bluuebunny/crossref_metadata_2025 huggingface dataset:
Poor birth outcomes among Aboriginal Western Australians and smoking, alcohol and substance misuse, and assault
Authors: Gibberd Alison , Simpson Judy , Jones Jocelyn , Williams Robyn , Stanley Fiona , Eades Sandra
Published: September 2018

IntroductionOn average, Aboriginal neonates in Western Australia (WA) weigh 200g less than non-Aboriginal infants and are 2-3 times more likely to be preterm, stillborn, or die neonatally. They are also more likely to be exposed in utero to maternal behaviour risks like smoking, due to factors such as intergenerational trauma.

Objectives and ApproachWe aimed to estimate the proportion of small for gestational age (SGA) births, preterm births, and perinatal deaths of Western Australian Aboriginal infants from 1998-2010 attributable to maternal smoking, alcohol misuse, drug misuse, and assault against the mother. We used linked birth, hospital, mental health, and death records of all Aboriginal singletons and their parents. Using logistic regression with a generalized estimating equation approach, associations between birth outcomes and the four risk factors of interest were estimated after adjusting for maternal age, height and health. Using coefficients from these models, we estimated adjusted population attributable fractions (PAFs).

ResultsOf 28,119 births, 16% of infants were SGA, 13% were preterm and 2% died perinatally. 51% of infants were exposed to maternal smoking, alcohol misuse, drug misuse, and/or assault, and 37% [95% CI: 35%, 40%] of SGA births, 16% [95% CI: 14%, 19%] of preterm births and 20% [95% CI: 12%, 28%] of perinatal deaths were attributable to these factors, predominantly smoking. The PAFs for alcohol misuse (for example, for SGA, 3% [95% CI: 2%, 3%]) are likely to be underestimates as it is difficult to identify alcohol misuse using administrative data.

Conclusion/ImplicationsWhile smoking rates have dropped considerably, reduction measures have been less successful among Aboriginal women than non-Aboriginal women. Significant improvements in perinatal health are possible with identification and support of effective risk reduction approaches for Aboriginal women, as well as their communities and families.
Finding Maternal Siblings in Birth Registration Data to form a Pregnancy Spine – Data Linkage & Graph Based Methods for Unknown Cluster Sizes
Authors: Gammon Shelley , Morris Charles
Published: September 2018

IntroductionWe have developed an innovative methodology to link maternal siblings within 2000 – 2005 England and Wales Birth Registration data, to form a Pregnancy Spine, a unification of all births to each unique mother.

Key challenges in this many-many linkage scenario:

Blocking (reduction of record pair comparisons)

Cluster resolution

Objectives and ApproachProbabilistic data linkage (Python) was followed by generation of clusters (using igraph in R) and graph theory community detection techniques.

To optimise geographical blocking and increase accuracy, we incorporated Internal Migration data to map the likely geographic movement of mothers between births.

Maternal sibling clusters were modelled as a graph and the structure of clusters was optimised using community detection methods to link, split and evaluate sibling groups.

Additionally, we incorporated additional childhood statistics data relating to child date of birth to evaluate likely accuracy of sibling pairs and remove false edges (links).

ResultsOur development has resulted in a new blocking method and cluster resolution method. In addition, we developed new ways to assess and measure the accuracy of sibling groups, beyond traditional classifier metrics, and infer error rates.

We applied our method to Registration Data used in earlier studies for QA of our methods.

Using this, and by comparing against other statistics on maternal sibling composition we will present results which show that a high degree of accuracy (precision / recall and new checks) was obtained for precision, recall, and other evaluation metrics.

Conclusion/ImplicationsThese methods will improve other linkage projects with unknown clusters sizes; for de-duplicating datasets, linkage of multiple datasets, or incorporation of data from a longer time-period through longitudinal linkage.

To this Spine, researchers can now append and link other data sources to answer questions about maternal and child health outcomes.
International comparison in walkable environments and hospital burden in type 2 diabetes patients
Authors: Mah Sarah M , Akbari Ashley , Fry Richard , Ross Nancy
Published: September 2018

IntroductionWhile some comparative work has provided evidence for a universally positive impact of built environment features that promote physical activity, less is known about chronic diseases and hospitalization among different social contexts and health care systems. Parallel international linkage efforts present an opportunity to study health impacts of the built environment.

Objectives and ApproachThis study compares the impact of neighbourhood environments on health outcomes for patients with type 2 diabetes (T2D) in two countries. Neighborhood-level measures for walkable environments were derived for Canada and Wales using Geographic Information Systems. Hospitalization admissions from routine data sources and linked survey data responses (from the Welsh Health Survey and Canadian Community Health Survey) allow for the generation of population-based descriptive statistics on socio-demographic information, self-reported health, diagnostic patterns, and health care use. We examine the feasibility of investigating contextual differences in walkable environments, T2D, and hospitalization between Wales and Canada.

