bluuebunny/crossref_metadata_2025 huggingface dataset:
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.
Developing a Primary Care EMR-based Frailty Definition using Machine Learning
Authors: Aponte-Hao Sylvia , Mele Bria , Jackson Dave , Katz Alan , Leduc Charles , Lethebe Brendan , Wong Sabrina , Williamson Tyler
Published: September 2018

IntroductionFrailty is a geriatric syndrome that is predictive of heightened vulnerability for disability, hospitalization, and mortality. Annually an estimated 250,000 frail Canadians die, and this estimate is expected to double in the next 40 years, as Canadians grow older. Currently there is no single accepted clinical definition of frailty.

Objectives and ApproachThe objective of this study was to develop an operational definition of frailty using machine learning that can be applied to a primary care electronic medical record (EMR) database.

The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is a pan-Canadian network of primary care practices that collect de-identified patient information (such as encounter diagnoses, health conditions, and laboratory data) from EMRs.

780 patients from CPCSSN have were randomly selected and assessed by physicians using the Rockwood Clinical Frailty Scale (as frail or not frail), and their clinical characteristics from CPCSSN used to develop the definition using machine-learning.

ResultsA total of 8,044 clinical features were extracted from these tables: billing, problem list, encounter diagnosis, labs, medications and referrals. A chi-squared automatic interaction detector (CHAID) approach was selected as the best approach. The bootstrapping process used a cost matrix that prioritized high sensitivity and positive predictive value. 10-fold cross validation was used for validity measures. Key features factored into the algorithm included: diagnosis of dementia (ICD-9 code 290), medications furosemide and vitamins, and use of key word “obstruction” within the billing table. The validation measures with 95% confidence intervals are as follows: sensitivity of 28% (95% CI: 21% to 36%), specificity of 94% (95% CI: 93% to 96%), positive predictive value of 53% (95% CI: 42% to 64%), negative predictive value of 86% (95% CI: 83% to 88%).

Conclusion/ImplicationsNo other primary care specific frailty screening tools have sufficient validity. These results suggest heterogeneous diseases require clearly defined features and potentially more sophisticated algorithms to account for heterogeneity. Further research utilizing continuous features and continuous frailty scores may be more suitable in the creation of a case detection algorithm.
Cross-Sectoral Data Linkage: Tracking Mental Health Service Utilization from Childhood into Adulthood
Authors: Schraeder Kyleigh , Cairney John , Carter Jeffrey , Vingilis Evelyn , Neufeld Richard , Barwick Melanie , Kurdyak Paul , Tobon Juliana
Published: September 2018

IntroductionOf the 15-18% of children and youth in Canada with a mental health disorder, some receive specialized mental health (MH) services and need additional treatment as young adults. Lack of a shared database across child and adult sectors has prevented examining predictors of future MH health service use.

Objectives and ApproachWe examined predictors of mental health service utilization in adulthood, and compared a sample of youth who received specialized MH treatment and age-, sex-, and region- matched controls. Patient-level administrative data from five MH agencies funded by the Ministry of Children and Youth Services (MCYS) in Ontario, with population health sector datasets held at the Institute for Clinical Evaluative Sciences (ICES). We expanded previous definitions of coding a MH visit by including codes specific to long-lasting childhood MH diagnoses (e.g., Attention Deficit-Hyperactivity Disorder).

ResultsOur match rate for linking the MCYS treated youth with their population health data was 77%. Youth who received MH treatment (N= 2957) were twice as likely as matched controls (N= 8891) to have a MH visit in the medical system in adulthood (i.e., after age 18). The most common diagnostic codes for the first visit were anxiety, depressive disorders, and ADHD. The median survival time (when 50% had a visit) from age 18 to first MH visit was 3.3 years. In adjusted Cox regressions, significant predictors of having an adult MH visit included service use history in both medical and MH systems during childhood and adolescence (e.g., ongoing pattern of children’s MH service use).

