bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Linked Data and Advanced Analytics to Prioritize Health Concerns within Regions
Authors: Powell Guido Antonio , Lavigne Maxime , Yuan Mengru , Okhmatovskaia Anya , Boston-Fisher Nikita , Buckeridge David 
Published: September 2018

IntroductionLinked population health data have the potential to inform evidence-based actions targeting serious public health concerns. However, large-scale data integration efforts can produce hundreds of population health indicators, which can overwhelm the ability of decision-makers to synthesize and interpret the information.
Objectives and ApproachOur research uses an existing semantic web application for population health surveillance, the Population Health Record (PopHR). PopHR automates a computational pipeline for linking data sources, building timely population health indicators, and uses artificial intelligence to organize indicators along a determinants of health framework. To assist users in interpreting the thousands of indicators, we developed computational algorithms combining values of multiple indicators across chronic diseases, to prioritize conditions within each region. This analytic approach can assist regional decision-makers in identifying their region’s priority conditions by facilitating the integration and analysis of multiple types of indicators (e.g. disease burden, temporal patterns).
ResultsA pilot implementation of the regional prioritization algorithm focused on indicators defined in the Public Health Agency of Canada’s Chronic Disease Indicators Framework. Within this subset of diseases, we developed a computational algorithm to integrate into a priority index regional estimates of incidence, mortality, and prevalence taking into account the relative importance of each indicators’ outlier status and statistical significance of temporal trends. Our results allowed for the development of region-specific data visualizations dashboards, emphasizing the different factors driving the rankings of indicators within and across regions. For example, regions with higher socioeconomic status having generally lower disease burden are presented with visualizations emphasizing temporal trends and other statistically compelling patterns rather than simple indicators of magnitude.
Conclusion/ImplicationsThis ranking approach represents initial stages ongoing research, expanding our methods to use machine learning strategies and additional expert knowledge. Current and future prioritization analyses within the PopHR platform offer the potential for public health to gain insights from an otherwise challenging complexity and richness of linked data.
Applications of Big Data Analytics within a Dynamic Simulation Modeling Platform to Inform Osteoarthritis Care in Alberta
Authors: Sharif Behnam , Vik Shelly , Marshall-Catlin Deborah A 
Published: September 2018

IntroductionOsteoarthritis (OA) is a leading cause of chronic disability. There is need to leverage administrative data to support OA policy analysis. Our objective was to develop and apply a multidimensional data cube as an input parameter repository using health administrative data to populate an OA simulation model.
Objectives and ApproachHealth administrative data including practitioner claims, inpatient and ambulatory visits from 1994 to 2013 were integrated into a multidimensional data cube. OA cases were identified using validated algorithms, and followed through stages of care (primary, specialist, acute and post-operative). The cube provided rate calculations, duration and average cost for each stage of care across the model dimensions (age categories, sex, comorbidity status and geographic zones). The rates were then linked to the model as input parameters to simulate patient flow across the continuum of care. We used the model to predict direct costs across all dimensions from 2010 to 2035.
ResultsUsing the model, total number of patients with OA in Alberta will increase from 312,000 in 2010 to 1.4 million in 2035. The average annual cost per OA patient also increases from $2,800 to $4,900, and the total cost increases from $450 million in 2010 to 2.2 billion in 2035. The majority of the patients were at earlier stages (non-surgical 78%, surgical 22%), with lower average cost (non-surgical $3,300 vs. surgical $16,400) in 2010. As new administrative data are being provided routinely, the data cube is capable of providing real-time updates for the input parameters of the model, which will aid in validation of the model results and improving the precision of projections.
Conclusion/ImplicationsThe data cube has significantly improved our ability to manage and analyze administrative data within a simulation model to project the burden of OA in Alberta. The integrated model can be used as a real time decision-support tool to inform osteoarthritis service planning and variations in resource utilization.
Understanding the social determinants of opioid related hospitalizations
Authors: Sanmartin Claudia , Carriere Gisele 
Published: September 2018

IntroductionThe current opioid crisis is recognized by governments at many levels as an urgent priority. While there is basic demographic information on who experiences opioid related adverse events, there is little information to provide a more fulsome profile of those experiencing these events for targeted intervention and forward projection estimation.
Objectives and ApproachThis study is the first to use a nationally-representative Census of Population linked with health administrative data to examine opioid-related hospitalization patterns across income and Aboriginal status.
ResultsPreliminary analyses using 2006 Census-hospital linked database found cohort rates of opioid-related hospitalizations are up to 7 times higher among Aboriginal youth, and also for young adults (12-19/ 20-24) compared with non-Aboriginal youth or young adults. Rates among these youth living on reserves were 8.4 times higher; among those off reserve 8.7 times higher. Rate among all youth living in lower income households was 5 times higher compared with those living in highest income households, For Aboriginal persons in lowest income quintile, the rate was 3 times higher relative to non-Aboriginal persons in same quintille.
Conclusion/ImplicationsNew linked health data reveal new information regarding the profile of those who experienced opioid-related adverse events. This information will serve to inform targeted intervention strategies, models for forward estimation of events.
UK and Canadian Gulf War Veteran Mortality: Using A Fellow Military Cohort as a Comparison Population
Authors: Rolland-Harris Elizabeth , Harrison Kate , Simkus Kristen , Baird Lisa , Palmer Kate , Sandra Dear , VanTil Linda 
Published: September 2018

