bluuebunny/crossref_metadata_2025_split huggingface dataset:
The burden of acute eye conditions on different healthcare providers in Wales: a retrospective population-based study
Authors: Rawlings Anna , Hobby Angharad , Ryan Barbara , North Rachel , Carson-Stevens Andrew , Smith Mat , Sheen Nik , Acton Jennifer 
Published: September 2024

Objective & ApproachDemand for urgent eyecare exponentially outstrips public healthcare capacity in the United Kingdom. Such eye conditions, and related vision impairment, affect the lives of people everywhere. We aimed to quantify the burden of urgent eyecare on primary- and community-care providers in a national population using data produced by General Practitioner, Accident and Emergency, pharmacy and optometry services. A secondary aim was to characterise some drivers of this burden.
We analysed data from the Secure Anonymised Information Linkage Databank (linked), Eye Health Examination Wales Service (unlinked) and Common Ailments Scheme (unlinked) during 2017-2018 to quantify burden. We applied generalised linear modelling and logistic regression to understand drivers.
ResultsOf 365,044 episodes of care during the study, GPs and A&E managed 46.2% (168,877) and 1.4% (5,122) respectively while optometrists and pharmacists managed 51.8% (116,868) and 0.6% (2,635). Older females and infants of both sexes were more likely to use GP prescribing services, while adolescent and middle-aged males were more likely to visit A&E. GP prescribing burden was driven partially by economic deprivation, access to local services, and overall community health. Season, day of the week, and time of day were predictors of burden for GP and A&E services.
Conclusion & ImplicationsAcute eyecare continues to place considerable burden on primary care services in Wales, particularly in urban areas with greater deprivation. This is likely to increase with an ageing population. With ongoing pathway development to better utilise community care, there may be scope to change this trajectory.
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.
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).
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.
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.
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.
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.