ResultsData linkage in respective privacy protecting safe havens in the Canada Research Data Centre Network (CRDCN) and the Wales Secure Anonymised Information Linkage (SAIL) Databank show promise for a comparative study, enabling parallel modelling of environmental and socio-demographic factors with hospitalization data. Both the Canadian and Welsh surveys ask respondents about their current diabetes status, allowing us to compare hospitalization rates and neighborhood effects of those who report having diabetes with the those who do not. Moreover, the linking of survey responses and similarity in geographic scale permitted consistent measurement of walkable environments across countries. Key administrative variables have been identified relating to health and behaviors, such as socio-demographic information, smoking status, and body mass index, and hospitalization metrics in both countries are commensurable.

Conclusion/ImplicationsThe generation of comparable linked datasets, built environment indicators and comparative research for T2D patients will have wider implications for international assessment of the impacts of environment on chronic diseases, and the hospital burden associated with these conditions.
Deaths in young people after contact with the youth justice system: a retrospective data linkage study
Authors: Kinner Stuart , Tibble Holly , Hail-Jares Katie , Borschmann Rohan , Spittal Matthew , Clough Alan , Sawyer Susan , Miller Adrian , Cadet-James Yvonne
Published: September 2018

IntroductionYoung people who have contact with the youth justice system are distinguished by a high prevalence of complex, co-occurring health problems, including known risk factors for preventable mortality. However, almost nothing is known about health outcomes for these young people after separation from the youth justice system.

Objectives and ApproachWe aimed to examine the incidence, timing, causes and risk factors for death in justice-involved young people. We linked youth justice records in Queensland, Australia 1993-2016 (N=48,963) with adult correctional records and the National Death Index. We split the cohort into three subgroups: those who had ever been in detention (n=7,643), those supervised in the community but never detained (n=12,953), and those charged with an offence but never convicted (n=28,367). We calculated all-cause and cause-specific crude mortality rates (CMRs), and indirectly standardised mortality ratios (SMRs). We used Cox regression to identify static and time-varying risk factors for death.

ResultsDuring a median of 13.6 years of follow-up there were 1,452 deaths (3.0%). The all-cause CMR was 2.2 (95%CI 2.1-2.3) per 1000 person-years, and the all-cause SMR was 3.1 (95%CI 3.0-3.3). The leading external causes of death were suicide (32% of all deaths), transport accidents (16%), accidental drug-related causes (13%), and violence (3%). In adjusted analyses, independent risk factors for all-cause mortality included being male (HR=1.4, 95%CI 1.2-1.6) and older (>=15 vs. vs. charge only; HR=1.6, 95%CI 1.2-2.0) and subsequent incarceration as an adult (HR=1.8, 95%CI 1.4-2.4).

Conclusion/ImplicationsYoung people who have contact with the youth justice system are at markedly increased risk of preventable death, after separation from that system. Efforts to improve long-term health outcomes for justice-involved youth have the potential to reduce preventable deaths in these highly vulnerable young people.
A machine-learning approach to identify cerebral palsy cases using primary care database
Authors: Fan Heng , Li Leah , Wijlaars Linda , Gilbert Ruth
Published: September 2018

IntroductionCerebral palsy (CP) is a complex condition that can manifest in different ways and is likely to be under-recorded in primary care databases. As identification based only on diagnostic codes will underestimate the incidence of cerebral palsy, an approach is needed to use all available information to identify more cases.

Objectives and ApproachWe used a machine-learning approach to identify likely CP cases in the Clinical Practice Research Datalink (CPRD), a UK primary-care database: i) we selected potential codes (symptoms, therapies and managements) to identify CP cases by comparing relative frequencies of codes associated with known cases versus non-cases; ii) codes with higher discriminative ability were further selected using a Random Forest method based on a resampled, balanced population; iii) we calculated the predictive score for each patient employing the discriminative ability of selected codes; and iv) manually reviewed the full medical records of likely cases (i.e. patients with higher predictive score).

ResultsPrimary care records were available for 343,199 young people aged 2000 were identified as likely cases (n=365, 0.1% of previously non-cases). Their full medical records in CPRD were manually reviewed by experts and 85 children (23.3% of likely cases) were validated as CP cases additional to the 341 initially identified by diagnostic codes, resulting in a 20% increase of CP cases.

Conclusion/ImplicationsData-driven schemes, such as the machine learning methods applied here, have the potential of identifying the most informative predictors in a cost-effective and rapid way to identify likely CP cases or other complex medical conditions in primary care database.
Linking environment and health data to investigate the association between access to unhealthy food and child BMI
Authors: Mizen Amy , Rodgers Sarah , Fry Richard , Lyons Ronan
Published: September 2018

IntroductionModelling the daily exposure environment provides evidence for policy and practice. However, the dose-response relationship between exposure to food environments and obesity has not been widely investigated. This study investigated whether increased retail food environment (RFE) exposure in children was associated with a larger body mass index (BMI).

Objectives and ApproachIndividually tailored environmental exposures were calculated in a GIS for home and school locations, and modelled walking routes to and from school. Exposures were linked to individual level health data in the SAIL databank for a cohort of individuals aged 11-13 years from south Wales who had BMI measurements. A fully adjusted multilevel regression model was fitted to investigate the association of RFE exposure with BMI. Based on the distance individuals lived from school, we investigated differences between children who have the potential to walk to school (“walkers” lived 4.8km).

