bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Determinants of Supply Chain Performance in Manufacturing Industries: A Case Study of Proton Malaysia
Authors: SUHAIME INTAN LIANA , SEHAT NANI SHUHADA , DAUD SITI ROHANA , JOGERAN JUMAELYA 
Published: September 2024

This study examines the key elements that significantly impact supply chain performance in Proton Malaysia, a prominent participant in the automotive sector in Southeast Asia. The objective is to understand the impact of crucial factors on Proton's supply chain's performance, including information quality, information technology, information sharing, big data analytics capacity, supply chain integration, traceability, and agility. The study used a qualitative research methodology to examine Proton's supply chain dynamics, focussing on its strategic collaboration with Geely and the incorporation of new technology. Both primary and secondary data are utilized for analysis. The results demonstrate that Proton's focus on up-to-date information, sophisticated analysis, and robust supplier connections has greatly improved its ability to respond quickly and effectively to operational challenges and maintain its ability to recover from disruptions. Furthermore, the research emphasizes the significance of supply chain agility and integration in effectively responding to market fluctuations and reducing risks. The findings indicate that Proton must consistently engage in technology and supply chain innovation to retain its competitive advantage and successfully traverse the intricate nature of the global automobile market. These lessons apply to Proton and other manufacturing enterprises aiming to optimize their supply networks in a progressively dynamic and linked environment.
Prevalence of Multimorbidity and Chronic Diseases in citizens of the Métis Nation of Ontario
Authors: Tsui Noel , Cripps Shelley , Simms Abigail , Tjong Gabriel , Golding Haley , Edwards Sarah 
Published: September 2024

Objective and ApproachPopulation-based analyses of Métis health in Canada are limited. The Métis are a distinct Indigenous people with both First Nation and Euro-Settler ancestry. This study aimed to examine multimorbidity in the Métis Nation of Ontario (MNO) citizens from 2009 to 2019. Registered MNO citizens were linked to Ontario’s administrative health data. An existing data algorithm identified individuals with multimorbidity (2+ chronic conditions) among MNO citizens and the Ontario population aged 18+. Annual prevalence rates of multimorbidity were calculated and rates in the latest year were compared across income quintiles, age, and sex.
Results & ConclusionThe prevalence of multimorbidity increased in MNO citizens from 49.2 per 100 (CI: 48.1-50.2) in 2009 to 61.0 per 100 (CI: 59.9-62.1) in 2018. A consistently higher prevalence rate was seen in MNO citizens compared to non-MNO citizens across the entire period. Female MNO citizens had a higher prevalence of multimorbidity compared to males. The prevalence of multimorbidity increased with age in MNO citizens from 40.5 per 100 (CI: 39.1-41.8) in those aged 18 to 44 years up to 91.6 per 100 (CI: 88.4-98.0) in those aged 65 years and older. An income gradient was evident with MNO citizens in the highest income quintile having the lowest prevalence of multimorbidity (57.1 per 100) compared to those in the lowest income quintile (66.3 per 100).
ImplicationsUnderstanding the burden of multimorbidity in MNO citizens is essential for the MNO to guide program and policy planning, as well as support decision-making related to resource allocation.
Local authority variation in special educational needs provision at the start of primary school: observational study of preterm children born in England, 2003-2013
Authors: Lewis Kate , Nguyen Vincent , De Stavola Bianca , Dearden Lorraine 
Published: September 2024