Conclusion/ImplicationsThis study represents the first longitudinal, case-control cohort study in Canada to examine MH service utilization in the medical sector by youth treated for MH problems. The linkage of information from multiple datasets allowed for a broader understanding of MH service utilization across sectors of care, specific to children and youth.
Correspondence between self reported and GP coded alcohol consumption
Authors: Greene Giles , Trefan Lazlo , Farewell Daniel , Paranjothy Shantini , Akbari Ashley , Fone David
Published: September 2018

IntroductionSelf reported data on health is often burdensome and expensive. Administrative data provides inexpensive global coverage of health and is less prone to social desirability for behaviors such as alcohol consumption. Recent studies have found varying correspondence between self-reported and administrative data for a number of chronic and acute conditions.

Objectives and ApproachWe sought to test the agreement between self-rated heavy drinking (35+ units for women, 50+ for men) and primary care physician (GP) coded (Read mapped ICD-10 codes) heavy drinking, and their association with alcohol related hospital admissions.

We assessed agreement between self-reported and GP coded heavy drinking data, from a prospective UK cohort and linked GP and hospital data using Cohen's kappa (95% CI). Then using Cox regression we the compared the time to alcohol related admission for both. Goodness-of-fit was assessed using AIC.

ResultsOf the 10,892 participants a total of 6,609 were linkable to both the Hospital Admissions database (PEDW) and the GP practice data, with no systematic differences between those linked and not. The sample were mostly female (57%) with a mean age of 48.2 years (SD = 15.5). In total there were 81 alcohol related admissions, with 2.7% classified as heavy drinkers by GPs and 31.7% self-rated. There was poor agreement between raters (K=0.044; 95% CI = 0.037, 0.050). GP coded heavy drinking was strongly associated with admission (β = 1.90 95% CI 1.34, 2.58, AIC = 1350.71), as was self-rating (β = 1.14 (5% CI 0.67, 1.62, AIC = 1358.19).

Conclusion/ImplicationsThe low levels of agreement but similar AICs suggest that self-rated and GP classification are measuring a similar construct but at different levels. This analysis suggest that routinely collected GP ratings of heavy drinking may be a cheaper and more efficient method of assessing heavy drinking at a population level.
Ontario’s stroke report cards: Cross-continuum data linkage allows evaluation of system of care
Authors: Hall Ruth , Khan Ferhana , Levi Jen , Ma Huiting , Martin Cally , Moher Cheryl , Kelloway Linda , Linkewich Elizabeth , Bayley Mark
Published: September 2018

IntroductionReport cards or scorecards typically reflect one particular sector along the care continuum; however, stroke patients typically require acute care, inpatient rehabilitation and community care highlighting the need to link data sources to demonstrate the interdependencies between and across sectors.

Objectives and Approach1) Identify stroke best practice indicators from across the care continuum; 2) develop a one page report card that reports on the quality of the stroke system of care through data linkage and 3) visually impactful knowledge translation tool. The indicators cover five health care sectors starting with pre-hospital stroke symptom onset, then to management of the acute event, to institutional and community-based rehabilitative care, reintegration into the community and secondary prevention. The report card is a knowledge translation tool that identifies gaps in best practice, provides achievable benchmarks of regional and provincial stroke system performance to drive system change.

ResultsUsing data linkage techniques, seven administrative datasets are used to populate the 20 indicators in the annual Ontario stroke report card. Indicator performance was trended by comparing the previous 3 years’ results to the most recent year of data. Fifteen of 17 indicators improved (11 statistically significant) compared to the previous three years and 2 indicators did not change / declined. Performance benchmarks were calculated using Achievable Benchmarks of Care™ methodology and 14 of 16 performance benchmarks improved since 2014/15. There was wide variation across indicators with only 4 indicators showing a reduction in regional variation. The Ontario stroke report card can be viewed at https://www.ices.on.ca/Publications/Atlases-and-Reports/2017/Stroke-Report-Cards.