ResultsHome exposure and exposure along the walk to school was significantly greater for children living in deprived catchments, compared with children living in affluent school catchments (t = -5.25, p

Conclusion/ImplicationsIncreased BMI was associated with greater RFE exposure along the walk home from school. The findings suggest that the walk home from school should be the focus for developing interventions and policies to discourage unhealthy eating. Research should be undertaken to better understand child purchasing habits.
The Mortality After Release from Incarceration Consortium (MARIC) study: Strengths of international data linkage
Authors: Borschmann Rohan , Kinner Stuart , Spittal Matthew
Published: September 2018

IntroductionAdults released from incarceration experience complex physical and mental health problems, and are at markedly increased risk of preventable death. Despite this, not enough is known about the granular epidemiology of mortality in this population to inform development of targeted, evidence-based responses.

Objectives and ApproachWe created the Mortality After Release from Incarceration Consortium (MARIC), a multi-disciplinary collaboration from 12 countries representing 30 cohorts of adults with a history of incarceration. The combined sample size is 1,210,168, with 58,840 deaths recorded over 8,261,743 person-years of follow-up time. In this protocol paper, using a two-step, individual participant data meta-analysis (IPDM-A) methodology involving 22 MARIC cohorts, we calculated 1) a crude mortality rate (CMR; with 95% confidence intervals) for each individual cohort over the first 84 days (12 weeks) following release; and 2) a combined, meta-analysed CMR for the same period.

ResultsOf 1,704,208 individual releases, we observed 4,018 deaths over the first 84 days. The overall CMR over the first 84 days after release was 1610.97 deaths per 100,000 person-years (95% CI: 1263.4 - 1958.5). The rate was highest on the day of release (5768.0; 95% CI: 3296.5 - 8239.4), which was significantly higher than on days 4-84.

Conclusion/ImplicationsAdults released from incarceration were at an acutely increased risk of death on the day of release, and this risk remained elevated for at least the first 12 weeks. The MARIC study will provide decisive and empirical evidence to guide clinicians and policy makers in reducing mortality in this marginalized
The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort
Authors: Johnston Marjorie , Black Corri , Mercer Stewart , Prescott Gordon , Butler Jessica
Published: September 2018

IntroductionMultimorbidity, the co-existence of two or more health conditions, is a growing challenge. It may be measured using health service administrative data via the emerging consensus measure by Barnett. However, the original Barnett was developed using Scottish-specific primary care coding, which restricts its application in other health systems.

Objectives and ApproachThe aim was to create and test International Classification of Disease (ICD) coding algorithms for all 40 Barnett conditions.

We evaluated this new measure by:

Assessing the prevalence of secondary care multimorbidity in 2001

Assessing the association between multimorbidity and mortality rate over 15 years

Participants of the Aberdeen Children of the 1950s cohort (ACONF) were linked to their secondary-care healthcare records and mortality records. Multimorbidity was defined as the presence of two or more of the 40 conditions. The association between multimorbidity and mortality was assessed using Cox proportional hazards regression with adjustment for key covariates.

ResultsWe combined results of a review of the coding literature with codes used commonly by the National Health Service in Scotland, to apply ICD codes to each Barnett condition.

The ACONF were aged 45 to 51 years in 2001. Of 8,094 members who were alive and linked to Scottish administrative data, 246 (3%) had multimorbidity. There were 629 deaths by 2016 with 83 occurring in the multimorbidity group.

Relative to those without multimorbidity, those with multimorbidity in 2001 had a mortality hazard ratio (HR) of 5.9 (95% CI 4.6-7.4) over 15 years follow-up. This was unchanged when adjusted for age, gender, social class at birth, cognition at age 7, secondary school type and educational attainment (HR 6.2, 95% CI 4.4-8.5).

Conclusion/ImplicationsWe have created a new version of the influential Barnett measure using ICD codes, which allows for its wider application across health systems. We found that this measure of multimorbidity was associated with greatly increased mortality, indicating it could help predict poor outcome using administrative records.
Variation in Access to Specialist Care and Risk of Surgery in Patients with Inflammatory Bowel Disease: A Population-Based Cohort Study
Authors: Kuenzig Ellen , Stukel Therese , Murthy Sanjay , Nguyen Geoffrey , Talarico Robert , Benchimol Eric
Published: September 2018

IntroductionInflammatory bowel disease (IBD; subtypes: Crohn’s disease (CD) and ulcerative colitis (UC)) is a chronic disease of the gastrointestinal tract with rising prevalence among people ≥65y. Rural residents, especially those ≥65y, have decreased access to specialist care. Specialist care is associated with lower risk of hospitalization and surgery.

Objectives and ApproachWe evaluated variation across physician networks in access to specialist care and surgery among incident patients ≥65y in Ontario health administrative data. Access to specialist care was defined as: ≥1 outpatient visit to gastroenterologists or the majority of IBD-specific outpatient care by gastroenterologists. Variation was assessed with multilevel logistic regression and median odds ratios (MOR), adjusting for age, sex, distance from IBD physician, comorbidities, neighbourhood income, and rural/urban. Models evaluating surgical risk also adjusted for specialist care use, emergency department visits, and hospitalization at diagnosis. Network-level variables included rurality (RIO score), population colonoscopy and gastroenterologist supply.

