improves the accuracy of administrative data repositories and linkage, providing novel information on where errors in previous linkages have occurred due to limited familial or intergenerational information. Our large population-based birth cohort of twins can be used to investigate the familial and non-familial determinants of health using advanced causal inference which leverages the natural similarity between twins.
Transitions Between Home and Unscheduled Care in the Last Year of Life
Authors: Pedro Luciana , Taylor Richard , Bowers Sarah , Mills Sarah , Alexander Robin , McCowan Colin
Published: September 2024

Almost half of Scottish people who die currently die in hospital, which may represent a complex need or lack of alternative options. Nearly 95% of people use unscheduled care in their last year of life, which includes the Emergency Department (ED) – the outcome of ED attendance is often hospital admission. This increased use of unscheduled care services is associated with high costs and poor patient outcomes. This study analyses sequences of patient visits and describes patterns of ED attendance and inpatient admissions in the patients' final year of life to help understand their healthcare journeys.
This work examines the use of ED attendance and hospital admissions in NHS Tayside and NHS Fife between 2000 and 2021 for people in the last year of life. The retrospective cohort consists of all patients 18+ who died and visited the ED or were admitted to the hospital at least once. From a study population of 981,879, 164,506 (17%) people died, with 148,734 (90%) people having an ED visit or hospital admission. Data was divided for the 52 weeks before death, with three possible states for each week: home, ED visit, and admission.
A preliminary analysis shows high and significant variability in ED attendance and hospital admissions with distinct usage patterns. A better understanding of the patients' characteristics within each pattern may allow for potential interventions that improve patient care by reducing avoidable ED attendances or hospital admissions in the last year of life.
The Networked Data Lab: lessons from four years of analytical collaboration on common problems in health on social care
Authors: Knight Hannah , Fraser Caroline , Prendergast Tom , Kifetew Chamut
Published: September 2024

ObjectiveThe Networked Data Lab (NDL) is a UK-wide network of analytical teams embedded in the health and care system. Each year, we support five local partners to acquire and link new health and social care datasets on a different topic. The NDL provides insights from this linked data to help UK policymakers improve health and care, leveraging public, patient, and stakeholder engagement to prioritise topics of shared local interest.
Approach Now in its fourth year, the NDL has commissioned a Learning Study (LS) to evaluate progress towards its aims. This employs a theory-based approach to test and assess key assumptions about programme impact through a Theory of Change. For the study, semi-structured interviews with analysts and stakeholders at the five NDL sites were conducted to identify factors influencing the programme’s impact.
ResultsDrawing on interim LS findings, we will describe the types of impact the programme has achieved, and some of the key barriers and enablers to analytical collaboration across geographic and organisational boundaries. Themes include senior sponsorship; stakeholder input into problem definition; information governance and tools and skills. Themes will be illustrated with case studies drawn from the different NDL topic areas, including children and young people’s mental health and unpaid carers.
Conclusions and ImplicationsThe Networked Data Lab shows that data linkages can provide unique insights that local service planners can act on, but highlights a complex set of conditions that need to be met to enable impactful analytics using real-world health and care data.
Mental health of children with epilepsy compared to their peers: population-based cohort from linked primary and secondary healthcare record in England
Authors: Wagstaff Millie , Zylbersztejn Ania , Bennett Sophie
Published: September 2024

BackgroundChildren with epilepsy have higher rates of internalising mental health (MH) conditions compared to their peers, although available evidence is limited by small and selective samples. We used linked primary care and hospital admission records covering approximately 4.42% of English population to describe incidence of mental health problems in children with epilepsy compared to their peers.
MethodsWe developed a cohort of young people aged 7-17 years old between 2010-2019, with minimum 1 year of follow-up until death, 18th birthday or 2020 using linked data from the Clinical Practice Research Datalink and Hospital Episodes Statistics. Epilepsy (exposure), depression and anxiety (outcomes) were identified using a combination of diagnostic codes, and primary care prescribing records. We estimated incident rate ratios (IRR) for anxiety/depression/any MH condition for children with epilepsy compared to their peers using negative binomial regression adjusted for sex, age, and area-level deprivation. 
ResultsStudy cohort included 510,177 children and young people, of whom 3,011 (0.59%) had epilepsy. Children with epilepsy had higher incidence of any MH condition (IRR: 1.39, 95% CI: 1.11–1.73) and anxiety (IRR: 1.38, 95% CI: 1.06–1.77), with differences in depression being non-significant (IRR: 1.25, 95% CI: 0.92–1.66). 
DiscussionChildren with epilepsy have higher rates of MH problems than their peers. Further work will examine if this can be partially explained by increased opportunity for MH diagnosis due to more healthcare contacts. Our findings emphasise the importance of integrated care models that address both neurological and psychological aspects of epilepsy management.
Evidence from an Applied Research Health Question (AHRQ): Physician-prescribed medications to children for oral health issues
Authors: Morais Samantha , An Diana , Durbin Anna , Zweig Khai-Nhu , Tadrous Mina , Plumptre Lesley
Published: September 2024

