bluuebunny/crossref_metadata_2025 huggingface dataset:
LinkWise: A Modern Record Linkage Software Application
Authors: Izakian Hesam
Published: September 2018

IntroductionBecause of a lack of unique identifiers among datasets, and different data collection standards, record linkage is challenging. Thus, despite the importance of record linkage in unleashing the power of data, there are few software applications built for this purpose. Each software application has unique strengths and weaknesses.

Objectives and ApproachData linkage comprises various steps such as selecting linkage identifiers, data cleaning, data pre-processing, calculating the linkage weights for identifiers, and estimating similarity thresholds to decide if two records are true matches. These steps require expertise and are costly for organizations interested in data sharing.

Although data linkage software applications have been developed, there are drawbacks with these applications. They are either costly, difficult to use, not able to preserve the privacy of individuals, not able to handle big datasets, or perform poorly in terms of specificity and sensitivity. LinkWise is a software application developed to resolve these issues.

ResultsLinkWise is a probabilistic modern linkage software implemented using Microsoft C#.Net. The following features are implemented in this software: automated all data linkage steps, a simple and user friendly interface, ability to link both unencrypted and encrypted data (privacy preserving record linkage), transparent linkage algorithm (not a black box), ability to perform incremental linkage (linking new data to previously linked data), ability to handle millions of records, ability to run on multiple processors to reduce run time, and high specificity and sensitivity. The software was tested over many datasets with various characteristics (e.g., different data fields, data formats, number of records, various amount of noise etc.). Results show that it is able to link data with a high specificity and sensitivity in a reasonable time.

Conclusion/ImplicationsLinkWise is a software application designed to address many issues arising in the process of data linkage. The software automated all steps of data linkage and preserves the privacy of individuals. It is very easy to use and technical background knowledge is not required to work with this software.
Privacy preserving record linkage meets record linkage using unencrypted data
Authors: Izakian Hesam
Published: September 2018

IntroductionPrivacy preserving record linkage (PPRL) resolves privacy concerns because of its capabilities to link encrypted identifiers. It encrypts identifiers using bloom filters and performs record matching based on encrypted data using dice coefficient similarity. Matching data based on hashed identifiers impacts the performance of linkage due to loss of information.

Objectives and ApproachWe propose a technique to optimize the bloom filter parameters and examine if the optimal parameters increase the performance of the linkage in terms of precision, recall, and f-measure. Let us consider a set of string values and calculate the similarity between any two of them using the Jaro-Winkler method. Now let us encrypt the string values using bloom filters and calculate the similarity between any two of them using the dice coefficient technique. Optimal parameters of bloom filters are those that minimize the difference between the calculated similarities using Jaro-Winkler vs. the calculated similarities using the dice coefficient technique.

ResultsUsing publically available data, several first name and last name datasets each comprising 1000 unique values were generated. The following values for bloom filter parameters were considered: q in q-grams (q=1,2,3), bit array length (l=50,100,200,500,1000), number of hash functions (k=5,10,20,50). The following five setups of bloom filters were able to minimize the difference between the calculated similarities on encrypted data using the dice coefficient technique, and the calculated similarities on unencrypted data using the Jaro-Winkler method: q=1,l=1000,k=50/q=1,l=500,k=20/ q=2,l=1000,k=50/ q=3,l=500,k=50. These setups were considered to perform data linkage over 10 synthetically-generated datasets. Results show that PPRL was able to achieve similar performance compared to data linkage over unencrypted data.

Conclusion/ImplicationsThis study showed that optimal parameters of bloom filters minimized loss of information resulting from data encryption. Experimental findings indicated that PPRL using optimal parameters of bloom filters achieves almost the same performance as data linkage on unencrypted data in terms of precision, recall, and f-measure.
Impact of clinical subtypes of preterm birth on child health and development
Authors: Metcalfe Amy , Brown Paul , McMorris Carly , Chaput Kathleen , Ospina Maria , Ramage Kaylee , Chari Radha , Wilson Doug
Published: September 2018

IntroductionPreterm birth (birth <37 weeks of gestation) is common. While the clinical conditions leading to preterm birth are heterogeneous, most studies examining the short- and long-term consequences of preterm birth on child health and development, only consider the gestational age at delivery, and not the underlying mechanism of preterm birth.