ResultsThere was significant variation in having ≥1 gastroenterologist visit (CD p=0.0001, MOR 3.3; UC p<0.0001, MOR 3.1) and gastroenterologist providing the majority of care (CD p=0.0001, MOR 3.0; UC p<0.0001, MOR 3.7) within 12 months of diagnosis. Variation remained significant after accounting for network-level characteristics (≥1 gastroenterologist visit: CD p=0.0002, MOR 2.6, UC p<0.0001, MOR 2.2; majority of care: CD p=0.0002, MOR 2.4; UC p<0.0001, MOR 2.4). In CD, there was no variation in the five-year risk of surgery (p=0.07, MOR 1.3) and was unchanged by network-level factors (p=0.13, MOR 1.3). Variation in the risk of colectomy exists for patients with UC (p=0.016, MOR 1.3) and was not reduced when accounting for network-level characteristics (p=0.019, MOR 1.3).

Conclusion/ImplicationsAccess to specialist care among patients with elderly-onset IBD is varies greatly between networks but this variation cannot be explained by differing provision of gastroenterological services across physician networks. Further research is needed to understand the factors that influence access to care and outcomes in elderly patients with IBD.
Mapping Clinical Contents onto Longitudinal Depictions of Cross-Continuum Service Events in Island Health: Clinical Context Coding Scheme
Authors: Koval Andriy , Moselle Kenneth
Published: September 2018

IntroductionAll bits of clinical information acquire meaning against a backdrop of longitudinal engagement with a potentially large constellation of services. Full cross-continuum transactional data will be refractory to analysis unless the full continuum of service locations can be rendered in a form that is transparent with regard to target populations.

Objectives and ApproachThe work entailed two streams of activity: (1) building a six-dimensional framework (Clinical Context Coding Scheme - CCCS) that is layered directly onto the full array of secondary and tertiary service locations to render transparent the clinical function of the services; and (2) developing tools that work from that framework to reduce very large numbers of granular service entities down to a smaller number of clinically-functionally homogeneous entities. This solution serves both to supply the data in an analyzable form, and to address problems of small cell sizes and associated challenges around risk for re-identification of high-dimensional longitudinal data sets.

ResultsThe CCCS consists of an extensible array of meta-data categories (currently six) that are layered onto each of the 1700 service locations extracted from the location build in Island Health’s deployment of the Cerner EHR. This scheme was linked to the large body of longitudinal encounter data in Island Health. Service encounters, classified and aggregated using this CCCS scheme, were used to perform the following functions: (a) supply a base longitudinal encounter layer onto which other data sets could be superimposed (linked); (b) generate within-person-over-time visualizations of individual patients that reflects full secondary and tertiary cross-continuum service utilization; (c) generate cohort definitions reflecting patterns of service utilization, and (d) generate aggregate level reports that summarize full cross-continuum service utilization for cohorts.

Conclusion/Implications

The CCCS produces views of patients that are more complete and/or quite different from those created with the “usual datasets” (e.g., Acute Care + ER). Applying the scheme to diverse populations (e.g. addictions; stroke patients) illustrates the scheme’s viability – and the consequences/costs of NOT bring the full continuum into focus.
How integration of the federal Indian Register has enhanced First Nations-specific analysis of ICES data
Authors: Schultz Sue , Jones Carmen , Walker Jennifer
Published: September 2018

IntroductionIn Ontario, First Nations are increasingly seeking population-level data about the health of their citizens. However, First Nations people are not readily identified in standard health administrative data and indirect strategies, such as the use of on-reserve addresses, are limited in scope and validity.

Objectives and ApproachThe Chiefs of Ontario entered into a Data Governance Agreement with the Institute for Clinical Evaluative Sciences (ICES) that enabled the linkage of the federal Indian Register (IR) to data at ICES. This study examined the impact of the IR linkage on First Nations population estimates and location of residence, measured by postal code or residence code. Overall, and for each First Nation community in Ontario, we compared First Nations population estimates from the ICES data with and without the IR linkage to estimates available from Indigenous and Northern Affairs Canada (INAC).

ResultsWithout the IR, using only Ontario residence codes or postal codes that were unique to a given community, 62,242 individuals were identified as living in First Nations communities. This is approximately 30% lower than the current INAC on-reserve population estimate of 92,234 for First Nations communities in Ontario. Adding the IR allowed the use of non-unique postal codes as well, resulting in the identification of an additional 15,183 First Nations individuals. It also allowed the identification of over 113,000 First Nations individuals who live outside of First Nations communities, especially in urban areas. Finally, the combination of residence information and the IR permits communities to identify their registered member living within and outside their communities.