ObjectivesTo understand changes in prescription patterns over time, and support dental and oral health program planning, Toronto Public Health issued an AHRQ request to collect information on physician-prescribed medications following an oral health-related incident.
ApproachAn algorithm was created to identify oral health-related incidents among children and youth aged up to 17 years old in Ontario and Toronto during fiscal years 2013 to 2022. The algorithm used provincial data on physician visits, emergency department visits, inpatient hospitalizations, or day surgeries to define ‘dental-related incidents’. Physician-prescribed medications (e.g., chlorhexidine, opioids, benzodiazepines, antibiotics, NSAIDs and others) within seven days of a dental-related incident were recorded using Ontario Drug Benefit Claims and the Narcotics Monitoring System.
ResultsOf 522,674 dental-related incidents in Ontario between 1 April 2013 and 31 March 2023, 9.2% had physician-prescribed medications (versus 8.6% of 90,810 dental-related incidents in Toronto). The proportion of incidents with prescriptions increased from 6.4% in 2013 to 10.7% in 2022 in Ontario, and from 5.9% to 10.3% in Toronto. The most prescribed medication was antibiotics, followed by immediate-release combination medications and non-long-acting medications.
Conclusions/ImplicationsOver the 10-year period examined, an increasing proportion of dental-related incidents had physician-prescribed medications, which may be attributed to the implementation of Ontario’s pharmacare program (OHIP+) in 2018. Early access to routine and preventative dental care could become more accessible as part of Canada’s new federal dental program. Results from this AHRQ will inform better resource allocation in dental and oral health program planning, potentially reducing avoidable healthcare costs.
Efficiency gains from the implementation of Research IDs for data linkage: A case study from Population Data BC and the Data Innovation Program in British Columbia, Canada
Authors: Jarrett Mike , Hills Brent , Kim-Bautista Maria , Ahuja Megan , Mintha Jim , Oldendorff Gitta , Wilmer Brett
Published: September 2024

Objective and ApproachPopulation Data BC (PopData) transitioned to Research IDs from Study IDs for the Data Innovation (DI) Program, with the objective of improving efficiency of data preparation, linkage, and provisioning while maintaining privacy standards. Study IDs are person-specific encrypted identifiers unique to each study, preventing Researchers from combining records from different projects, in turn reducing risk of re-identification. Research IDs are also person-specific encrypted identifiers, except they are not project specific. Advancements in technology and changes in data provisioning models have reduced utility of Study IDs.
ResultsImplementing Research IDs instead of Study IDs decreased: processing, setup/review, per transfer effort, errors/omissions, storage requirements, staff training/knowledge, licenses, record keeping, specialized knowledge, and per project data tracking. There was a marginally higher risk of re-identification with Research IDs, counter-acted by a higher degree of technological security and stronger procedural and ethical frameworks, resulting in the ability to provide more data to more users.
ConclusionsAdopting Research IDs has allowed PopData and the DI Program to access established data resources faster, more efficiently, with less per project person effort and reduced storage requirements without a net risk change. The benefits of adopting Research IDs, counter a potential minimal risk gain arising from replacement of Study IDs with Research IDs.
ImplicationsEfficiency gains from the use of Research IDs allows PopData and the DI Program to redistribute operational and staff resources, in turn increasing their ability to scale, to provide data in more diverse formats and improve service provision.
Addressing data gaps on long-term care in Canada through data linkage
Authors: Frank Kristyn
Published: September 2024

BackgroundWithin the context of Canada’s aging population, the complexities of its long-term care system, and the COVID-19 pandemic, information about long-term care facilities, their residents, and their workers is needed. However, little information exists on long-term care residents as they are rarely included in population surveys, and data on the facility characteristics of long-term care workers’ places of employment are often not available.
Objective and ApproachTo effectively monitor changes, improvements, and health outcomes in Canada’s long-term care sector, many data gaps need to be addressed. This paper will present the results of an initiative that sought to examine the potential of integrating existing survey and administrative data sources to fill these gaps. A novel approach was taken which focused on how both facility-level and individual-level data could be integrated, allowing for a more comprehensive understanding of long-term care in Canada. 
ResultsThis initiative resulted in the development of two data linkage proposals. This presentation will provide an overview of the data sources identified for linkage, the approach taken to examine the feasibility of these linkages, challenges with integrating the data sets, and next steps to move the initiative forward. 
ImplicationsThe data linkages that will be discussed will help to address data gaps on Canada’s long-term care system. The proposed data linkages may also provide researchers with ideas for using similar data sources to address data gaps in long-term care in their respective countries.