IntroductionTo compare 1990-91 Gulf War Veterans (GWV) survival outcomes with a comparable cohort, UK’s Ministry of Defence and Canada’s Department of National Defence combined data from their respective cohorts. The survival estimates/comparisons emanating from this collaboration will be novel as they will control for healthy worker/soldier effect (HW/SE).
Objectives and ApproachGWV cohort building and record linkage methods used by Canada and the UK are described in more detail elsewhere. To ensure comparability in mortality outcomes between cohorts, the following steps will be conducted prior to analysis:

ICD-9 causes of death (COD) will be recoded to ICD-10; recoding by each country will be cross-validated by the other, to ensure high inter-coder reliability;
CODs will be analysed at the ICD-chapter level;

Calculated age- and sex-specific rates will be directly standardized using the WHO 2012-2022 Standard Population. Cox proportional hazards will be used to compare survival between cohorts.
ResultsWe are currently in the process of completing this exciting cross-sectoral linkage study and expect to have preliminary results to present. To our knowledge, this will be the first time that mortality outcomes for two discrete Gulf War veteran cohorts (ascertained by record linkage) will be analytically compared, rather than comparing to the general population. These findings will not only provide a more recent evaluation of the health status of GWV in Canada, but will also be a rare opportunity to control for the HW/SE, using comparisons with non-equivalent cohorts (e.g., general population, other deployment) cannot achieve.
Conclusion/ImplicationsBeyond evidence of a strong inter-sectoral research relationship between military nations, these findings also represent a feasible solution to controlling for the HW/SE. The ability to control for this will mean more accurate UK and Canada GWV mortality/survival estimates than either country can generate on their own.
Enhancing Environmental data Resources in Cohort Studies: ALSPAC exemplar (ERICA)
Authors: Boyd Andy 
Published: September 2018

IntroductionNovel data platforms are needed to expedite the linkage of geospatial and natural environment data with longitudinal population study(ies) (LPS) data. However, the intrinsic relationship between geospatial data and participant identities raises confidentiality concerns amongst participants which need to be accommodated within platform designs to ensure acceptable data use.
Objectives and ApproachWe aimed to establish generalisable mechanisms for linking spatial records into a cohort study LPS databank. Using ‘Data Safe Haven’ (Burton et al. 2015) approaches we developed a pipeline of technical processes (e.g. geocoding participants’ residential and school address records, developing an ‘engine’ for linking exposure data to LPS data), which we tested for participant acceptability (through a focus group testing acceptable use of personal identifiers in this context) and tuned to meet regulatory requirements (e.g. privacy impact assessments, information security accreditation). We demonstrated our approach through an exemplar investigation assessing in utero NO2 exposure with later childhood respiratory outcomes.
ResultsParticipants’ expressed clear expectations that the research use of location data should be restricted to trusted study staff (as distinct from the wider research community), although this expectation is context specific and does not represent a carte blanche for using granular information (e.g. GPS tracing data). This necessitated a ‘split stage’ protocol, where personal identifiers are handled separately from data/analysis. Daily NO2 exposure was modeled using road, other local and regional records; with validation exposure data collected from city-based sensors. Participants’ location information was geocoded and linked to NO2 using the ALGAE (ALorithms for Generating address histories and Exposures) privacy-preserving geocoding engine. We will summarise participant views, our exemplar findings, and describe the linkage engine we have developed and its availability via an open-source repository.
Conclusion/ImplicationsParticipants’ expect that studies control for confidentiality risks introduced by research using spatial identifiers. It is not realistic to expect that all LPS have the capacity to undertake specialist spatial linkages. Our generalisable approaches and open-source software could provide the basis for geospatial and natural environment epidemiology platforms in LPS.
Advancing cross-centre research networks: learning from experience, looking to the future
Authors: Jones Kerina , Heys Sharon , Daniels Helen 
Published: September 2018