Conclusion/ImplicationsUsing the IR in combination with geographic residence information, made possible through the Data Governance Agreement signed between Chiefs of Ontario and ICES, will provide First Nations communities with more accurate and complete population estimates, which is key to the production of useful and relevant First Nations-specific health research.
Cancer Screening in the Toronto Central LHIN by Sub-region and Neighbourhood: Evidence from an Applied Health Research Question (AHRQ)
Authors: Ellison Lisa , Graves Erin , Ishiguro Lisa , Lofters Aisha , Vahabi Mandana , Damba Cynthia
Published: September 2018

IntroductionThe Toronto Central (TC) LHIN has aligned its vision with the Ministry of Health and Long-Term Care and Cancer Care Ontario to prioritize participation in population-based cancer screening programs and to address screening inequities. This request was accepted by the ICES AHRQ review team to help impact policy and programs.

Objectives and ApproachBy linking cancer screening data to geographic, provider and immigration databases, underlying contributors and barriers to cancer screening can be better understood and used to target interventions to specific groups and areas of the province. Thus, the purpose of this study was to: 1) determine the rates of cancer screening in the TC LHIN by sub-region and neighbourhood, and 2) determine how these differences vary by immigration status, primary care provider characteristics and neighbourhood income level. Using OHIP billing claims, screening for breast, cervical and colorectal cancer was identified between fiscal years 2013 to 2016.

ResultsDuring the study period, 58.4% of eligible TC LHIN residents received a mammogram, 57.1% received a pap smear and 55.1% received colorectal cancer screening. Screening rates varied by Toronto neighbourhood: 48.4%–72.9%, 38.8%–70.1% and 42.7%–68.7% for mammograms, pap smears and colorectal cancer screening respectively. Residents who recently immigrated to Ontario received less cancer screening than non-immigrants; 51.8% of immigrant women eligible for cervical cancer screening received a pap smear compared to 60.4% of non-immigrant women in the TC LHIN East region. Not having a female physician (54.3% vs 68.6%), lacking comprehensive care (55.6% vs 62.5%), having a foreign trained physician (56.6% vs 64.7\%) and living in a lower income neighbourhood (51.6%-62.5%) were other factors associated with lower rates of cancer screening.

Conclusion/ImplicationsCancer screening rates vary according to neighbourhood, and certain groups may be vulnerable to inadequate screening. These findings will help to address cancer screening disparities due to structural barriers, and will help in the delivery of culturally appropriate and relevant cancer screening educational packages and outreach programs in Toronto.
Challenges in linking administrative data for monitoring bloodstream infection in neonatal units in England and Wales
Authors: Fraser Caroline , Gilbert Ruth , Blackburn Ruth , Muller-Pebody Berit , Harron Katie
Published: September 2018

IntroductionMonitoring risk-adjusted trends of neonatal bloodstream infection (BSI) is vital and linkage of neonatal electronic health records to national infection surveillance enables this. We demonstrate why changes in data quality and collection methods over time must be accounted for to minimise spurious findings.

Objectives and ApproachFirst, we determined the effect of a system change in 2014 (changed from only clinically relevant BSI to automated reporting of all BSI), by investigating changes in number of all BSI and BSI excluding the contaminants coagulase-negative staphylococci for infants aged <1 year reported to infection surveillance, using interrupted-time-series Poisson regression. Second, we evaluated the impact of changes in identifier completeness over time in each database, and determined variation in infection rates according to linkage method (deterministic linkage on NHS number or probabilistic linkage). Third, we will use multiple imputation when link status cannot be determined due to missing identifiers.

ResultsThe number of BSI reported to infection surveillance system following the change in data collection increased by 34% (incidence rate ratio (IRR) of 1.34, 95% confidence interval 1.28-1.40) for all BSI compared to 19% (IRR 1.19, 1.12-1.27) excluding coagulase-negative staphylococci. Completeness of NHS number in infection surveillance increased from 69% (3,296/4,792) in 2010 to 92% (3,037/3,307) in 2017. We linked 12,003 neonatal admissions to 15,571 BSI episodes (2% of 497,936 admissions and 41% of 37,660 BSI). The proportion of links that were deterministic changed from 83% (1,089/1,307) in 2010 to 96% (968/1,008) in 2017. There were 12,094 BSI for which the link status could not be determined due to missing identifiers; multiple imputation will be used to determine if any are links.

Conclusion/ImplicationsSpurious trends in infection incidence can arise from changes in data collection and quality, impacting the quality of linkage to clinical data. Data quality and system changes must be explored in each source dataset before analysis. Probabilistic linkage and imputation of missing data minimises spurious findings due to data quality.
Cross-sector service use among youth and young adults involved in the Alberta provincial justice system
Authors: Cui Xinjie , Werk Christine
Published: September 2018

IntroductionYouth and young adults who are involved in justice and correctional system often have complex service needs and experience poor health and social outcomes. To improve outcomes for these young Albertans, it is important to understand their characteristics and service utilization patterns across health and social areas.

Objectives and ApproachThe current analysis provides cross-sector service use information on Alberta youth and young adults aged 12 to 25 who were involved in the criminal justice system from 2005 to 2011. Administrative data linked data across multiple Alberta provincial ministries were used for the analysis. These included over 20 programs and services in areas such as health, education, child intervention, disability supports, income support, and justice and corrections.