Conclusion/ImplicationsThe Ontario stroke report card spans the stroke care continuum, provides a snapshot of Ontario’s stroke system performance. Data linkage is essential for a system-wide opportunity to evaluate and influence system performance. This cross-continuum approach and report card format could be applied to other health related conditions.
Analysis of factors associated with changing general practice in the first 14 years of life in Wales using linked cohort and primary care records: implications for using primary care databanks for life course research
Authors: Akbari Ashley , Lyons Ronan , Bandyopadhyay Amrita , Bedford Helen , Brophy Sinead , Cortina-Borja Mario , Griffiths Lucy J , De Stavola Bianca , Tingay Karen , Dezateux Carol
Published: September 2018

IntroductionPrimary care electronic health records (pcEHRs) are a valuable resource for life course research, however loss to follow up due to changing practices has received little attention. We investigated factors associated with changes in registration and record continuity in the Secure Anonymised Information Linkage (SAIL) databank, with ~80% practice coverage.

Objectives and ApproachWe analysed linked pcEHRs for 1834 (882 girls) Millennium Cohort Study (MCS) participants, resident in Wales and with parental consent to health record linkage at the age seven MCS interview. We studied time from first to next general practice (GP) registration in Wales by fitting Cox proportional hazards models, and estimated mutually-adjusted hazard ratios (aHRs) for the following factors: child (sex, ethnicity, mode of delivery, gestation, birthweight, neonatal illness, wheeze, longstanding illness); maternal (age, education, lone parent status); household (income, housing tenure, residential mobility, urban/rural residence); GP type (SAIL-contributing/-non-contributing). Analyses were weighted for survey design (Stata: Release 15; StataCorp LP).

ResultsThere were 3065 Welsh GP registrations for 1834 children. By age 5 years, 25% of children changed GP at least once, with 1070 (58.3%), 477 (26.0%) and 287 (15.7%) registered with 1, 2, 3+ GPs respectively up to 14 years of age. Children with older mothers (aHRs; 95% CI: 0.96; 0.95, 0.98; per year) or those residing in rural areas (0.75;0.56,0.99) were less likely, and those whose first registration was not with a SAIL contributing GP (2.16;1.60,2.93), whose mothers had no educational qualifications (1.40;1.15,1.71), or had recently changed address (1.62;1.21,2.16) more likely, to change GP. 305 (16.6%) children had never registered with a SAIL-contributing GP. Of 403 children initially registered with a SAIL contributing GP who then changed GP, 66.7% re-registered with a SAIL contributing GP.

Conclusion/ImplicationsGeographically contiguous primary care databanks, such as the SAIL databank, enable a high proportion of children to be reliably followed over time despite changing GP. Similar analyses of databases based on geographically disparate volunteer GPs are needed to quality assure their suitability for life course epidemiology research.
Multi-morbidity using General Practice drug chapters and the relationship with secondary healthcare utilisation in Wales, UK
Authors: Lyons Jane , Lyons Ronan , Akbari Ashley , Berridge Damon
Published: September 2018

IntroductionMulti-morbidity and polypharmacy are increasing but are under investigated. Data linkage has much to offer in understanding trends in prevalence, inter-relationships between variables and impact on healthcare activity. We created Welsh population e-cohorts in 2000 and 2014 to study these issues, using the Secure Anonymised Information Linkage (SAIL) Databank.

Objectives and ApproachThe aim of this study was to measure changing prevalences of multimorbidity, initially through disease chapter prescribing and then to explore the relationship between the number of morbidities recorded in primary care and use of different hospital based outpatient services. Data linkage was used to create cohorts of Welsh residents registered to SAIL providing General Practices (GPs) for at least 360 days in 2000 and 2014. The 13 Read code drug chapters were used to calculate morbidity scores between 0 and 13. Proportional odds or cumulative logit models were used to relate GP recorded morbidities to outpatient attendance patterns.

ResultsThe GP cohorts included 1.6 million and 2.1 million population with 56.6% and 73.4% having at least one recorded morbidity for 2000 and 2014 respectively. In 2014, 5+ morbidities were most prevalent (61.3%) in 85+ year olds and least common (2.7%) in 5-9 year olds. Some 35% of individuals attended at least one outpatient specialty in 2014, varying from 22.4% for 5-9 year olds and 63.2% for 80-84 year olds.

