bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Impact in Fighting the Global HIV Epidemic
Authors: Ritz Derek , Ketani Violet 
Published: September 2018

IntroductionLinking healthcare expenditure data with health outputs and outcomes data is challenging. This is especially true in low-resource (LMIC) settings. Where such linking can be accomlished, however, it supports the development of IMPACT-per-DOLLAR metrics that may be leveraged to support programme optimization.
Objectives and ApproachThis session will describe a new data-linking design for a global health programme targeted to low and middle-income countries (LMIC). The US Government's President's Emergency Plan for AIDS Relief (PEPFAR; www.pepfar.gov) is a \$7 billion/year programme spanning 58 LMICs. PEPFAR prepares annual budgets and plans. On a quarterly basis, Implementing Partners report programmatic district-level Monitoring, Evaluation and Reporting (MER) indicators to a central database. Starting in July, 2018, quarterly expenditure data will also be captured, broken down by major programme area and high level account code. The novel new data-linking approach triangulates the budget, indicator and expenditure datasets.
ResultsThe PEPFAR programme is managed by the US State Department's Office of the Global AIDS Coordinator (S/GAC). S/GAC undertook, in 2017, a significant re-design of its information system requirements and the software systems that will support these. A multi-year design and prototyping effort has yielded a novel new approach for financial monitoring intended to improve S/GAC's abilities to exert its mandates regarding both programmatic and financial oversight.
The new data-linking solutions are being implemented across all PEPFAR countries during the first half of 2018. Information model design choices (and trade-offs), solution architecture designs, and preliminary pilot results of this new implementation will be reported at the confernce. A discussion of implementation science lessons-learned specific to deploying in LMICs will also be presented.
Conclusion/ImplicationsPEPFAR's goal and mission is to operationalize HIV epidemic control and achieve an AIDS-free generation by 2030. Data analytics are proving essential to achieving this goal. S/GAC's re-design efforts will help better link its huge financial and programmatic (MER) datasets to support DALY-per-DOLLAR impact optimization on this important initiative.
Combining Artificial Neural Networks, Routine Health Records and Suicide Risk Estimation
Authors: Del Pozo Banos Marcos , Travieso Carlos M , Loxton Kate , Petkov Nicolai , Berridge Damon , Lloyd Keith , Jones Caroline , Spencer Sarah , John Ann 
Published: September 2018

IntroductionEvery year ~800,000 people die by suicide worldwide. The pathway to suicide is mediated by highly complex processes, integrating a large number of risk factor variables which are extensively dependent on one another. Unfortunately, suicide risk prediction has been a challenging problem for epidemiological studies and their application to practice.
Objectives and ApproachWe aim at exploring the feasibility of using artificial neural networks (ANNs) based on routinely collected electronic health records (EHRs) to support the identification of those at high risk of suicide when in contact with health services. We used the Secure Anonymised Information Linkage Databank UK to extract those who died by suicide between 2001 and 2015 and identify controls. We extracted risk factors from primary and secondary care about mental health, injury, substance misuse, maltreatment, sleep disorders and prescriptions. We trained a simple ANN to differentiate between cases/controls to test the feasibility of this approach.
ResultsA total of 2,604 suicide cases and 20 paired controls per case were used during 10x10 K-Fold repeated cross-validation. We obtained an error rate of 26.78% ± 1.46 differentiating between cases and controls. The distribution of controls was concentrated around estimated risks"
Conclusion/ImplicationsThe proposed method performed similar to other works based on specialized questionnaire data. Prescription of psychotropics, depression and anxiety, and self-harm were strongly linked with higher risks, followed by hospital admission and substance misuse. This is in keeping with known literature, providing evidence that the proposed approach is feasible.
Getting animated about routine data: co-producing a video and toolkit with young families
Authors: Lugg-Widger Fiona , Segrott Jeremy , Gee Peter , Kenkre Joyce , Robling Mike 
Published: September 2018