Objectives and ApproachMaternal hospitalization and perinatal data for deliveries occurring in Alberta, Canada in 2004, 2009, and 2014 were linked to identify underlying mechanisms for delivery (i.e., infection/inflammation (I/I), placental dysfunction (PD), both, or neither). Linked hospitalization, emergency department, and physician claims data were used to assess child health outcomes up to age 10. Chi-square tests were used to assess differences in the absolute rate of each outcome stratified by gestational age at delivery and underlying mechanism for delivery. Logistic regression was used to assess relative differences following adjustment for confounders compared to term infants without exposure to I/I or PD.

ResultsA total of 134,424 children were included in the analysis. For preterm births occurring <32 weeks of gestation, no differences were observed in child health outcomes based on the underlying mechanism of preterm birth. However, infants born at 32-33 weeks following PD compared to I/I had significantly higher odds (PD:69.1%, OR=29.7, 95% CI:25.7-34.2 vs. I/I:47.2%, OR=18.7, 95% CI:16.8-20.9) of neonatal morbidity; while those born at 34-36 weeks had increased odds of neonatal morbidity (PD:21.1%, OR=5.1, 95% CI: 4.7-5.5 vs. I/I:16.2%, OR=3.7, 95% CI:3.4-3.9) and developmental disabilities (PD:3.3%, OR=2.2, 95% CI:1.8-2.6 vs. I/I:1.6%, OR=1.7, 95% CI:1.4-2.0). No differences were observed in mortality by sub-type of preterm birth; however, as expected perinatal mortality rates were significantly more common in preterm than term births.

Conclusion/ImplicationsBoth the short- and long-term outcomes of preterm birth differ by the underlying mechanism leading to preterm delivery. Having a clearer prognosis for infants born preterm may promote the use of clinical interventions earlier for children at increased risk, leading to improved child health and development.
Using administrative data to examine mental health service use among post-secondary students in Alberta, Canada
Authors: Lamba Navjot , Jagodzinski Robert
Published: September 2018

IntroductionPoor mental health among post-secondary students has been on the rise, and as such, has become a growing concern for the Alberta government. Alberta’s major post-secondary institutions have emphasized the need for evidence that would improve mental health supports for students troubled by mental health issues.

Objectives and ApproachResponding to the need for evidence, the Child and Youth Data Laboratory profiled the socio-demographic characteristics (sex, socio-economic status, etc) of students who used mental health services between 2005/06 and 2010/11. In addition, using linked administrative data from a range of government programs, the profiles provide new data on the program involvement of post-secondary students who used mental health services, including educational achievement in high school, high cost health service use, the presence of chronic conditions, injury diagnoses, disability status, justice system involvement, income support, and type of mental health condition.

ResultsOver the study period, 7% (~6,000) of post-secondary students received mental health services. Of those, between 11 and 13% were high cost health service users, ~20% received an injury diagnosis, and ~15% had a chronic condition. These proportions were higher compared to the proportions among students who did not receive mental health services. Rates of income support service use, corrections involvement, and students with disabilities were higher compared to students not receiving mental health services. A greater proportion of Canadian students (between 6.5% and 7.1%) compared to non-Canadian students (between 3.4% and 4.1%) received mental health services. In 2010/11, a greater proportion of part-time compared to full-time students were diagnosed with an anxiety disorder (3.4%, part-time; 2.3% full-time) or depression (4.0% part-time; 2.3% full-time).