Preliminary modelling results show the number of GP recorded morbidity chapters was strongly related to increasing outpatient attendances at different specialties, e.g. OR 15.3 (95%CI: 15.1-15.4) of being in a higher outpatient attendance category for the 5+ morbidity group relative to the zero morbidity group. Increasing age and female gender were associated with increased numbers of specialists attended whilst deprivation had a more modest impact.

Conclusion/ImplicationsThere has been a large increase in recorded multimorbidity across all age groups in Wales. In this exploratory cross-sectional design, multimorbidity was strongly related to increasing use of outpatient services. Further work is ongoing to define and utilise more refined multimorbidity metrics and incorporate longitudinal designs in analysis.
Intellectual Disability in Children with Congenital Heart Defects in Western Australia
Authors: Nembhard Wendy , Luo Chunqiao , Leonard Helen , Bourke Jenny , Bower Carol
Published: September 2018

IntroductionCongenital heart defects (CHD) are diagnosed up to age 6 in 8-12/1,000 births annually in Western Australia. Recent improvements in management of infants with CHDs has significantly increased survival; approximately 85\% of infants with CHDs live beyond childhood. However, children with CHDs may have increased risk of life-long intellectual disabilities.

Objectives and ApproachWe conducted a study of 20,997 children to determine risk of intellectual disability (ID). All singleton, live born infants with CHDs born 1983-2010 were identified from the Western Australian Register for Developmental Anomalies, a statewide birth defects registry (n=6,968). Infants without CHDs born 1983-2010 were randomly selected from birth records (n=14,029). All data were linked to the Western Australia Midwives Notification System to obtain maternal and infant information. Children with ID were identified by linkage to the statewide Intellectual Disability Exploring Answers database. Risk ratios (RR) and 95% confidence intervals (CI) were calculated from multivariable logistic regression analyses.

ResultsOf 20,997 children, 965 (4.6%) had an ID; 1.3% of children without CHDs and 11.2% of children with CHDs had an ID (P<0.001). 0.2% of children without CHDs and 0.4% of children with CHDs had autism. Three percent of children with CHDs had a known biomedical cause for ID (excluding trisomy 21) and 4.4% of children with CHDs had trisomy 21. Children with CHDs had 9 times the risk of ID compared to children without CHDs (RR=9.30; 95% CI: 7.91, 10.94). Children with CHDs almost had a twofold increased risk of autism compared to children without CHDs (RR=1.78; 95% CI: 1.07, 2.95). The greatest risk of ID among children with CHDs was associated with trisomy 21 (RR=166.0; 95% CI: 78.5, 350.8).

Conclusion/ImplicationsChildren with CHDs have higher risk of ID than children without CHDs. Although the greatest risk for ID was for trisomy 21, children with CHDs still had increased risk of ID from other causes and all causes overall. Future research should elucidate the underlying etiology of ID in these children.
A Bayesian Network Model of the Relationships between Chronic Disease Indicators
Authors: Yuan Mengru , Buckeridge David
Published: September 2018

Introduction We previous developed an informatics platform to: 1) generate large numbers of indicators of chronic conditions and determinants from heterogeneous sources, 2) present indicators in context of known causal relationships. However, the causality was defined by expert-consensus and only concerning direction. Quantitative estimates of causal effects are needed to drive public health decision-making.

Objectives and ApproachThe objective of this work is to quantify the strength of the relationships between chronic disease indicators through empirical analysis of data for a defined population.

Eight chronic diseases were explored and the individual data were obtained from linked administrative data for one million randomly sampled Montréal residents. We use Bayesian networks (BN) with our causal model based on expert consensus as a prior for the structure of the BN. In addition, we compare two networks estimated separately from individual-level data and data aggregated at the regional level, the latter being most commonly available to public health agencies.

ResultsBNs were developed using constraint-based and score-based algorithms for structure learning, and maximum likelihood for parameter estimation. We found that the BN structures and parameters learned from individual-level data differed from the one estimated from data aggregated by community health centers. Specifically, the BN structure learned from individual data contained 9 more arcs between indicators and tened to fit the data better (the Bayesian factor between two network structures was 25.55), however, the results from the aggregated data matched our prior understanding of epidemiological knowledge more closely.