Objective and ApproachWe explored variation in special educational needs (SEN) provision between local authorities (LAs) in England by focussing on children born preterm (24-<37 weeks gestation). We used linked individual-level state-funded hospital and school records from the ECHILD database, alongside publicly available school-level records. LA of child’s residential address (n=150) and recording of SEN provision (split into SEN support and education, health and care plans, EHCPs) were captured at the January school census in year one, when pupils were five/six years old. We fitted multi-level logistic regression models to the child-level records that included a-priori selected child- and LA-level characteristics.
ResultsOur population included 226,419 children (45.4% female ; 10.6% with a congenital anomaly) born between 2003-2013 and attending a state-funded primary school. Across LAs, the median prevalence of SEN support and EHCPs recorded in year one was 18.4% (interquartile range 16.4%-20.4%) and 4.2% (3.5%-4.8%), respectively. In the SEN support vs. no SEN provision model, there was very low correlation among children from the same LA (intraclass correlation coefficient (ICC)=0.006 )). There was higher correlation in the EHCP vs. no SEN provision model (ICC=0.032). Of the LA-level characteristics, the percentage of children eligible for free school meals had the greatest impact on the ICC values (reduction of 26.7% in the EHCP model).
ConclusionsLess than 1% of the variation in SEN support and approximately 3% of the variation in EHCPs was explained at the LA level. We will extend these models to consider variation at the school level.
Free Text Analysis: Identification of adverse drug events in clinical notes
Authors: Katz Alan , Dhankar Abhishek , Leong Christine , Hamad Amani , Singer Alex 
Published: September 2024

ObjectiveTo explore the prevalence of adverse drug events (ADE) leading to drug changes using Artificial Intelligence (AI) based free text analysis of primary care encounter notes .
ApproachWe used electronic medical record l encounter notes linked to population-based drug dispensation records. Dispensation records were used to identify drug switching to another agent in the same therapeutic class, which could suggest an undesirable side-effect requiring discontinuation of the drug. We annotated clinical notes by identifying ADEs after retrieving the last encounter note written for that patient on or before the identified date. We ran different AI models, including BERT and Large Language Models (LLMs), to identify ADEs.
ResultsWe annotated 1085 notes with 362 ADEs. These were used to train BERT models (precision or PPV: 0.584 ) and prompt-based LLM (0.563) but with improved sensitivity (0.725) and specificity (0.739) .
ConclusionsIdentifying ADEs requires deep medical knowledge and simple Natural Language Processing models trying to identify ADEs only on the basis of language of encounter notes was not successful based on the BERT model performance. Prompt based models have deep knowledge but were trained with the objective of producing grammatically correct, coherent sentences, not with the medical knowledge required. LLMs also require significant computational power.
ImplicationsWhile AI does have significant potential to advance our capacity for complex analytic tasks the current LLMs are not yet able to adequately identify ADEs in a corpus of electronic clinical notes.
Linking for Impact: Enhancing Linked Data Infrastructure to Meet Clinical Trials Sector Needs
Authors: Bailey Rowena , Davies Jo , Pedrick-Case Rebecca , Mizen Amy , Johnson Rhodri , Fry Richard , Griffiths Lucy 
Published: September 2024

BackgroundAustralia possesses valuable population health data, yet its potential for advancing medical product development remains largely untapped. Transformative growth in the use of linked data in clinical trials will support Australia’s therapeutic development sector to be more responsive in the development of new therapeutics and the monitoring and surveillance of their safety and effectiveness.
MethodsWe conducted interviews with clinical trialists and data linkage experts to understand the current state and awareness of linked data within the clinical trials sector, identify existing pain points in the linkage process, and explore opportunities for improving visibility and access for the clinical trials sector. Researchers represented all stages of the medical product development pipeline and had a diverse range of experience with linked data.
ResultsInterviews revealed numerous barriers hindering the clinical trials sector from effectively using linked data, limiting its impact. Barriers included a lack of awareness, the complexity of the application and approval process, and lengthy delays in accessing data.
Participants readily recognised several ways that linkage of real-world data could be applied to their work in clinical trials, with pre-recruitment data, measurements of primary and secondary endpoints, and health economic analysis being the most consistently noted use cases.
ConclusionTo optimise the use of linked data to support clinical trials and medical product development in Australia, increased awareness among the therapeutic development sector regarding available real-world data and its potential is needed urgently. Lowering the barriers to accessing linked data will enhance health services and patient outcomes across Australia.
Policy-driven multidisciplinary primary care after stroke or Transient Ischaemic Attack (TIA) improves survival – an observational target trial evaluation involving linked registry data
Authors: Andrew Nadine , Ung David , Kilkenny Monique , Olaiya Muideen , Dalli Lachlan , Churilov Leonid , Collyer Taya , Snowdon David , Kim Joosup , Srikanth Velandai , Cadilhac Dominique , Sundararajan Vijaya , Thrift Amanda , Nelson Mark , Lannin Natasha 
Published: September 2024