Conclusion/ImplicationsEvidence produced from linked administrative data offers a unique understanding of students who use mental health services, particularly in terms of their government program involvement. This new evidence can be used, for example, to determine if mental health service needs are different for Canadian versus non-Canadian students, or for full-time versus part-time students.
Cross-validation of Drug Use Records in Two Pharmaceutical Databases: A Population-based Study of Alberta’s Tomorrow Project Cohort
Authors: Ye Ming , Vena Jennifer , Xu Jian-Yi , Robson Paula , Eurich Dean , Johnson Jeffrey
Published: September 2018

IntroductionPharmaceutical Information Network (PIN, 2008-now) is a provincial database collecting patients’ medication information in Alberta, Canada. Alberta Blue Cross (ABC), the largest health benefit provider in Alberta, has been managing pharmaceutical records for senior patients (65+ years) whose medications are covered by Alberta’s government-sponsored health benefit plan since 1970s.

Objectives and ApproachOver 96% of participants in Alberta’s Tomorrow Project (ATP), a province-wide cohort study of cancer and chronic diseases in Canada, consented to data linkage to healthcare databases. To cross-validate medication records in the two pharmaceutical databases in Alberta, individual-level data of ATP participants aged 65+ years were cross-linked between PIN and ABC databases (2008-2015) using Personal Health Numbers. Concordant and discordant records were identified by whether or not a specific record co-existed in the two databases. Concordance and discordance (discrepancy) rates, i.e. percentage of concordant or discordant records, were estimated by years and drug types.

ResultsDuring 2008-2015, there were 1,116,176 records collected by PIN, 1,005,548 records collected by ABC, and a total of 1,218,191 records collected by both for 13,413 ATP participants. The average discrepancy rate between PIN and ABC was 25.8%, and the rate was significantly lower for drugs commonly prescribed for health conditions in seniors, including cardiovascular diseases (18.7% for statin), hypertension (18.9% for beta blockers, ace inhibitors and diuretics), diabetes (23.8% for glucose lower drugs), COPD (20.2% for inhalers) and stomach disorders (22.3% for H2 antagonists and proton pump inhibitors), compared to other drugs (34.4%). For insured drugs, using ABC as reference database, 88.6% of ABC records were concordant with (co-existing in) PIN. The concordance rate for insured drug use was improved by 10% over 2008-2015.

Conclusion/ImplicationsBy cross-linking two pharmaceutical databases in Alberta for senior ATP participants, we found remarkable discrepancies in pharmaceutical records between PIN and ABC, although there was noticeable improvement over the years. The discrepancy rate between PIN and ABC was drug-specific and significantly lower for drugs commonly prescribed in senior patients.
Mortality attributable to poor dietary patterns in Canada: Evidence from the nationally-representative nutrition survey linked with health administrative data
Authors: Jessri Mahsa , Hennessy Deirdre , Sanmartin Claudia , Eddeen Anan Bader , Manuel Doug
Published: September 2018

IntroductionDietary pattern modeling and linkage with health outcomes is essential for development of evidence-based dietary guidelines to support reduction of chronic diseases. National nutrition surveys are not routinely linked with health administrative databases, resulting in a lack of evidence on the health impact of unhealthy diets at the population level.

Objectives and ApproachThis study is the first to use a nationally-representative nutrition survey (i.e., Canadian Community Health Survey-Nutrition-2004) linked with health administrative databases to examine the association of 5 key dietary quality indices with mortality risk. In total, 16,212 adults ≥20 years were followed for an average of 7.3 years. Two 24-hour dietary recalls were used to estimate the usual dietary intakes using the National Cancer Institute’s method. Weighted regression calibration was performed to obtain a true parameter relating diet (continuous) to mortality. Population Attributable Fractions were calculated to estimate the burden of all-cause mortality attributable to poor dietary patterns in Canada.

ResultsThe 5  dietary quality indices examined were Dietary Approaches to Stop Hypertension(DASH); Dietary Guidelines for Americans Adherence Index 2015(DGAI); Healthy Eating Index-2010(HEI); Alternative HEI-2010(AHEI); and Mediterranean Style Dietary Pattern Score(MSDPS). Having a better diet quality (90%ile vs. 10%ile of index score) was associated with a significant 31-51% reduction in all-cause mortality hazard ratio among adults 45 to 80 years and 10-35% reduction in those ≥20 years (in order of significance: DASH, DGAI, HEI, AHEI and MSDPS). Survival benefit was incrementally greater for higher diet quality scores; however, even the 90%ile scores (Reference) were notably lower than the recommended levels (45.99% of recommended score). On average, 26.42% of all mortality in Canada was attributable to poor dietary patterns (range: 19.01% for MSDPS to 31.39% for DGAI).