Conclusion/ImplicationsConclusion: We compared BNs built using different resolutions of data as means to describe patterns among indicators for a defined population. This strategy for interpreting indicators combines prior domain knowledge with data and represents an initial step towards an intelligent decision-support tool for public health practitioners.
Establishing an International Data Linkage Repository Workgroup Toward a Benchmarking Repository
Authors: Kum Hye-Chung , Leonard Susan , Akgün Özgür , Alexander Trent , Antonie Luiza , Levenstein Margaret , O'Hara Amy
Published: September 2018

IntroductionAccess to real data with diverse attributes is critical for effective development of any data analytic algorithm. Benchmarking data repositories have all been vital to the development of research communities focused on algorithm development. This work reports on the development of such a data repository for record linkage.

Objectives and ApproachEstablishing a common benchmarking repository of real data can propel a field to the next level of rigor by facilitating comparison of different algorithms, understanding what type of algorithms work best under certain real data conditions and problem domains, promoting transparency and replicability of research, and creating incentives for proper citations for contributions. In addition, benchmarking repositories can bring together the diverse stakeholders (e.g., computer scientists, statisticians, data custodians, data users including social, behaviour, economic, and health (SBEH) scientists) that can advance the field more effectively than could researchers from any single discipline.

ResultsIn Fall 2016, international leaders in record linkage formed a Data Linkage Repository workgroup (DLRep) to establish a benchmarking data repository for record linkage. The workgroup is working in collaboration with The Inter-university Consortium for Political and Social Research (ICPSR) to host the site data repository planned for release in Summer 2018. The repository for record linkage research will house various types of real data that require linking with metadata, unique handles for citations, proposed algorithms for evaluation criteria, and a platform for posting, sharing, and comparing results as well as citations of relevant papers. Some datasets will have the gold standard published that researchers can evaluate their results against. Other datasets will gather results to build the gold standard as a community.

Conclusion/ImplicationsRecord linkage methodology is important to domains where data needs to be integrated from multiple sources, including diverse disciplines. Establishing an international interdisciplinary research community around a benchmark data linkage repository to validate and compare linkage algorithms is crucial to fully realizing the social benefits of data about people.
Better than blocking: building and using multiple variable pattern indexes (MVPi) to screen data sources for possible matches and reduce linkage search space
Authors: Hermansen Sigurd
Published: September 2018

IntroductionScaling up data linkage presents a challenging problem that has no straightforward solution. Lacking a prescribed ID in common between two data sources, the number of records to compare increases geometrically with data volume. Data linkers have for the main part resorted to “blocking” on demographic or other identifying variables.

Objectives and ApproachAmong the more efficient of better blocking methods, carefully constructed multiple variable pattern indexes (MVPi) offer a robust and efficient method for reduction of linkage search spaces in Big Data. This realistic, large-scale demonstration of MVPi combines 30,156 SSA Death Master File (DMF) and NDI matches on SSN with equal dates of death (true matches) and 16,332 DMF records with different or missing SSN, and links the total of 46,448 records on names, date of birth, and postal code (ignoring SSN) to >94MM DMF records. The proportion of true matches not linked tests for loss of information during the blocking phase of data linkage.

ResultsBlocking has an obvious cost in terms of completeness of linkage: any errors in a single blocking variable mean that blocking will miss true matches. Remedies for this problem usually add more blocking variables and stages, or make better use of information in blocking variables, requiring more time and computing resources. MVPi screening makes fuller use of information in blocking variables, but does so in this demonstration in one cohort (>30K) and DMF (>94MM) data sets. In this acid-test demonstration with few identifying variables and messy data, MVPi screening failed to link less than eight percent of the cohort records to its corresponding true match in the SSA DMF. MVPi screening reduced trillions of possible pairs requiring comparisons to a manageable 83MM .