ObjectiveTo determine the effectiveness of government policies supporting coordinated multidisciplinary primary care (MDC) in improving long-term survival following stroke or Transient Ischaemic Attack (TIA).
ApproachWe used the target trial framework for observational data to assess the average population effect of primary care MDC policies. The cohort comprised patients from the Australian Stroke Clinical Registry (January 2012-June 2015) linked with (i) Australian Medicare claims to define exposures (MDC claims in the 6-18 months post-stroke); (ii) hospital, pharmaceutical and aged care datasets for additional covariates; (iii) National Death Registry for survival outcomes (19-30 months post-stroke). Level of impairment was classified by latent class analysis using EQ-5D-3L questionnaire data obtained 90-180 days post-stroke. Multilevel survival analysis with inverse probability treatment weights was applied.
ResultsAmong 7,255 people with stroke (42% female, median age 71 years, 24% TIA, level of impairment: 39% minimal, 32% moderate, 29% severe), 29% had a Medicare claim for MDC (23% minimal, 31% moderate, 39% severe). Mortality was reduced in those receiving a claim (vs non-receipt) in the minimal (adjusted Hazard Ratio (aHR): 0.50, 95%CI:0.27, 0.91) and severe (aHR: 0.65, 95%CI:0.46, 0.91) impairment groups, but not the moderate impairment group (aHR: 1.31, 95%CI:0.86, 1.99). Group differences in allied health services claimed during MDC were observed: secondary prevention (14% minimal vs 10% severe impairment), rehabilitation (21% minimal vs 25% severe impairment).
ImplicationsDrawing causal inferences from linked observational data demonstrated the population effectiveness of primary care MDC policies, in improving survival following stroke/TIA, with variation by impairment class.
Mortality in adolescents receiving special education and social care provision: A population-level cohort study in England
Authors: Ward Isobel , Jay Matthew , Ward Joseph , Gilbert Ruth , Zylbersztejn Ania 
Published: September 2024

BackgroundOver a third of children in England receive either special educational need (SEN) provision/children’s social care (CSC) support at least once during school. We aimed to describe all-cause and adversity-related mortality for adolescents who received SEN or CSC provision in England.
ApproachWe used linked data from hospital admissions, death registrations, social care and education in the ECHILD database to follow all adolescents in state schools from age 13-years between 2009/10-2014/15 until death or 2020. Adolescents were grouped according to provision ever recorded before age 14: None, SEN only, CSC only or CSC and SEN. We estimated all-cause and adversity-related mortality in children with SEN/CSC/both compared to peers.
ResultsThe cohort comprised 3,381,502 children (51% boys), of whom 30.1% (n=1,017,670, 62% boys) received SEN only, 4.2% (n=143,430, 36% boys) received CSC only and 8.7% (n=293,310, 57% boys) received SEN and CSC. In ten-year follow up, 6,590 deaths occurred (66% in boys). Mortality rates were 5.4 times higher for adolescents receiving both SEN and CSC, 2.4 times higher for CSC only, and 1.7 times higher for SEN only compared to peers. Rates of adversity-related deaths were highest for boys receiving SEN and CSC compared to peers.
Conclusions & Implications8-in-1000 adolescents who received both SEN and CSC before age 13 died by age 23 years, far more often than their peers. Policies need to consider support for young people with additional educational and social care needs as they leave school and transition to adulthood.
Public informed training: Developing a curriculum for trialists using health systems data
Authors: Lugg-Widger Fiona , Trubey Rob , Robling Mike , Mafham Marion , Sydes Matthew , Shepherd Victoria , Cannings-John Rebecca , Hood Kerenza , Ahmed Nagheen , Islam Sadman , Rawlinson Sarah 
Published: September 2024