Conclusion/ImplicationsThe diet-attributable burden of mortality was higher than those reported for other behavioural risks (e.g., smoking). This research informs future formulation of nutrition interventions and policies with a focus on dietary patterns. This project demonstrates the importance of leveraging linked data and analytical capacity to inform future evidence-based nutrition policies.
Utilizing population-based clinical and administrative data to estimate the incremental healthcare costs of dementia and frailty among community-residing care recipients.
Authors: Mondor Luke , Maxwell Colleen , Bronskill Susan , Campitelli Michael , Hogan David , Wodchis Walter
Published: September 2018

IntroductionCurrent cost estimates for dementia in Canada are lacking and no studies have yet to examine the incremental healthcare costs associated with both dementia and frailty, despite evidence of increasing prevalence of both conditions and their bidirectional association. These data are essential for informed clinical and public policy programs.

Objectives and ApproachUsing linked clinical and health administrative databases in Ontario, we conducted a cohort study of all long-stay home care clients aged 50+ years with a clinical assessment between April 2014 and March 2015 (n=160,209). We defined dementia using a validated algorithm, and frailty categories (robust, pre-frail, frail) using a modified frailty index from clinical assessment data. Clients were followed prospectively for 1-year, for which we obtained total- and sector-specific healthcare costs for all encounters. We calculated cost differences (in $2015CAD) between dementia-frailty groups using a survival- and covariate-adjusted cost estimator described by Manning and Basu (2010) that included dementia-frailty interactions.

ResultsIn this population-based cohort of long-stay home care recipients, the prevalence of dementia was 26.8% and 33.3% of these clients were frail (vs. 26.9% among clients without dementia). Approximately 15% of the cohort died over the 1-year follow-up. The average 1-year estimated total health system cost was $26,965. On average, home care clients with dementia categorized as frail incurred $14,291 (SE=$139) more in charges than similar robust clients ($35,381 vs. $21,091, respectively). In contrast, frail persons without dementia incurred $12,796 (SE=$95) more in charges that similar robust clients ($33,659 vs. $20,864, respectively). Among frail persons, those with dementia incurred $1,722 (SE=$149) more in expenditures, on average. Wide variation in sector-specific costs were also observed by dementia and frailty strata.

Conclusion/ImplicationsDementia and frailty pose significant challenges to healthcare systems. Our findings illustrate large incremental costs associated with frailty, regardless of dementia status. Further research using the linked clinical assessment and administrative data is needed to inform variations in, and to delineate key drivers of, formal healthcare and informal care costs associated with dementia and frailty.
Development of a Concept Dictionary to Standardize Definitions and Classifications While Working With a Common Repository of Linked Administrative Data
Authors: Macdonald Erin , Chu Anna , Cooper Michelle , Croxford Ruth , Duchen Raquel , Fung Kinwah , Gandhi Sima , Gatley Jodi , Jin Fiona , Khuu Wayne , Kopp Alex , Maclagan Laura , Porter Joan , Stumpo Robert , Zaidi Ali Syed , Azimaee Mahmoud
Published: September 2018

IntroductionSupporting standardized approaches to common tasks is an important component of quality research using linked administrative data. Standard concept definitions and classifications are vital for ensuring accuracy and consistency in definitions between projects, and improving efficiency and quality. Other leading organizations have published online standard definitions of concepts and classifications.