Conclusion/ImplicationsThe screening phase of a large-scale linkage project reduces linkage search space to the pairs of records more likely to be true matches, but it may also lead to selectivity bias and underestimates of the sensitivity (recall) of data linkage methods. Efficient MVPi screening allows fuller use of identifying information.
Evaluation of interventions to improve inpatient hospital documentation within electronic health records: A Systematic Review
Authors: Wiebe Natalie , Varela Lucia Otero , Niven Daniel , Ronksley Paul E , Iraggori Nicolas , Robertson Helen Lee , Quan Hude
Published: September 2018

IntroductionDespite increased use of electronic health records (EHRs), EHR documentation quality remains poor. Consequently, EHR data quality is also negatively affected. Many services, including disease surveillance and health services research, utilize EHR data. Accordingly, several studies have attempted to improve EHR documentation quality in the inpatient setting using various interventions.

Objectives and ApproachThe purpose of this systematic review was to synthesize the literature, and assess the effectiveness of interventions seeking to improve inpatient EHR documentation quality. To identify relevant experimental, quasi-experimental and observational studies, a search strategy was developed based on elaborate inclusion/exclusion criteria using four main themes: EHR, documentation, interventions, and type of study. Four databases, Cochrane, Medline, EMBASE, and CINAHL, were searched. Study quality assessment and data extraction from selected studies were performed using a Downs and Black and Newcastle-Ottawa Scale hybrid tool, and a REDCap form, respectively. Data was then analyzed and synthesized in a narrative semi-quantitative manner.

ResultsAn in-depth search of the identified databases, grey literature and reference lists, revealed a final 20 studies for inclusion in this systematic review. Due to high heterogeneity in study design, population, interventions, comparators, document types and outcomes, data could not be standardized for a quantitative comparison. However, statistically significant results in interventions and affected outcomes were further presented and discussed. A higher number of studies reported significantly improved EHR documentation when using the interventions: ‘Education’ and ‘Implementing a new EHR Reporting System’. When implementing two or more interventions, more outcome measures were affected. There was no association between study quality or study design and number of interventions used. Only one of the 20 studies found EHR documentation worsened with the interventions used.

Conclusion/ImplicationsInterventions implemented to enhance EHR documentation are highly variable and require standardization. Emphasis should be placed on this novel area of research to improve communication between healthcare providers, enhance continuity of care, reduce the burden in health information management, and to facilitate data sharing between centers, provinces, and countries.
Patterns of pharmacotherapies used to treat alcohol use disorders: A population-based administrative data study
Authors: Nickel Nathan , Leong Christine , Prior Heather , Konrad Geoffrey , Bolton James , MacWilliam Leonard , Ekuma Okechukwu , Paille Michael , Valdivia Jeff
Published: September 2018

IntroductionAlcohol use disorders (AUDs) – mental and/or physical health diagnoses due to harmful alcohol consumption – are associated with compromised quality of life for the individual. Over the past two decades, pharmacotherapies have been developed to treat alcohol addiction and may help mitigate the harmful outcomes linked with excessive alcohol.

Objectives and ApproachThe objectives were to examine the pharmacotherapy dispensation patterns among individuals with an AUD and their mental health comorbidities. We used ICD codes from medical claims and hospital discharge data to identify anyone with a physical / mental health diagnosis due to harmful alcohol consumption – AUD, April 1, 1996-March 31, 2015. We identified mental health comorbidities using administrative health records. Drug dispensation data were used to identify all first-time prescriptions for acamprosate, naltrexone, or disulfiram occurring after an initial AUD diagnosis. Generalized linear models tested for predictors of receiving a prescription and to identify differences in mental health comorbidities.

ResultsWe identified 53,556 treatment niave individuals with an AUD who were eligible to receive one of these three prescriptions. 493 of these received a prescription for acamprosate, naltrexone, or disulfiram. The majority of prescriptions came from general practitioners from urban centers. Those with a prescription were significantly more likely to have a comorbid mood or anxiety diagnosis. Those with a prescription were more likely to have a physician visit for a mental health issue a year to two years before diagnosis compared with those who did not have a prescription; and, they were more likely to be dispensed a selective serotonin, a sedative, and an anti-anxiety medication prior to receiving an AUD diagnosis.