IntroductionResearchers are increasingly using health systems data to support clinical trials. A recent Delphi study identified a number of remaining challenges across the trial lifecycle and highlighted opportunities to address them through the development of training resources.
Objective and ApproachWe present a programme of work to identify, facilitate and optimise emerging practices for using health systems data in trials, informed by subject matter experts and steered by public input, to begin addressing the ongoing challenges for trial teams.
ResultsDirectly addressing a key identified priority for building public trust, we co-developed a series of freely-available online training videos on how public involvement and engagement can impact across the trial lifecycle plus practical tips for such activities. This curriculum was informed by public members who then featured in the training videos. We broadened the training focus to align with trials community needs, whilst retaining the public co-production element. A diverse and purposive group of applicants were selected to contribute to the ongoing work of the HDR UK Transforming Data for Trials workstream. Our presentation reviews how models of involvement have informed our approach including reflections from our public members on what has worked well and what can be improved. We will reflect on the intersection of public involvement in trials and public involvement in healthcare/administrative systems data research.
Conclusions & ImplicationsCo-development with a diverse public group ensures all current and future training resources developed reflect a diversity of views, increasing the quality and credibility of materials.
Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people across four nations in the UK
Authors: Aldridge Sarah J , Agrawal Utkarsh , Murphy Siobhán , Millington Tristan , Akbari Ashley , Almaghrabi Fatima , Anand Sneha N , Bedston Stuart , Goudie Rosalind , Griffiths Rowena , Joy Mark , Lowthian Emily , De Lusignan Simon , Patterson Lynsey , Robertson Chris , Rudan Igor , Bradley Declan T , Lyons Ronan , Sheikh Aziz , Owen Rhiannon K 
Published: September 2024

Background and ObjectivesSARS-CoV-2 infection in children and young people (CYP) can lead to life threatening conditions including COVID-19, transmission to more vulnerable individuals, or even long COVID. Vaccination against COVID-19 reduces the chance of infection and transmission of the virus, but vaccine uptake in the UK has been shown to decrease with age.
ApproachWe undertook a multistate-model approach to estimate hazard ratios on national cohorts constructed from linked health and administrative data, adjusting for several demographic factors. The models were applied to 3,433,483 CYP aged 5-17 years between 4th August 2021 and 31st May 2022. The results were combined in a random effects meta-analysis.
ResultsUptake of the first COVID-19 vaccine in CYP was lower compared to older age groups in the UK, and diminished further with subsequent doses (34%, 20% and 2% for 1st, 2nd, and booster dose respectively). Age of the CYP and vaccination status of the adults in the household were identified as important risk factors. For example, 5-11-year-olds were less likely to receive their first vaccine compared to 16-17-year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06-0.19), and CYP in unvaccinated households were less likely to receive their first vaccine compared to partially vaccinated households (aHR: 0.19, 95%CI 0.13-0.29).
Conclusions and Implications Our work highlights the need for targeted strategies to increase COVID-19 vaccine acceptance and uptake among CYP, especially considering the influence of parental consent and household factors. Further research could help identify risk factors in household types to investigate more direct associations, which may be influenced by factors such as living with vulnerable people, familial structure, or deprivation.
Investigating long-term health outcomes in high-level rugby union players using linked administrative data
Authors: D'Souza Stephanie , Milne Barry J. , Anns Francesca , Quarrie Kenneth L. 
Published: September 2024