Objectives and ApproachWe developed a comprehensive concept dictionary using a standardized definition template of key components including data sources, codes, scale or range of values, validation details, limitations, SAS code and formats, related concepts, and MeSH terms. A web-based application (built on the Microsoft SharePoint platform) was developed to offer the latest web content authoring capabilities, and advanced search mechanisms enabling the user to search concepts by MeSH terms and key words. It also allowed for navigating concepts through category navigation including clickable categories and sub-categories. Entries will be reviewed annually to ensure the content remains up-to-date.

ResultsTo date, ten concepts, with accompanying codes, have been published on the concept dictionary with another ten currently undergoing editorial review. These concepts span a variety of topics such as injuries, mental health and addictions-related outpatient services, and annual physical exams. New concepts written by content experts and reviewed by an editorial committee will be added on an on-going basis; thirty concepts are currently under development.

Conclusion/ImplicationsDevelopment of a concept dictionary provides standardized definitions, algorithms and codes to ensure consistency and quality of research and analysis across multiple projects. Future aims include expansion of the internal organizational site to an external site through collaboration with key stakeholders.
Extending follow up of randomised clinical trials by linkage to routinely collected data – results of a scoping review of the published literature
Authors: Fitzpatrick Tiffany , Perrier Laure , Lix Lisa , Rosella Laura , Henry David
Published: September 2018

IntroductionAlthough RCTs remain the gold standard for generating clinical evidence, follow up of participants to study long-term effects is limited by cost and other logistical considerations. Linkage of participant information to routinely collected data potentially offers a cost-effective solution to achieving long-term follow-up of treatment effects

Objectives and ApproachThis scoping review aimed to identify RCTs that had been extended by record linkage, and characterize these in terms of nationality, numbers of trials, disease areas and outcomes, types of data, linkage modes and duration of follow-up. We followed published guidelines for the conduct of scoping reviews, with a registered protocol and comprehensive literature search. Criterion-based selection of studies and extraction of date were performed in duplicate. Descriptive statistics were used to summarise the characteristics of eligible studies.

ResultsOne hundred thirteen RCTs had been extended by record linkage. Fifty-six were conducted in Nordic countries, 26 in the USA and 24 in the UK. Types of linkage data used were: vital statistics 36, adimistrative data 31, cancer registry 28, special registries 13 and others 11. The literature spanned 45 years, but 66 (58%) were published between 2010 and 2016. Linkage methods were reported as: deterministic 33, probabilistic 16 and unspecified 64. In 44 studies researchers reported ethics approval for linkage; this was not obtained in 39 cases and was absent in 30 reports. The overall follow up times achieved by record linkage were: 1-4 y (6 studies), 5-9y (34), 10-19y (48), 20-29y (21), 30-39y(4) and over 50y (1).

Conclusion/ImplicationsAlthough we uncovered over 100 RCTs that were extended by record linkage this is tiny compared with the number of trials that have been undertaken. Linkage to routinely collected data seems to be a feasible but under-used approach to extending the follow-up of clinical trial participants for very long periods.
Osteoporosis and fracture risk - a linked data study in Wales
Authors: North Laura , Davies Llion , Berridge Damon , Walters Angharad , Akbari Ashley , Lyons Ronan
Published: September 2018

IntroductionOsteoporosis is a global disease with a 30-40% lifetime fracture risk according to the World Health Organisation. Over half a million people receive treatment for fragility fractures annually in the UK. Osteoporosis incidence is rising with aging populations; however, medical secondary prevention treatment may reduce fracture risk.

Objectives and ApproachPrimary aims were to investigate if secondary medical prevention treatment following an index fracture was associated with survival and subsequent fracture risk, evaluated using a pseudonymised population based e-cohort study design. Patients aged ≥60 years with an index fragility fracture at any anatomical location were identified from the Secure Anonymised Information Linkage (SAIL) databank. Fracture data were identified from secondary care datasets (emergency department and inpatient) and the National Hip Fracture Register data. In addition linkages were made to primary care datasets for medical prescription and Office for National Statistics records for mortality, supplementing data on demographic characteristics and co-morbidity.

