bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated KT 2.0: The next generation of teamwork
Authors: Fransoo Randy , Sibley Kathryn 
Published: April 2017

ABSTRACTObjectiveThe goal of this study was to engage members of a long-standing Integrated KT collaborative in a process to revitalize team goals and processes. “The Need to Know” Team started in 2001 in Manitoba, to engage knowledge users in the conceptualization, creation, and application of population health research. The team has garnered numerous national awards and citations for its approach.
We conducted a survey of team members (N=27), representing all Health Authorities in the province, plus provincial government reps. Questions included frequency of data use and medium (print vs online), how well the team is meeting is goals, open-ended questions about how the team could be more useful to members and their organizations, and their top 3 suggestions to ensure the ongoing success and increase the impact of the team.MethodTwenty-two of 27 members responded to the survey (81.5%) within one week. Responses to questions about how well the team is meeting its existing goals revealed high scores – especially among those goals which lay entirely within the scope of the team’s control (91% extremely or moderately well). Objectives relating to larger-scale impacts on the healthcare system had lower ratings (72% extremely or moderately well), as might have been expected. ResultsOver 75% reported that the team’s work had impacted their organization’s work moderately or a lot. The most commonly cited examples were that the work of the team increased capacity for data analysis/interpretation and research (18%), provided results that were used in staff and/or board meetings (15%), influenced decisions and the discussions leading up to them (15%), influenced the development and use of region-relevant quality indicators (13%), and were used in the ongoing education of health professionals (13%). The open-ended questions regarding optimal next steps solicited a variety of suggestions ranging from developing even richer relationships with existing partners, to including a wider variety of partner organizations (e.g. Indigenous groups); aligning team priorities with those of the provincial government (where feasible); and moving to occasional electronic meetings for appropriate content issues and to increase impact in partner organizations.
ConclusionThis exercise in reflection and strategic planning has shown that the team has done an exceptional job in achieving its initial goals, most of which remain relevant, but some of which need revision. More importantly, several creative approaches have been suggested which may increase future impact and enhance both the breadth and depth of the team’s reach.
Reliability of Geneological Cemetery Records in Ascertaining Vital Status in an Historical Cohort Study
Authors: Gwini Stella , MacFarlane Ewan , Benke Geza , Sim Malcolm 
Published: April 2017

ABSTRACTBackground Ascertainment of vital status is a particular challenge in studies of historical cohorts, particularly when the time last known to be alive precedes available and linkable death databases. In Australia, vital status is typically ascertained by linkage to the National Death Index (NDI) which contains detailed information on all deaths occurring after 1 January 1980. While the Australian National Death registry has electronic records dating back to the 18th century searching for deaths prior to this date can only be undertaken on an individual basis by requesting specific death certificates from state/territory registrars of births, deaths and marriages, which is unfeasible for a whole cohort. In the past decade, a number of publically accessible online genealogical databases containing either details of burials/cremations or tombstone inscriptions have become available. While genealogical cemetery records are a potential source of mortality ascertainment, their reliability for this purpose is unknown. We used the Australian NDI, as a gold standard, to assess the reliability of electronic cemetery records in ascertaining vital status in a cohort study.
MethodsIn a historical cohort of former workers employed at a Tasmanian cement factory from 1936, Tasmanian electronic cemetery and tombstone inscription databases were checked for ‘fact of death’ for workers last known to be alive after 01 January 1980 (N=867, 31% of the cohort). The same cohort was also linked to the NDI. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) of cemetery records were calculated.
ResultsThe NDI identified 78 deaths (9%) while we identified 50 deaths (6%) through cemetery record checks. The sensitivity of cemetery matching was low (53.8%; 95% CI 42.2-65.2) while specificity was 99.0% (95% CI 98.0-99.6). Positive and negative predictive values were also good, 84.0% (95% CI 70.9-92.8) and 95.6% (95% CI 94.0-96.9), respectively.
ConclusionsThe results show that deaths identified from electronic cemetery records can be reliable (i.e. high PPV), even though this method correctly identified about half of deaths (i.e. low sensitivity). This methodology can be useful when sources of vital status ascertainment are limited.
CHERISH: Understanding Suicide Clusters tHrough ExploRIng Self Harm behaviours
Authors: Delpozo-Banos Marcos , Hawton Keith , Gunnel David , Lloyd Keith , Scourfield Jonathan , Dennis Michael , John Ann 
Published: April 2017