IntroductionMany jurisdictions have programmes for the large-scale reuse of health and administrative data that would benefit from greater cross-centre working. The Advancing Cross centre Research Networks (ACoRN) project considered barriers and drivers for joint working and information sharing using the UK Farr Institute as a case study, and applicable widely.
Objectives and ApproachACoRN collected information from researchers, analysts, academics and the public to gauge the acceptability of sharing data across institutions and jurisdictions. It considered international researcher experiences and evidence from a variety of cross centre projects to reveal barriers and potential solutions to joint working. It reviewed the legal and regulatory provisions that surround data sharing and cross-centre working, including issues of information governance to provide the context and backdrop. The emerging issues were grouped into five themes and used to propose a set of recommendations.
ResultsThe five themes identified were: organisational structures and legal entities; people and culture; information governance; technology and infrastructure; and finance and strategic planning. Recommendations within these included: standardised terms and conditions including agreements and contractual templates; performance indicators for frequency of dataset sharing; communities of practice and virtual teams to develop cooperation; standardised policies and procedures to underpin data sharing; an accredited quality seal for organisations sharing data; a dashboard for data availability and sharing; and adequate resource to move towards greater uniformity and to drive data sharing initiatives.
Conclusion/ImplicationsThe challenges posed by cross-centre information sharing are considerable but the public benefits associated with the greater use of health and administrative data are inestimable, particularly as novel and emerging data become increasingly available. The proposed recommendations will assist in achieving the benefits of cross-centre working.
Mortality among single fathers as compared with single mothers and partnered fathers: a cohort study
Authors: Chiu Maria , Rahman Farah , Vigod Simone , Lau Cindy , Cairney John , Kurdyak Paul 
Published: September 2018

IntroductionSingle-parent families are becoming increasingly common around the world with a particularly steep rise in households headed by single fathers. Research suggests that single parenthood is associated with adverse outcomes, however, little is known about the health profile or risk of death of single fathers compared to other parents.
Objectives and ApproachWe aimed to examine mortality risk in single fathers compared to single mothers and partnered parents, which is the first head-to-head comparison of single and partnered parent groups. Our population consisted of 871 single fathers, 4590 single mothers, 16,341 partnered fathers and 18,688 partnered mothers. We combined cross-sectional samples derived from the Ontario component of Statistics Canada’s Canadian Community Health Survey (2001 to 2012) linked to health administrative databases to identify medical conditions, health service use, all-cause mortality and cause of death. We investigated differences in mortality using Cox proportional hazards models adjusted for socio-demographic characteristics, lifestyle and clinical factors.
ResultsEach family group was followed up for a median of 11.10 years (IQR 7.36–13.54). Single fathers had a poor risk profile, particularly among lifestyle factors, such as low fruit and vegetable consumption and alcohol consumption. The mortality rate was three-fold higher for single fathers compared to single mothers and partnered fathers (5.81, 1.74 and 1.94, respectively). Even after adjustment, single fathers had a significantly higher risk of death compared to both single mothers (hazard ratio (HR): 2.49 (95% CI: 1.20 – 5.15, p=0.01)) and partnered fathers (HR: 2.06 (95% CI: 1.11 – 3.83, p=0.02). Small sample sizes precluded us from identifying the leading cause of death for single fathers.
Conclusion/ImplicationsWe found that single fathers had the least favorable risk factor profile and greatest risk of mortality, which may be mitigated by physician intervention. Our study highlights that through cross-sectoral data linkages we can further advance our knowledge of social factors and their profound effects on health.
The Overlap Between the Child Welfare and Youth Justice Systems in Manitoba, Canada
Authors: Brownell Marni , Nickel Nathan , Turnbull Lorna , Au Wendy , MacWilliam Leonard , Ekuma Oke , Valdivia Jeff , McCulloch Scott , Lee Janelle Boram 
Published: September 2018

IntroductionManitoba has one of the highest rates of children taken into care of child welfare services (Child and Family Services; CFS) in the world, and also one of the highest youth incarceration rates in Canada. Policy-makers recognize there is overlap between these systems; the extent of that overlap is unknown.
Objectives and ApproachWe linked CFS, Justice, and Population Health Registry data to quantify the overlap between having a history of CFS during childhood (0-17 years) and being charged with a crime as a youth (12-17 years). Using a cohort approach, we selected all individuals in Manitoba who were born in 1988 (N=28,178); those not in the province at any time from 12-17 years were excluded, leaving a final cohort of 18,182. The cohort was divided into 3 groups according to CFS involvement: CFS out-of-home care (1,148); CFS in-home services (3,395); no CFS (13,639). Criminal charges between 12-17 years were identified.
Results6.3% of our cohort had CFS out-of-home care, 18.7% received CFS in-home services, and 75% had no CFS involvement. 10.5% of the cohort were charged of a crime between 12-17 years. Almost half (46.6%) of youth who had CFS out-of-home care had criminal charges, compared to 19.4% of youth who had CFS in-home services, and 5.3% of youth with no CFS. Despite accounting for only 6.3% of the cohort, youth who had out-of-home care accounted for 28.0% of youth with criminal charges. Indigenous (First Nations (FN) and Metis) children/youth were over-represented in both systems; for example, 24.5% of FN youth had been in care compared to 3.1% of non-Indigenous; and 32.2% of FN youth were charged with a crime compared to 6.6% of non-Indigenous youth.
Conclusion/ImplicationsThere is substantial overlap between the child welfare and youth justice systems, with overrepresentation of Indigenous youth in both systems. Culturally appropriate programs and policies aimed at supporting parents, families and communities to care for their own children will likely have long-term positive impacts on the youth justice system.
Population survival impact of new targeted and immune based therapies for metastatic or unresectable melanoma
Authors: Nguyen Paul , Baetz Tara , Booth Christopher , Eisenhauer Elizabeth , Hanna Timothy 
Published: September 2018