ResultsThe cohort comprised 81,252 cases between April 2009 and December 2016 of median age 78 years (range 60-109) and 22,896 (28%) males. Medical secondary prevention treatment was received by 29,393 cases (36%). Subsequent fractures were reported for 10,907 cases (14%) and 29,026 cases (36%) died during the study period. For those that received medical prevention, the subsequent fracture and mortality rates were 15% and 28% respectively compared to 12% and 31% for those that did not receive the prevention treatment. Further analyses will include a discrete time competing risks model.

Conclusion/ImplicationsA population based e-cohort was successfully created by linking data across multiple datasets. Preliminary findings identified that <50% of eligible patients receive secondary medical prevention treatment after an index fragility fracture. These findings may help inform and unify treatment pathways for those at risk of fragility fractures.
Using Administrative Data to Evaluate the Effectiveness of Home Visiting Programs for Improving the Well-Being of First Nations Children and Parents
Authors: Chartier Mariette , Brownell Marni , Nickel Nathan , Campbell Rhonda , Phillips-Beck Wanda , Enns Jennifer , Sarkar Joykrishna , Burland Elaine , Chateau Dan
Published: September 2018

IntroductionThe province-wide Families First Home Visiting Program (FFHV) provides home visiting to families with children living in conditions of risk. It remains unknown if First Nations families are benefiting from the program. Using existing administrative and population-wide data is an innovative practice to evaluate programs that have been scaled up.

Objectives and ApproachThe objective is to determine FFHV’s effectiveness at improving outcomes for First Nations children and parents. The partnership with First Nations Health and Social Secretariat of Manitoba facilitated access to First Nations identifiers and provided guidance in conducting the study. Program data from 4,010 First Nations children and parents were linked at an individual-level to administrative data housed at the Manitoba Centre for Health Policy. We compared the predictive probability of outcomes of program and non-program families. Inverse probability of treatment weights were used to adjust for confounders related to both entry into FFHV and the outcomes under study.

ResultsThe cohort of First Nations children and parents was successfully linked through an individual scrambled health identifier. FFHV was associated with higher rates of child immunization at age one (71% versus 66%) and age two (47% versus 41%) and parental involvement in community support groups (21% versus 17%). It was also associated with lower rates of being in care of child welfare at age one (10% versus 14%) and age two (15% versus 19%); maltreatment-related hospitalizations at age three (0.4% versus 1.0%); and child victimization as measured by justice system records (1.7% versus 3.0%). However, there were no differences in being “not ready for school” between the two groups of children, nor between the groups of mothers in physician visits for mental health reasons.

Conclusion/ImplicationsHome visiting services can play a role in supporting healthy development of First Nations children by providing support to parents and connecting children to health and social services, however, there also remains an urgent need for long term strategies to address structural inequality and the ongoing effects of colonization.
Validating health conditions in a clinical registry using administrative data algorithms
Authors: Lix Lisa , Zhang Lisa , Yan Lin , Sajobi Tolu , Sawatzky Richard , Bohm Eric
Published: September 2018

IntroductionClinical registries are a potentially valuable resource to study the effects of medical interventions on outcomes, particularly patient-reported outcomes like health-related quality of life, which are not included in administrative data. However, because clinical registries are primarily intended for patient management and not for research, their validity must be established.

Objectives and ApproachOur objective was to validate patient self-reported health conditions in a clinical registry. Study data were from a population-based regional joint replacement registry in the Canadian province of Manitoba. The clinical registry data were linked to administrative health data. Validated administrative data algorithms for 12 conditions were defined using diagnosis codes in hospital and physician records and medication codes in prescription drug records for the period up to three years prior to the joint replacement surgery. Accuracy of the clinical registry data was estimated using Cohen’s kappa coefficient, sensitivity, specificity, and positive and negative predictive values (PPV; NPV); 95% confidence intervals were also estimated. Analyses were stratified by joint type, age group, and sex.