IntroductionWhile public engagement activity in healthcare may include a focus on uses of patient data, use of social care/ education data may be relatively overlooked. The public may be less aware about how their social care data may be used. Some concepts such as benefits and risks may also differ.
Objectives and ApproachOur objective is to co-produce with members of the public a package of materials that researchers may then use to promote public understanding of and engagement in research that uses routine data from health and social care settings.
We are running workshops with two groups of young families (teenage mothers, some of whom have received specialist home-visiting support) to explore key concepts and messages about routine data use, including sensitive data such as maltreatment and regulatory child protection interventions. The workshop includes completing a story board for an animated video. This will be co-produced by the same young people.
ResultsOur recent work with young families has shown a preference for visual based methods over text-based approaches to explain routine data linkage. This represents a key opportunity for innovation. We have explored how members of the public understand and make sense of routine data from various settings (health/social care) and its use in research. Working with a professional animator, the co-production of a prototype animation aims to engage members of the public about the nature, benefits and safeguards of using routine public records in health and social care research. The presentation will summarise the method of co-production, review the prototype animation and associated materials for researchers (‘toolkit’). Finally, we will recap key messages identified from the workshops that underpin the animation and other dissemination plans.
Conclusion/ImplicationsOur existing understanding of public views (e.g. from consumer panels) may not represent well perspectives from population groups, such as teenage parents. Working with young families who may otherwise rarely engage in such work provides their unique perspectives, adding richness to our understanding of public views on routine data usage.
Distributed team health data science in risk of non-Vitamin K Oral Anticoagulant after Intracranial Haemorrhage
Authors: Song Jiao , Elliot Elizabeth , Morris Andrew , Kerssens Joannes , Akbari Ashley , Thompson Simon , Lyons Ronan 
Published: September 2018

IntroductionNew non-vitamin K Target Specific Oral Anticoagulants (TSOACs) have a favourable risk-benefit profile and debatable cost effectiveness. Large numbers and data from multiple countries in a European study are required to investigate safety issue of TSOACs in subgroups, e.g. people with an intracranial haemorrhage.
Objectives and ApproachWe developed an approach to rapidly replicate data and analyses to support cross-country distributed research within the UK/EU using Electronic Health Records (EHRs). This project was conceptualised and initialled by linking relevant datasets held in multiple data warehouses, in Scotland with the Scottish National Data Safe Haven, and in Wales through the Secure Anonymised Information Linkage (SAIL) databank. Analysts in Edinburgh and Swansea had remote access to each other’s datasets and worked collaboratively to harmonise variables and analysis scripts. . A common R code script has been produced to harmonise individual data as well as the outputs from the study.
ResultsThe study screened data on 8M people to develop a cohort that included pseudonymised information of 4,153 individuals in Scotland and 2,676 individuals in Wales, 6,829 individuals in total. Standardised risk analyses were completed in both settings with ongoing work in combining the analyses. In Wales, 39.5% of the patients in the cohort had been admitted to hospitals due to serious vascular events or died caused by these events, after intracranial haemorrhage. Incident rates for male and female are 0.63 and 0.7 respectively. Within the cohort, 0.5% were prescribed with TSOACs and 3% with Warfarin (included as reference). The project is also in the process of including other European jurisdictions.
Conclusion/ImplicationsThe adopted approach was the simplest, yet most efficient and cost-effective method to ensure consistency in analysis and coherence with currently available governance systems of both safe havens. It can also be considered as an initialisation of developing infrastructure to support research using EHRs across the UK and EU.
Assessing lifestyle risk factors and inequalities in health outcomes in most deprived communities in Wales
Authors: Song Jiao , Akbari Ashley , Cox Caryn , May Leon , Watkins Williams , Thomas Sarah , Aitken Sarah , King William 
Published: September 2018

IntroductionThe Inverse Care Law (ICL) programme in Wales was piloted in Aneurin Bevan (AB) and Cwm Taf (CT) University Health Boards, chosen due to being located in areas of Wales which experience some of the most significant health inequalities and lower life expectancy and potential to effect change.
Objectives and ApproachThe programme is aiming to address inequalities in health outcomes between the most and least deprived communities in Wales and implement targeted interventions towards lifestyle risk factors, such as poor diet, physical inactivity, smoking and high alcohol intake. The project collaborated with multiple stakeholders within the Health Boards, Swansea and Cardiff University and Public Health Wales to ensure the correct outcomes were identified and measured. The Welsh Longitudinal General Practice (WLGP) data held in Secure Anonymised Information Linkage (SAIL) databank was used to extract clinically relevant information for evaluation, with the Welsh Demographic Service Dataset (WDSD) providing demographic characteristics.
ResultsBetween AB and CT University Health Boards, from February 2015 to November 2016, over 7000 people who were offered a health check completed one at a participating General Practice. 96% of these were in the three most deprived Welsh Index of Multiple Deprivation (WIMD) quintiles. 51% were referred within primary care for follow up based on their health check results, 71% were overweight/obese, and 20% were identified as current smoker of within which 28% were referred to smoking sensation services. Alchohol usage and other health issues have also been investigated. For example, 20% of those tested for blood pressure had an elevated result and 24% were subsequently prescribed anti-hypertensive medication.
Conclusion/ImplicationsResults showed risks have been identified from health checks and targeted interventions were introduced based on the results. Repeated analysis in future should be used to further evaluate the effectiveness of the interventions longitudinally. Outcomes are reported back on a scheduled basis to monitor and improve the implementation across Wales.
Linking Pan-Canadian Administrative and Clinical Registry Data to gain insights across the continuum of care
Authors: Wu Juliana , Gnidziejko Nick , Terner Michael 
Published: September 2018