IntroductionNew classes of drugs for metastatic or unresectable melanoma (MM) have shown improved survival in randomized trials (e.g., anti-CTLA-4, anti-PD-1, BRAF/MEK inhibitors). We sought to describe uptake of these new drugs and their impact on population-based survival outcomes of MM.
Objectives and ApproachWe sought to describe uptake of these new drugs and their impact on population-based survival outcomes of MM. This was a retrospective, population-based cohort study of all treated MM in Ontario 2007-2015. Administrative data sources from the Institute for Clinical Evaluative Sciences (ICES) were utilized. Within ICES, cutaneous and non-cutaneous primaries were identified in the Ontario Cancer Registry. Administrative sources from Cancer Care Ontario, Ministry of Health and Long-Term Care, and Canadian Institute for Health Information identified patients treated with palliative systemic therapy, radiotherapy and metastatectomy. Temporal trends in utilization and survival were investigated. Survival by drug class was described.
ResultsWe identified 2,793 MM patients. First treatment was systemic therapy (46%), radiotherapy (41%) or metastatectomy (14%). MM patient number increased from 270 in 2007 to 418 in 2015. Systemic treatment rose from 125 MM first treated in 2007 to 343 in 2015. New drug treatments increased from <6% of reported first-line regimens in 2007 to 82\% in 2015. 1-year and 2-year overall survival (OS) was 28% and 15% respectively for all MM in 2007-2009, rising to 46% and 35% for 2014-2015 (logrank p<0.001; adjusted hazard ratio (AHR) 0.56, 95% confidence interval (CI): (0.49,0.63)). Survival gains were largely in the subset treated primarily systemically, where new drugs were increasingly utilized (2-year OS 16% 2007-2009 vs. 44% 2014-2015 logrank p<0.001; AHR 0.46, 95% CI: (0.38,0.56)).
Conclusion/ImplicationsUtilization of systemic therapy for MM has increased considerably in routine practice during 2007-2015; at least some of this increase relates to use of novel agents since 2011. In line with randomized trial findings, new drug adoption was associated with substantial increases in population-based MM survival.
Analysing complex linked administrative data in health services research: Issues and solutions
Authors: Rachael Rachael , David David , Harris Mark 
Published: September 2018

IntroductionLinked administrative data are increasingly being used to evaluate the impact of health policy on health-service use/cost because they can comprehensively capture whole of population interactions with the health system. These analyses are complex comprising unbalanced panels and are at risk of endogeneity and associated problems.
Objectives and ApproachWe evaluated the impact of changes in regularity of general practitioner contact on diabetes related hospitalisation before and after care coordination policies using whole of population, person-level linked primary care, hospital, Electoral Roll and death records. Complex panel random-effects modelling techniques were required due to the unbalanced structure of the data (individuals could exit and re-enter the study repeatedly), over-dispersion and high proportion of zeros, changes in availability of tests (ascertainment bias), the likelihood of prior health service use influencing the dependent variable (initial conditions and simultaneity/reverse causality bias) and likely correlation of observed and unobserved variables.
ResultsMultivariable zero-inflated negative binomial and Cragg-hurdle clustered robust regression, which include separate components to model zero and non-zero outcomes, were required for these data. Mundlak variables (group-means of time-varying variables) were used to relax the assumption in the random-effects estimator that the observed variables were uncorrelated with the unobserved ones. Prior health service use was adjusted for using 4-year lags of GP contact and one-year lag of hospitalisation. The initial value of the dependent variable resolved the “initial condition” problem. Ascertainment bias was addressed using the number of years available for identification for each person as a covariate. AIC/BIC values were used to identify the best model. We found that more regular GP contact was associated with fewer hospitalisations, however this attenuated over time.
Conclusion/ImplicationsAvailability of linked data, together with increases in computing power, has vastly increased its potential for use. This has also increased the complexity of analyses being undertaken necessitating recognizing and addressing problems, such as endogeneity, that arise due to the observational nature of the studies undertaken.