ABSTRACTObjectivesIn Wales suicide accounts for 20% of deaths among men aged 15-24 years and almost 10% of deaths among women of that age. Up to 2% of suicides in young people are thought to occur in clusters. Yet, our understanding of the social and psychological determinants of suicide clusters is limited, with none of the cross-discipline theories proposed having been tested via in-depth research on an actual cluster. This HCRW funded mixed methods study had qualitative and quantitative data linkage work packages to explore here the factors that trigger a suicide cluster, cause it to continue and then eventually subside.
ApproachThe data of 1866 individuals’ who attended the Princes of Wales Hospital emergency department (ED) with self harm between 1st January 2006 and 31st December 2013 was anonymously linked within the Secure Anonymised Information Linkage (SAIL) databank. We had a matching rate of 99.7. We performed both time-trend analysis on this data around the apparant suicide cluster in 2007-08, and a comparison across three defined populations: those attending ED at the time of the cluster; those attending during the same period, one year before; and those attending one year after.
ResultsWe are able to present the characteristics of those who attend ED during a cluster with self harm compared to those who attend at other times and their long term outcomes.
ConclusionTo inform the development of appropriate policy to respond to suicide clusters at an early stage.
The effect of ultraviolet radiation on birth weights and gestational length in a scottish birth cohort
Authors: Clemens Tom , Lauren Megaw , Dibben Chris , Stock Sarah , Weller Richard 
Published: April 2017

ABSTRACT
ObjectivesOutcomes at birth such as prematurity and birthweight are important determinants of later life health and social outcomes including education attainment, cognitive and behavioural development and a large number of health outcomes. Recently, it has become clear that characteristics of the physical environment, including air pollution, plays an important role in mediating outcomes of pregnancy. Vitamin D deficiency from lack of sunlight has also shown associations with pregnancy outcomes but this has not been replicated in intervention studies of vitamin D supplementation. Recent clinical evidence has pointed to a sunlight pathway that is independent of vitamin D, which instead mediates blood pressure through the production of Nitric Oxides in the skin from exposure to the UVA component of sunlight. This pathway might explain the lack of association with vitamin D supplementation and provides a plausible pathway for direct effects of sunlight exposure for pregnancy outcomes. In this study, we examined the effect of exposure to sunlight during pregnancy hypothesising that higher levels of exposure might reduce risks of premature birth and low birthweight.
ApproachWe used routinely collected maternity health data covering all births in Scotland in the period 2000-2010 (~ 550000 births). Using the mothers residential postcode at birth we attached estimates of UV exposure for each trimester of pregnancy based on a combination of MET office spatially detailed sun hours data and satellite derived solar insolation data. We modelled the effect of UV exposure for birthweight and risk of preterm birth with adjustment for confounding variables including smoking, parity and maternal stature. Sensitivity analysis using sibling pairs with discordant UV exposures was also explored to test the robustness of the findings to residual confounding.
ResultsResults are not available at time of writing but will be available for the conference presentation and will discuss the effects of UV exposure for both the risk of premature birth and low birthweight.
ConclusionsTogether with clinical evidence, findings from this study may serve to highlight a possible need to revisit public health advice regarding reducing UV exposure during pregnancy and may provide evidence for possible interventions including sun lamp therapy for pregnant mothers.
Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
Authors: Boyd Andy , Cornish Rosie , Provis Jennifer , Teyhan Alison , Macleod John 
Published: April 2017

ABSTRACT
Objectives“Clearly, details about an individual’s mental health, for example, are generally much more ‘sensitive’ than whether they have a broken leg.”
UK Information Commissioners Office
There is a perceived wisdom – based on issues such as social taboos, religious sensitivities, or financial implications linked to health status – that some health data is more sensitive than others. This distinction is present in many of the regulatory interpretations of privacy law (e.g. the UK Information Commissioners Office interpretation of the EU Data Directive, illustrated above), and is factored into the thinking of ethics and other regulatory decision-making committees. However, these particularly ‘sensitive’ data are defined at a regulatory level in broad terms (e.g. mental health), yet need implementing by researchers in precise terms. In 2013 our longitudinal research study was given approval by the UK Secretary of State for Health to access identifiable patient health records with the exception of those relating to mental health, sexual health or termination of pregnancy. Our objective therefore was to develop a generalisable informatics approach which enabled us to filter out sensitive records at the point of extraction.
ApproachWe developed a methodology based on the Cochrane systematic review approach: firstly using internationally recognised definitions of health concepts and reference texts (e.g. British National Formulary drug manual) we identified keywords associated with sensitive health events (including symptom and diagnostic terms, drug and appliance codes, community and secondary care references); secondly, through data-mining code terminologies – using both code terms and information embedded within the structure of the schema itself - we identified code values relating to these terms; thirdly we minimised our results through filtering out spurious results via manual review; finally, the resulting code lists were then crossed-referenced with other terminologies to ensure interoperability.
ResultsWe produced separate definitions of mental health and sexual health events initially using Read codes. Using NHS cross-reference tables we were able to translate Read observation and diagnostic codes to the SNOMED CT vocabulary, but were unable to translate Read drug codes into the SNOMED/DM+D vocabulary.
ConclusionWe have demonstrated a systematic and partially interoperable approach to defining ‘sensitive’ health information. However, any such exercise is likely to include decisions which will be open to interpretation and open to change over time. As such, the application of this technique should be embedded within an appropriate governance framework which can accommodate misclassification while minimising potential patient harm.
PATHS Data Resource: A population-based suite of linkable administrative records and metadata for population health research
Authors: Nickel Nathan , Brownell Marni , Chateau Dan , Katz Alan , Burland Elaine 
Published: April 2017