IntroductionData linkages expand the potential of discrete national health databases to follow patients across the health care continuum. Novel linkages across health care sectors, jurisdictions, and over time provide a deeper understanding of a patient’s journey and can facilitate health systems performance evaluation to ultimately improve patient-level health outcomes.
Objectives and ApproachThe objective was to increase the value of pan-Canadian administrative and cost data using novel linkages to longitudinal patient-based clinical registries. One such example is a data linkage comprised of three national data holdings to examine inpatient care and associated costs during ten years of chronic dialysis treatments. Patient data on dialysis treatment changes from the longitudinal clinical registry were linked to episodic inpatient hospitalization and corresponding cost data. Effect of various cofactors on the risk of hospitalization, as well as the cost burden of such hospitalizations on the health system, were examined.
ResultsEffective data linkage can facilitate analyses of a broader spectrum of outcomes adjusted for a broader set of patient characteristics and treatment modalities. Linking dialysis patient registry data to administrative inpatient care data showed that patient-specific covariates significantly affect the risk of dialysis patients being hospitalized. These findings were consistent for hospitalizations for dialysis-related infections, a highly preventable complication amongst dialysis patients. The rate of hospitalization of dialysis patients in Canada ranged from 1.1 to 1.4 hospitalizations per patient-year on dialysis. Linking to cost data showed that the average estimated cost for these hospitalizations ($13,634 per patient year on dialysis) was more than double that of the general population. These and other insights can be achieved more quickly and efficiently using data linkages.
Conclusion/ImplicationsCanada’s many health-related data assets, when combined through effective linkage, can provide tremendous potential for performing longitudinal, patient-oriented analyses in a pan-Canadian setting. Using administrative and cost data to augment the clinical information in the registry data proves to be useful for informing improvements in health and health services.
Educational outcomes of children with cerebral palsy
Authors: Jones Hywel , Carter Bethan , Bethan Jackie , Collins Huw , Wang Ting , Rees Sarah , Kemp Alison , Paranjothy Shantini 
Published: September 2018

IntroductionChildren with special educational needs (SEN) are more likely to have disadvantaged backgrounds than their peers, attend school less and do not achieve as well academically. Many children with a cerebral palsy (CP) have SEN but little is known about their educational outcomes.
Objectives and ApproachTo investigate the background of children in Wales with CP and describe their educational experience including: type of SEN and SEN provision; school attendance; achievement—teacher assessments at the end of the Foundation Phase and Key Stages 2 and 3 of the National Curriculum (NC)— and in General Certificate of Secondary Education (GCSE) examinations.
Data from the Pupil Level Annual School Census (PLASC), NC and GCSE results were linked with routine e-health records of primary and secondary health care data held in SAIL. Using health care records for everyone aged between 0-25 in 2004–14, cases of CP were flagged.
ResultsThe linked data set included some 1500–2000 children per school census classified as having a CP, representing a prevalence of some 0.3%. Provisionally, results show: prevalence of CP is higher amongst children living in relatively deprived areas; around 60% of CP children have a statement of SEN; the SEN type most commonly recorded for CP children with SEN is ‘Physical and medical difficulties’ and relatively high proportions have profound, multiple or severe learning difficulties; around 30% of CP children are educated in special schools; CP children in main stream (primary, middle and secondary) schools tended to miss more school sessions (~50% more) than other children and lower percentages achieved the expected levels at key stages 2 and 3 and the Level 2 GCSE threshold.
Conclusion/ImplicationsThis work demonstrates the utility of record-linkage for providing information to parents, carers and policymakers about education outcomes for this group of children to inform planning and service provision.
Primary, secondary care and mortality data-linked to identify the prevalence of cerebral palsy in children and young people
Authors: Carter Bethan , Jones Hywel , Bethell Jackie , Wang Ting , Rees Sarah , Kemp Alison , Paranjothy Shantini 
Published: September 2018