Conclusion/ImplicationsDrug therapies to aid in the recovery from AUD are being underutilized. Diagnosis of and treatment for mental health disorders is more common among those dispensed these medications. Programs that study clinicians’ use of AUD-targeted drug therapies should be considered, while psychiatric services in addiction care require significant improvement.
A Toolbox for Research – Population Data BC’s tools for overcoming challenges in the data access process
Authors: Medearis Melissa , Mintha Jim
Published: September 2018

IntroductionNavigating the regulatory environment of data access is complex. Where there are common challenges, there are opportunities to develop systems and services that can help researchers. These tools are designed to ensure secure and smooth navigation of the process of data access and data analysis.

Objectives and ApproachThere is increasing focus on technical solutions to support data requests and analysis. We have responded to existing challenges by developing a suite of tools and services including: MetaData Central, DARonline, AppTracker, Snippets, and REDCap. We will describe the obstacles that motivated each tool, how it was built, and how it addresses the original issue. We will also discuss the overall challenges in building these tools, including technical complexity and getting buy-in from data stewards and researchers. Finally, we will touch on some of the progress we have seen based on these tools, and our plans for future development.

ResultsMajor obstacles included providing information to researchers to help form their data request, communications among researchers, data stewards and PopData, general automation of procedures, and sharing among researchers. The tools developed in response include: MetaData Central, AppTracker (for project tracking); DARonline (for data requests); REDCap (for primary data collection); and Snippets (for code sharing). MetaData Central has proven to be a valuable resource for all stakeholders to learn basic data descriptions without needing access to the record level data. This helps in making sure the data requested meets the needs of the research project. AppTracker is helpful for monitoring applications, and reduces the time it takes for us to monitor compliance and provide reports. Other tools are newer and have less evaluation information.

Conclusion/ImplicationsUser-friendly, flexible tools are beneficial for making the data access process smoother and for meeting the evolving needs of researchers and data stewards. These tools can create both transparency through a common source of information and efficiency by automating routine processes.
Differential spatial distribution of hepatitis B virus by ethnicity in British Columbia, Canada: Expanded role of a large administrative cohort
Authors: Butt Zahid , Janjua Naveed , Wong Stanley , Yu Amanda , Alvarez Maria , Chapinal Nuria , Wong Jason , Binka Mawuena , Buxton Jane , Gilbert Mark , Darvishian Maryam , Rossi Carmine , Krajden Mel
Published: September 2018

IntroductionMost chronic hepatitis B virus (HBV) infections in Canada are diagnosed among immigrants from endemic countries and lack traditional risk factors while most acute infections are usually diagnosed in Caucasian population with co-occurring risk factors. Thus, understanding geographical distribution of HBV infection by ethnicity could inform screening and care strategies.

Objectives and ApproachWe identified geographic clusters of HBV infection in British Columbia by ethnicity during the years 1990-2015 using the BC Hepatitis Testers Cohort (BC-HTC). The BC-HTC includes ~1.7 million individuals tested for HCV or HIV at the BC Public Health Laboratory or reported as a case of HCV, HIV, or HBV linked to healthcare administrative databases. We plotted maps of HBV diagnoses (acute and chronic) rate at the Dissemination Area level between 1990-2015 stratified by ethnicity and compared this distribution with injection drug use (IDU) distribution in BC.

ResultsThe distribution of HBV varied considerably by ethnicity. From 1990 to 2015, a higher rate of HBV infection was found among East Asians and Caucasians followed by South Asians and other ethnicities. East Asians with highest rates were mainly concentrated in Vancouver city, Burnaby and Richmond (Metro Vancouver) while South Asians with highest rates were mostly concentrated in urban areas in Surrey and Abbotsford. Caucasians with higher rates were clustered in Downtown Eastside in Vancouver, Surrey and Abbotsford (Metro Vancouver) and urban areas in Greater Victoria (Vancouver Island), Prince George (Northern BC) and Kamloops (Interior BC). The distribution of IDU closely followed the distribution of HBV among Caucasians but did not align with other ethnic groups.

Conclusion/ImplicationsResults highlight distinct areas of HBV infection clustering by ethnicity, which differ from areas with high IDU distribution except in Caucasians. Findings support ethnicity-based HBV screening/prevention and care services to areas with immigrants from HBV-endemic countries and integrated HBV and harm reduction services for early diagnosis and treatment in Caucasians.