ResultsOffence types and court outcomes varied by social-demographic characteristics such as age, sex, social economic status, and residential mobility. Elevated mental health and high cost health services use was observed among youth involved in the criminal justice system. Access of social programs such as Child Invention service, Child Support services, Income Support and disability support services was more prevalent among youth and young adults who were involved in the justice system. A higher number of offences was associated with worse education and health outcomes.

Conclusion/ImplicationsCross-sector data linkage and analysis offer a unique opportunity for better understanding of clients/patients and services/programs at the broad system level. Knowledge gained through linked data can inform cross-ministry policies and integration of services.
Using linked routinely collected health data to explore the burden of respiratory syncytial virus (RSV) in Scotland
Authors: Reeves Rachel , Douglas Anne , Campbell Harry
Published: September 2018

IntroductionRespiratory syncytial virus (RSV) is the most frequent cause of lower respiratory tract infections (RTIs), particularly bronchiolitis, in young children worldwide. In order to inform policymaking and regulatory decisions regarding novel RSV vaccines and therapeutics, the health and economic burden of RSV needs to be quantified in further detail.

Objectives and ApproachThis project is part of the REspiratory Syncytial virus Consortium in Europe (RESCEU), a collaborative IMI funded EU project assembling routinely collected health data from at least seven European countries to produce detailed estimates of RSV health and economic burden. This study links national data on hospital admissions, deaths, RSV laboratory testing, prescriptions, and maternal/perinatal data. Using this linked data we calculate rates of hospital admissions, intensive care unit (ICU) admissions, and deaths (a) potentially due to RSV, (b) likely due to RSV, and (c) confirmed due to RSV. We also investigate maternal and perinatal characteristics associated with RSV-related episodes.

ResultsRSV is a major cause of hospital admission in Scotland, particularly in children <6 months old. Around 2,000 admissions with a primary diagnosis of bronchiolitis occur in children <12 months old per year, on average, with approximately 75% of these estimated to be due to RSV.  Children with known clinical risk factors, such as prematurity or chronic conditions, are at increased risk of ICU admission and death due to RSV.  Results will be presented on the age- and risk-group specific hospitalisation, ICU admission and mortality rates for RSV-associated RTI in children <5 years old.  The maternal and perinatal characteristics (e.g. maternal smoking, type of delivery, breastfeeding status, birthweight, APGAR score (5 mins), mechanical ventilation, oxygen use) associated with RSV-related RTI hospital episodes will be presented.

Conclusion/ImplicationsThis is the first study to explore the national burden of RSV in Scotland. Our results demonstrate the benefits of using linked routinely collected data to explore the epidemiology and burden of infectious diseases and inform policymaking and regulatory decisions. Our methodology can be applied to other countries and pathogens.
The BC SUPPORT Unit Data Platform: Offering Data-Related Services To Researchers In British Columbia
Authors: Kesselring Sarah , Mander Bryony , Djurdjev Ognjenka , Moselle Kenneth , Portales-Casamar Elodie , Schuckel Victoria , Singer Joel , Sobolev Boris , Wong Shirley , Brasher Penny , Cherban Erin , Young Ella , Sanderson Kelly , Neuman Maureen , Moran Kelly , Enjo Dan , McGrail Kim
Published: September 2018

IntroductionThe Canadian Institutes of Health Research (CIHR) and provinces co-fund local Units to increase the quality and quantity of patient-oriented research. These SUPPORT (Support for People and Patient-Oriented Research and Trials) Units include a prominent Data Plan component. The BC Plan is the result of collaboration between many organizational partners.

Objectives and ApproachA Data Advisory Committee comprised of eight organizational partners worked together for several months in 2016-2017 to develop BC’s provincial Data Plan. The Data Plan includes seven objectives; in general, the plan seeks to make additional data available for research, increase the speed and transparency of data access, and offer services to enable more efficient data use. The services resulting from the Data Plan are intended to improve support for the entire continuum of a research project, from developing a research question to analyzing the results. Several projects are part of Ministry of Health-led work developing a Health Data Platform.

ResultsThe projects initiated so far as part of the Data Plan include:

BC Data Scout\textsuperscript{TM}: an online tool that provides aggregate cohort information to inform research question development;

REDCap: software to support privacy-sensitive data collection and management;

INFORM: software to support data collection for complex clinical research studies and trials;

Direct Access: enables Population Data BC to access BC Ministry of Health databases so researchers have access to up-to-date data;

Streamlining: making the data request process more efficient;

New datasets: several projects that will provide new data sources, including patient experience and outcome measures and secondary use data drawn from electronic medical records; and

Inventory: an online catalog for all high-value and linkable data sets available to researchers.

Conclusion/ImplicationsThe services and tools included in BC’s Data Plan will help researchers develop and deliver world-class research and inform important health care decisions. The patient-oriented focus of these services help to ensure that research is done in partnership with patients and centered on research questions that matter to them.
BC Data ScoutTM: A New Tool To Investigate Datasets For Health Research
Authors: Kesselring Sarah , Galo Jessica , Sanderson Kelly , Wong Shirley , Neuman Maureen , Mintha Jim , McGrail Kim
Published: September 2018

IntroductionBC’s Ministry of Health (MOH) maintains many administrative databases with rich information and analytical potential. Researchers are keen to use these data for both discovery and applied research. Historically, limited views of data availability and populations therein have supported study feasibility. Therefore, we developed BC Data ScoutTM, a cohort browser.