IntroductionEvaluations of healthcare utilisation for children and young people (CYP) with chronic conditions, are increasingly relying upon routinely collected healthcare data to estimate healthcare burden and inform national policy and practice. However, chronic conditions are not consistently or accurately recorded making it difficult to conduct valid epidemiological analyses.
Objectives and ApproachWe explored routinely collected healthcare datasets of 2,122,914 CYP in the English Clinical Practice Research Dataset (CPRD) and 1,636,252 CYP in the Welsh Secure Anonymous Information Linkage (SAIL) databank to identify patients with CP (an exemplar of a chronic neurodisability) from diagnosis coding (G80-83.3). Linked primary care, hospital admission outpatient and mortality data were searched from birth and populations of CYP aged 0-25 years between 2004 and 2014 with and without CP were identified. We detected the ascertainment sources and compared the results from CPRD and SAIL. In a sample of cases G80-83 codes were validated against clinical records.
Results
England: Some 7,500 cases of CP were identified (period prevalence: 3.5 per 1000 CYP). Of those, 36.6% were identified from hospital admissions; 20.6% from GP data, 42.0% were in both datasets with 0.8% from outpatient/ONS mortality data.
Wales: Some 5,400 cases of CP were identified (period prevalence: 3.3 per 1000 CYP). Of those, 38.6% were identified from hospital admissions, 25.3% from GP data, 36.0% were in both datasets, and 0.1% from mortality/outpatient datasets.
729/877(83.1%) cases coded as G80-83 in secondary care case notes were validated cases of CP leaving 16.9% that were incorrectly coded. Approximately 70% of G80 cases were recorded as G80.8-9 (CP other/unspecified). Roughly 30% of cases were only coded as CP on one occasion within the primary and secondary care datasets.
Conclusion/ImplicationsSimilar proportions of CP cases were identified in the two datasets giving similar period prevalences. Inconsistent and incorrect coding will affect the accuracy of these figures and precludes any analysis by disease type/severity. Improved coding of chronic conditions is needed before accurate healthcare analysis of routine data can be undertaken.
Public housing and healthcare use: Determining whether public housing functions as an intervention using linked population-based administrative data
Authors: Hinds Aynslie , Bechtel Brian , Distasio Jino , Roos Leslie , Lix Lisa 
Published: September 2018

IntroductionPublic housing is a form of subsidized housing that is owned and/or managed by government. Previous research suggests that public housing has a positive impact on personal finances and education outcomes, but less is known about if/how it impacts health and healthcare use.
Objectives and ApproachUsing linked administrative health and social data, we tested for changes in healthcare use among a cohort who moved into public housing in 2012 and 2013 in Manitoba, Canada, and compared utilization to a matched general population cohort who did not move into public housing. Generalized linear models with generalized estimating equations tested for differences in numbers of healthcare contacts in the years before and after the move-in date, adjusted for economic, residential mobility, and health characteristics. The data were modeled using a Poisson (rate ratio, RR), negative binomial (incident rate ratio, IRR), or a binomial (odds ratio, OR) distribution.
ResultsThere were 2619 residents in the public housing cohort; 99.7% were matched to the general population. The cohort by time interaction was statistically significant for inpatient days (p
Conclusion/ImplicationsPublic housing residents were more likely to use healthcare services than the matched population, but changes in use were similar in the two cohorts. There is little evidence that public housing impacts healthcare use, but it serves an important function of meeting basic needs for a vulnerable population group.
From online banking to biobanking: designing and implementing a data delivery platform for researchers of the China Kadoorie Biobank
Authors: Sansome Sam 
Published: September 2018

IntroductionAs a large prospective cohort study of 512,891 participants, we routinely integrate data via linkage to population health outcomes to deliver up-to-date research datasets. Building on experience from the private sector, we have implemented a platform that supports the delivery and audit of secure datasets to internal and external researchers.
Objectives and ApproachWe aimed to create a platform that delivers secure research datasets for preliminary analyses and fieldwork with dynamic censor dates. It must also provide multiple static versions of an analysis-ready database with fixed censor dates. Individual participant outcome data from population health sources (death and disease registries and health insurance agencies) can be integrated and linked regularly to other health-related data, e.g., genetic, bioinformatics, and medical device. With knowledge of data management strategies used in major financial institutions, we have produced systems that successfully implement the techniques of data warehousing, multiple concurrent environments and secure dataset access and delivery.
ResultsAs at the end of 2017, we had over 300 registered and approved researchers eligible to request datasets. Using our platform, we have recorded over 150 requests and successfully delivered over 100 de-personalised and encrypted datasets to external researchers around the world. In addition, we have supplied secure datasets to over 20 Global Health MSc and DPhil students studying at The University. The platform currently hosts 4 completed analysis-ready databases with censor dates ranging from 31st December 2013 to 11 years of follow-up as of 31st December 2016. A 5th analysis-ready database (with the most recent outcome data from participants’ death, disease and hospitalisations) is already under development. We plan during 2018 to make available more data sources and outcome data to our external researchers.
Conclusion/ImplicationsWe have developed a versatile platform that delivers secure datasets for researchers from a selection of analysis-ready databases, each with differing censor dates and available data sources. This platform is scalable and can accommodate regular integration of known follow-up data sources along with new and emerging data sources.