ResultsThe study cohort included 20,592 individuals (average age 66.3 years; 58.4% female); 8,424 (40.9%) had a total hip replacement. Sensitivity of the clinical registry data ranged from 16% (anemia) to more than 70% (diabetes, high blood pressure, rheumatoid arthritis); specificity was greater than 92% for all conditions, except back pain and high blood pressure. PPV ranged from 19% (back pain) to 83% (diabetes). Chance-adjusted agreement was very good for diabetes (kappa: 0.74), moderate for heart disease and high blood pressure (kappa range: 0.41-0.53) and poor or fair for back pain, anemia, cancer, depression, kidney disease, liver disease, rheumatoid arthritis and stomach ulcers (kappa range: 0.14-0.37). Estimates varied by sex (i.e., generally higher agreement for females) and age (i.e., generally lower agreement for older age groups), but not joint type.

Conclusion/ImplicationsSelf-reported health conditions in registry data had good validity for conditions with clear diagnostic criteria, but low validity for conditions that are difficult to diagnose or rare (e.g., cancer). Linked registry and administrative data is strongly recommended to ensure valid and accurate comorbidity measures when developiong risk prediction models and conducting inter-jurisdictional comparisons of patient-reported outcome measures.
A framework to facilitate interprovincial sharing of secondary health data in Canada
Authors: Urquhart Robin , Maillet Donna Curtis , White Bev , MacDougall Jeanne
Published: September 2018

IntroductionThe use of administrative health data can generate knowledge to improve the delivery and outcomes of health care. Yet, the sharing and use of secondary health data presents concerns given these data were not collected for health research purposes. The sharing of patient-level health data across Canadian provinces is uncommon.

Objectives and ApproachThe Maritime SPOR SUPPORT Unit (a patient-oriented research unit serving the three Canadian Maritime Provinces of New Brunswick, Nova Scotia, and Prince Edward Island) struck a Working Group to develop a conceptual framework for the interprovincial sharing of secondary health data for research purposes. Membership comprised a researcher, two privacy managers/officers, and a manager of research ethics. The framework sought to: (1) facilitate researchers’ understanding of the foundational elements (legal/ethical) of interprovincial data sharing for health research; and (2) identify challenges and opportunities for improving sharing of data across the Maritime Provinces to support patient-oriented research.

ResultsIn all three Maritime provinces, de-identified personal health information may be used for approved health research purposes, with each province having its own data holdings and repositories. Applying the applicable governance principles and regulations (i.e., the ethical governance of research involving human subjects and the legal governance of health information) and drawing on best practices nationally and internationally, a framework was developed to incorporate and address the various aspects of sharing and using health data across provinces for the purposes of health research. The resultant framework discusses when and how the legal and ethical frameworks apply, the de-identification of data, degrees of data sharing, and information governance. It also identifies challenges and opportunities to moving forward with interprovincial data sharing.

Conclusion/ImplicationsDevelopment of this framework was the first phase of a multi-phase approach to move towards improved interprovincial data sharing for patient-oriented research. Cross-provincial sharing and linkage of data can lead to comprehensive, cost-effective, and multi-disciplinary research that benefits patients, the health system, and the public at large.
Data Services for Cohort Studies: Increasing the impact of existing research studies and epidemiological readiness
Authors: North Laura , Orton Christopher , Gallacher John , Lyons Ronan , Ford David , Thompson Simon , Bauermeister Sarah , Akbari Ashley
Published: September 2018

IntroductionThe Dementias Platform UK (DPUK) Data Portal is a secure, accessible environment facilitating provision of rich data towards the largest Dementia, cognition and ageing community of cohort studies in the world. DPUK is also providing services for cohort studies and researchers to maximise the research potential of the programme’s community.

Objectives and ApproachAs part of the engagement of DPUK cohorts with the Data Portal, cohorts will upload data onto the DPUK instance of UK Secure eResearch Platform infrastructure. The Data Portal allows access to a collaborative working space that allows cohorts to enrich their own data, perform their own analysis, and enhance the research potential of their data whilst making use of expertise at various DPUK sites, such as data linking, curation and multi-modal specialism. Cohort data divided into ontologies allows researchers to access data specific to their study needs and can be requested from multiple cohorts simultaneously.