ABSTRACT
ObjectivesOur objective was to develop a comprehensive longitudinal data resource, which population health research scientists could use to study the social determinants of child health and health equity.
MethodsThe PATHS Resource was created from data holdings within the Manitoba Population Health Research Data Repository. The Manitoba Health Registry sits at the centre of the Repository and includes information – including a scrambled personal health identification number (PHIN) and date when coverage commenced and expired – on every individual registered with the province’s universal healthcare system. The Repository also includes administrative data spanning several sectors including health, social services, justice, and education. We used individuals’ scrambled PHINs to link children’s administrative records across sectors to build a holistic picture of their health and development. We developed metadata, including routinized SAS algorithms and variable definitions, to ensure consistent operationalization of variables across studies. The longitudinal nature of these data allowed us to construct individual-level health and development trajectories from birth through adolescence for children born from 1984-2014. We used income data from the Canadian Census to develop both indicators of socioeconomic status (average neighbourhood level income) and provincial measures of income inequality (the Gini coefficient).
ResultsThe PATHS Resource includes data on the social determinants of health as well as health and development for children born 1984 to 2014 (n=608,007). We are able to follow children for a median observation period of 15.4 years. Income inequality – measured using the Gini coefficient – increased from 1984 to 2014: 0.16 to 0.21 (p<0.01). The proportion of children born to women from the bottom income quintile (i.e., the poorest 20% of families) also grew from 23.2% in 1984 to 27.2% in 2014 (p<0.01). When we followed children over their life course, we found that they were most likely to experience poverty (measured by family receipt of income assistance) at 2 years of age (p<0.01). Many studies from a variety of researchers have utilized the PATHS metadata to conduct child health and development research, ensuring consistent variable operationalization. These data have been used to identify policy levers for improving child health and reducing health inequalities.
ConclusionA resource such as the PATHS Resource can facilitate research into the health and development of children. Having data on the entire population allows investigators to both monitor trends in health inequities and identify strategies for improving health. Metadata ensure variable consistency and comparability across studies.
Patient-level data linkage across ambulance services and acute trusts: assessing the potential for improving patient care
Authors: Clark Sophie , Damiani Michael , Dorning Holly , Halter Mary , Porter Alison 
Published: April 2017

ABSTRACT
ObjectivesThe potential of linked healthcare data to support improvements to the care quality, efficiency and service planning is recognised by the Department of Health and NHS England. UK ambulance services however, have little information regarding the outcome of patients as there is no routine data sharing. An urban ambulance service has previously piloted linked data with one acute trust. The Pre-Hospital Emergency Department Data Linking Project (PHED Data) aims to assess the potential opportunities for and challenges to routinely linking data for several sites. It aims to define what indicator sets can be developed from these linked data, with a view to informing commissioning and improvement of healthcare delivery.
ApproachThe project is a two-year mixed-methods observational study, funded by the Health Foundation, working with six acute trusts of various size and CQC-derived performance, to carry out six work packages.
Work package one uses liaison activities with trust senior staff to negotiate information sharing agreements, and a learning log to enable an economic assessment of the set-up costs.
Work packages two to five analyse ambulance response time, referrals from healthcare professionals, ED mortality, and frequent ED diagnoses, respectively, exploring relationships with ED outcomes, quantitatively. Qualitative analysis will explore, with staff groups, how the findings might influence commissioning and pre-hospital care.
Work package six will examine commissioning decisions and patient care, through interviews with commissioners and performance managers.
ResultsIn work package one, we have successfully negotiated overall research ethics and governance approval, involving in-depth discussion about definitions of identifiable patient data, and protecting against potential re-identification. We have recruited six acute trusts, comprising 13 hospital sites, for whom equivalent data is available. We have been working for six months in liaison with these Trusts to deliver information sharing agreements (three are currently approved) and data transfer, working with research governance, information governance and clinical staff. The processes have varied, with intra-Trust co-dependencies introducing delays and non-linear processes being common.
For work packages two to five, some data analysis will be available for presentation at the conference.
ConclusionThis project has the potential to shed light on the practicalities of data linkage for health service providers who face similar challenges with patient data held in multiple organisations.
The study also anticipates being able to recommend quality improvement to support the development of new pathways in pre-hospital care.
Data linkage and statistical modelling to provide stratified risk assessment for HAI
Authors: Kavanagh Kim , Pan Jiafeng , Robertson Chris , Bennie Marion , Marwick Charis , McCowan Colin 
Published: April 2017