Objectives and ApproachWe developed a cohort browser service to provide information to researchers planning a study using MOH data. The objective was to create a tool that is simple to use, provides quick results and is free to users to encourage its use. A better understanding of the data available can improve study quality and expand the user-base by giving researchers access to information not previously available during the planning stages. The tool will be evaluated by examining the number of requests received and a user satisfaction survey. Plans are in place to expand into additional data sources and extend query sophistication.

ResultsThe BC Data ScoutTM online tool provides cohort information in the form of highly aggregated, approximate results to researchers planning a study. It was developed by the MOH, the BC SUPPORT Unit and Population Data BC (PopData) and was launched in February 2018. The service is delivered by PopData. BC Data ScoutTM offers province-wide information for query, is accessible to a wide group of eligible researchers, and has data availability from the year 2000 onwards. Four types of MOH data are available for query: hospital data; physician data; pharmaceutical data; and demographics. In addition to determining study feasibility, the aggregate reports also help to further refine a full data access request and provide enough information to complete and strengthen a funding application.

Conclusion/ImplicationsBC Data ScoutTM will be beneficial for researchers planning to request data. This preliminary information may increase the chances of meaningful research studies to obtain funding, and the production of relevant, high-quality research results. BC will be among the first jurisdictions across Canada to offer this type of feasibility service.
Big data and human biosensors – birthweight as a biomonitor for air pollution levels. A population based study using routine data.
Authors: Dibben Chris , Clemens Tom
Published: September 2018

IntroductionIn the natural sciences biomonitors, (organisms, such as pine needles, shells, lichen, that can provide quantitative information on the quality of their past and present environments) have been developed for environmental measurement. In recent year’s physiologists have started to explore if human tissue could also be used.

Objectives and ApproachThe costs of collecting and processing human tissues for biomonitoring, may be too prohibitive for its use in wide scale monitoring. In contrast if biomonitors could be identified within a routine data collection process that were part of standard medical recording a low cost, widely available large sample would be available to scientists. Pregnancy is known to be effected by air pollution, therefore we explore whether birthweight, recorded in maternity records, could be a biomonitor for air pollution.

ResultsWe use maternity records (~1 million births) in Scotland between 2000 and 2015. We modelled, at the individual mother level birthweight, controlling mother’s age, estimated household income, local area crime rates and area level of multiple deprivation. We then aggregate and calculate the averaged of the residuals for this model for all mothers within an intermediate datazones (small areas of around 4000 residents). These mean deviations were then compared with pollution modelled figures produced by AEA for the Scottish government averaged over the same spatial units and time period as the maternity data. "We find a relatively strong correlations (between -0.37 and -0.39) between our ‘biomonitor estimates’ of air pollution derived from the maternity records and the entirely separated modelled air pollution data."

Conclusion/ImplicationsAs far as we know this is the first study to demonstrate that it may be possible to use routine health data to derive ‘biomonitors’ information. Importantly if this method proves to be reliable it will be a relatively cheap method for collecting information that is actually personally monitoring.
Impact of a web-based clinical decision-support system on pulmonary embolism diagnoses
Authors: Haubrich Sydney , Ocampo Wrechelle , Babione Julie , Kaufman Jaime , Ghali William , Altabbaa Ghazwan
Published: September 2018

IntroductionPulmonary embolism (PE) is a disease that offers a diagnostic challenge for physicians. Literature suggests a gap remains between PE diagnostic guidelines and adherence to such guidelines in practice. While computerized decision support systems (CDSS) for PE exist, evidence is lacking on their impact in clinical settings.

Objectives and ApproachThe objective is to evaluate the impact of a web-based PE-CDSS on physician adherence to diagnostic guidelines by collecting and linking chart review data, hospital administrative data, and PE-CDSS usage data from six months before and after the CDSS is deployed. This CDSS was integrated into an electronic medical record system and deployed at two inpatient hospital sites in early 2018. Pre- and post-intervention workups are assigned a score based on their adherence to PE diagnostic guidelines, then compared. Data from a third hospital site with no access to the PE-CDSS will be used as a control.

ResultsPreliminary results will be available by mid-2018. Based on previous research, the investigators expect to see increased provider adherence to diagnostic guidelines for PE in settings where the PE-CDSS was deployed.

Conclusion/ImplicationsImplementing a PE-CDSS may increase provider adherence to evidence-based diagnostic guidelines by providing supportive information about PE diagnosis and addressing uncertainties about clinical decision making. This could result in greater diagnostic accuracy for PE and improved outcomes for patients with suspected PE.
Examination of High-Cost Patients in Ontario
Authors: Homenauth Esha , Graves Erin , Ishiguro Lisa , Saskin Refik , Schull Michael , Wodchis Walter , Tanke Marit
Published: September 2018

IntroductionIn Ontario, the top 5% of high-cost users account for 66% of health care costs. The heavy use of resources combined with perceived inefficiencies offer an imperative to target strategies to redesign care to better meet patient needs and increase value.