Objective and ApproachThe Kumanu Tāngata study investigates long-term health outcomes in male high-level rugby union players in New Zealand using the Integrated Data Infrastructure (IDI), a comprehensive de-identified whole-population administrative research database. A historical register containing players active between 1950-2000 was linked to the IDI. Rugby players (n=12,861) were compared to general population males (n=2,385,690), matched by age, ethnicity, and birthplace, on neurodegenerative disease outcomes from health records available between 1988-2018. Cox proportional hazards models were conducted.
ResultsRugby players exhibited a higher neurodegenerative disease incidence (4.7%) than the general population (3.9%). Players had an increased risk of any neurodegenerative disease (1.17 [95% CI 1.08–1.27]), Alzheimer's disease (1.42 [95% CI 1.22–1.66]), and other dementias (1.16 [95% CI 1.05–1.27]). An increased risk of any neurodegenerative disease was observed for professional- or international-level play (HR 1.51 [95% CI 1.04–2.18]), six or more years of play (HR 1.32 [95% CI 1.15–1.50], and a backline playing position (HR 1.30 [95% CI 1.17–1.45]).
ConclusionsThe study indicates a small-to-moderate increased risk of neurodegenerative diseases for high-level rugby players in New Zealand when compared to the general population, with variations observed across play duration, level and position. Future research will examine additional health outcomes, including mortality, musculoskeletal conditions, and mental health disorders.
ImplicationsThis large-scale linkage study allows for a comprehensive examination of long-term health outcomes and enhanced statistical power than previous research. Findings have the potential to influence health policies and athlete care strategies in contact sports.
Expanding opportunities in health data: Enhancing research by facilitating linkage of Ontario’s population-level health administrative data with data from patient support programs (PSPs)
Authors: Arnold Keresa , Ishiguro Lisa , Ho Minnie , Skvirisky Dina , Retnakanthan Jeruby , Etches Jacob , Mondor Luke , Saskin Saskin , Victor Charles 
Published: September 2024

ObjectivesPatient Support Programs (PSPs) provide real-world evidence on short-term outcomes and drug adherence for specialty care. These data are collected directly from patients by pharmaceutical companies. Data linkage is facilitated by a publicly-funded health research institute which houses population-based, individual-level health administrative data for 14 million Ontario residents in Canada since 1992. Linkage provides a more comprehensive and transparent view of patients’ pathways and care.
ApproachIndustry-funded research conducted through the data & analytic service must align with the institute’s mission, vision and values, and demonstrate a clear public benefit. For transparency, and to support broader public benefit and research access, final deliverables and analytic plans are posted on the institute’s website. Privacy impact assessments are conducted to ensure ethics approvals, consent and data sharing agreements are established, prior to data importation. To safeguard privacy, designated data covenantors encrypt and link the PSP data with in-house data holdings. Analyses are performed by senior analytic staff, providing researchers with summary-level reports.
ResultsSince 2016, the institute has worked with organizations to link data for research, including PSP data on thousands of patients, enabling crucial insight into treatment patterns, drug adherence, costs and long-term outcomes.
ConclusionLinkage of privately-owned PSP data with administrative health data at the institute, provides opportunities to identify gaps in care and improve quality of research. Data challenges around bias, transparency, completeness, and comprehensiveness are minimized.
ImplicationsResults provide decision-makers and healthcare professionals with a trusted and comprehensive understanding of patient care pathways to improve health outcomes.
AD|ARC (Administrative Data Agri-Research Collection): Linking Individual, Household and Farm Business Data for Sociodemographic Research on Farming Households
Authors: Morrison-Rees Sian , Madden Laura , Curds Matthew , Caskie Paul , Loftus Rachael 
Published: September 2024

ObjectiveTo understand the socio-demographic characteristics and structure of farming households in Wales who receive subsidies compared to non-farming rural households.
Approach We utilised the AD|ARC dataset, a comprehensive resource we created within the SAIL databank by linking de-identified records of farms receiving farming subsidies in Wales with socio-demographic information from the Census 2011. A control group was created by matching each farming household with up to three households in the 2011 Census from a similar geographical area that did not contain a farmer or household member in receipt of farming subsidies. We used Census 2011 variables to compare household size, family structure and age for 18,135 farming households with a control group of 53,365 rural non-farming households.
Results We found little difference between the age and gender distribution between cohorts, however we found significant differences in the household structure. Farming households had a larger average size compared to non-farming households. Single-occupancy farming households had a significantly higher proportion of males, farming households were more likely to have couples with children and a higher percentage of these couples were married compared to non-farming households.
Implications The agriculture sector in Wales is facing a range of challenges linked to social, economic, and environmental sustainability as it establishes a new direction after UK withdrawal from the EU. Understanding the sociodemographic characteristics of farming communities is essential for developing effective policies and interventions that address the specific needs and challenges faced by these groups.