ABSTRACT
ObjectivesThe use of “real-time” data to support individual patient management and outcome assessment requires the development of risk assessment models. This could be delivered through a learning health system by the building robust statistical analysis tools onto the existing linked data held by NHS Scotland’s Infection Intelligence Platform (IIP) and developed within the Scottish Healthcare Associated Infection Prevention Institute (SHAIPI).
This project will create prediction models for the risk of acquiring a healthcare associated infection (HAI), and particular outcomes, at the point of GP consultation/ hospital admission which could aid clinical decision making.
ApproachWe demonstrate the capability using the HAI Clostridium difficile (CDI) from 2010-2013. Using linked national individual level data on community prescribing, hospitalisations, infections and death records we extracted all cases of CDI and by comparing to matched population-based controls, examined the impact of prior hospital admissions, care home residence, comorbidities, exposure to gastric acid suppressive drugs and antibiotic exposure, defined as both cumulative (total defined daily dose (DDD)) and temporal antimicrobial exposure in the previous 6 months, to the risk of CDI acquisition. Antimicrobial exposure was considered for all drugs and the higher risk broad spectrum antibiotics (4Cs). Associations are assessed using conditional logistic regression. Using cross-validation we assess the ability of the model to accurately predict CDI infection. Risk scores for acquisition of CDI are estimated by combining these predictions with age and gender population incidence.
ResultsIn the period 2010-2013 there were 1446 cases of CDI with matched 7964 controls. A significant dose-response relationship for exposure to any antimicrobial (1-7 DDDs OR=2.3 rising to OR=4.4 for 29+ DDDs) and, with elevated risk, to the 4C group (1-7 DDDs OR=3.8 rising to OR=17.9 for 29+ DDDs). Exposure elevates CDI risk most in the month after prescription but for 4C antimicrobials the elevated risk remains 6 months later (4C OR=12.4 within 1 month, OR=2.6 4-6 months later). The risk of CDI was also increased with more co-morbidities, previous hospitalisations, care home residency, increased number of prescriptions, and gastric acid suppression.
ConclusionDespite limitations to current application in practice,(paucity of patient level in-hospital prescribing data and constraints of the timeliness of the data), when fully developed this system will enable risk classification to identify patients most at risk of HAI and adverse outcomes to aid clinical decision making.
Linked Data Paves the Way to Improved Health Care
Authors: Gaucher Michael , Nielsen Britta , Gapanenko Katerina 
Published: April 2017

ABSTRACTObjectivesOur organization links data from health care organizations and health ministries across Canada to create new knowledge. The new knowledge supports system and policy-decision makers in answering questions about the health or healthcare of population groups or healthcare sectors. This presentation provides an overview of recent analytical products that incorporate a variety of approaches to linking data.
ApproachKey success factors in data linkages are the use of standards and robust methodologies. Standardized data can be linked at the individual level across hospital, long-term care, home care and community settings. Expanding knowledge about a specific sector can be achieved by linking physician billing, drug, and financial data. Linking clinical and financial data at the person and/or organization level provides insight into the cost of providing services, laying the foundation for examining efficiency and value for money. Data may also be used in non-traditional ways, for example, using payment data linked to clinical data to better understand how services are provided in various settings and to identify best practices.
ResultsResults from these studies demonstrate how linked data creates new knowledge: 1) Hospital, emergency, and drug data were linked to show the number of emergency visits, hospitalizations, and the use of psychotropic medications by children and youth with mental health disorders are increasing, especially for those with mood and anxiety disorders living in urban areas. 2) Physician billing data was linked with hospital and emergency data to show that increased continuity of care with a family physician is associated with reductions in hospitalizations for people with chronic diseases and reductions in ED visits for people with conditions better managed in primary health care settings. 3) Drug data was linked with clinical assessment (InterRai) data to show that a large proportion of seniors living in long-term care exhibiting severe aggression were not being treated with antipsychotics, suggesting non-drug alternatives were often considered. 4) Financial data was linked with hospital clinical data to calculate an efficiency indicator that can be used at a system level to examine variation, and by individual managers to identify areas for further investigation and manage trends in spending.
ConclusionThis presentation demonstrates how new knowledge created using linked data can inform decision and policy makers, and lead to action within the health system. Several examples are presented to illustrate the approach and types of data being linked.