Objectives and ApproachAs part of a request submitted to the Applied Health Research Question (AHRQ) review team, the main objective of this study was to identify drivers of high health care use in Ontario in order to find better ways to improve the efficiency in healthcare delivery. Using data in fiscal year 2012/13, characteristics of the top 5% of high costs users were described, and further stratified by mental health status. Total spending by sector of care were also described. Data were linked including physician, hospital, medication and long term care databases for each patient.

ResultsIn the top 5% of high-cost users, there were 729,870 patients who accounted for $20,179,208,348 of total healthcare spending in 2012/13, with the highest percentage of spending observed among older adults aged 61-80 years old. Mental health high-cost patients accounted for 6.1% of these patients, of which 51.5% were female, had a low socio-economic status and an average age of 44 years. These patients had an average of 4.9 (SD=2.3) ICD chapters and used an average of 8.7 (SD=3.8) drugs. Using the health accounts methodology (ICHA), as described by the OECD and WHO, over 90% of healthcare costs among the top 5% of high-cost patients were from inpatient care, day surgery and clinic care, physician care, outpatients drugs and inpatient rehabilitation and complex/continuing care.

Conclusion/ImplicationsThis study provides a systematic description of the needs in a high cost patient group, and serves as a platform for international comparisons across healthcare systems to better understand gaps and identify targets for intervention. These cross-comparisons offer a tool to evaluate performance of healthcare systems and to prioritize policies.
Cultural and institutional barriers among data stewards regarding data access for research
Authors: Teng Jack , McGrail Kim
Published: September 2018

IntroductionIn British Columbia, the rules and procedures that data stewards follow to adjudicate data access requests (DAR) vary considerably. These variations can lead to discrepancies in the speed at which DARs are processed. With complex DARs involving numerous data stewards and data sets, the request may take over a year

Objectives and ApproachOur main goal was to understand the institutional and cultural factors that influence data stewards when processing a DAR. We wished to see in particular if risk aversion was playing a role when making decisions about data access. We interviewed 24 people representing 21 organizations in British Columbia. Most were data stewards, but we also interviewed people processing the data requests and also privacy advisors.

ResultsWe found that organizations varied greatly in terms of their skills and expertise regarding the rules and procedures around processing DARs. In particular, data stewards noted that they experienced differences in interpreting legislation, resulting in disagreements when they were working with other data stewards. In terms of risk aversion, data stewards stated they wished to encourage research, but in some cases followed unclear rules. Nearly all noted that there is little guidance provided for the job of “data steward” and either no or very little training when taking on these positions.

Conclusion/ImplicationsWhile there may be stated governmental policies promoting that linked data be used for research, ultimately it is the data stewards approving DARs that will determine access to data. Understanding how and why they make those decisions will help better implement data access policies.
Medical Needs after Pediatric Traumatic Brain Injury: Probabilistic Linkage of State Claims Data with Trauma Center Data
Authors: Bennett Tellen , Sevick Carter , Cox-Martin Matthew , Gritz Mark , Okada Carol , Kahn Michael
Published: September 2018

IntroductionTraumatic brain injury (TBI) causes enormous morbidity and mortality in both adults and children. Children who survive TBI may have significant disability. It is not known if patterns of outpatient claim use among TBI survivors can be used to estimate patient functional status.

Objectives and ApproachThe objectives of this study are to 1) link regional data sources to create a dataset containing information about the entire continuum of care for children with TBI and 2) identify patterns of outpatient medical needs that can serve as proxies for functional status. We probabilistically linked trauma registry and electronic medical record (EMR) data for children hospitalized after acute TBI at the two pediatric trauma centers in Colorado, Children’s Hospital Colorado (CHCO) and Denver Health (DH), with claims data from the Colorado All Payer Claims Database (APCD) (2009-2014). Probabilistic linkage was performed using LinkSolv (Strategic Matching, Inc., Morrisonville, NY).

ResultsOf 737 hospitalized children, 387 (53%) linked to records in the APCD. Among the children in the linked cohort (213 at CHCO and 174 at DH), the median age was 5 years (interquartile range [IQR] 2 to 13) and 264 (68%) were male. Most had either mild (Glasgow Coma Scale [GCS] 13-15, 51%) or severe (GCS <= 8, 36%) TBI. The 1-year hospital readmission rate among the 355 (92%) survivors was 52/355 (15%). Among the 248/355 (70%) who had a medication claim and the 316/355 (89%) who had an outpatient claim in the first year, respectively, the median number of medication claims was 6 (IQR 2 to 14) and the median number of outpatient claims was 5 (IQR 3 to 11).

Conclusion/ImplicationsWe will leverage the linked registry, EMR, and claims data by using unsupervised machine learning to identify patterns of outpatient care that can serve as proxies for functional status in children who survive TBI. Analyses are ongoing and will be completed by September 2018.