ResultsBy utilising the Data Portal researchers have access to cohort data that has been prepared for dementia epidemiology using the agreed ontologies, providing more rapid access to cohort data that otherwise may be large and complex. The knowledge and experience of DPUK staff and collaborators can also help to guide nascent cohorts and feasibility studies into producing research-ready datasets, enabling them to achieve greater impact with their data. A range of analytical tools are provided on the Data Portal making analysis of a cohort’s own data or multiple independent datasets more accessible. Alongside data curation, DPUK also facilitates data linkage to routine sources, beginning with a Wales-wide use case that will expand to the UK over the course of the project.

Conclusion/ImplicationsData from international sources accessible using a central platform permits international collaboration, with ontologies allowing previously disparate data to be combined and analysed to build knowledge and research impact. DPUK projects create policy leading results and operational research standards, enhancing cohort impact and discovery of benefits for Dementia patients.
Using natural language processing to extract structured epilepsy data from unstructured clinic letters
Authors: Fonferko-Shadrach Beata , Lacey Arron , Akbari Ashley , Thompson Simon , Ford David , Lyons Ronan , Rees Mark , Pickrell Owen
Published: September 2018

IntroductionElectronic health records (EHR) are a powerful resource in enabling large-scale healthcare research. EHRs often lack detailed disease-specific information that is collected in free text within clinical settings. This challenge can be addressed by using Natural Language Processing (NLP) to derive and extract detailed clinical information from free text.

Objectives and ApproachUsing a training sample of 40 letters, we used the General Architecture for Text Engineering (GATE) framework to build custom rule sets for nine categories of epilepsy information as well as clinic date and date of birth. We used a validation set of 200 clinic letters to compare the results of our algorithm to a separate manual review by a clinician, where we evaluated a “per item” and a “per letter” approach for each category.

ResultsThe “per letter” approach identified 1,939 items of information with overall precision, recall and F1-score of 92.7%, 77.7% and 85.6%. Precision and recall for epilepsy specific categories were: diagnosis (85.3%,92.4%),  type (93.7%,83.2%), focal seizure (99.0%,68.3%), generalised seizure (92.5%,57.0%), seizure frequency (92.0%,52.3%), medication (96.1%,94.0%), CT (66.7%,47.1%), MRI (96.6%,51.4%) and EEG (95.8%,40.6%). By combining all items per category, per letter we were able to achieve higher precision, recall and F1-scores of 94.6%, 84.2% and 89.0% across all categories.

Conclusion/ImplicationsOur results demonstrate that NLP techniques can be used to accurately extract rich phenotypic details from clinic letters that is often missing from routinely-collected data. Capturing these new data types provides a platform for conducting novel precision neurology research, in addition to potential applicability to other disease areas.
A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
Authors: Lloyd Keith , John Ann , Craddock Nick , Walters James , Linden David , Jones Ian , Bentall Richard , Lyons Ronan , Lee Sze Chim , Owen Michael
Published: September 2018

IntroductionPsyCymru was established to investigate the feasibility of linking a prospectively ascertained, well characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking genetic data.

Objectives and ApproachPsyCymru aimed to create a research platform for psychosis research in Wales by establishing two cohorts. The first was a well-characterised clinically assessed cohort with genetic data. Consented individuals underwent structured interviews using well-validated questionnaires and gave blood sample for DNA extraction, sequencing, and candidate gene identification. This data was then linked to routinely collected health and social datasets with identity encryption. The second is a larger e-cohort of prevalent psychosis cases created using a validated algorithm applied to anonymised routine data. Both cohorts were tracked prospectively and retrospectively in the Secure Anonymised Information Linkage (SAIL) databank.

ResultsIn total, data from 958 individuals for the clinical cohort were imported to SAIL. Among these individuals, genetic data for 740 were analysed. The genetic data included robust loci for schizophrenia, pathogenic copy-number variations (CNVs) for various conditions (e.g., autism, intellectual disability, congenital malformations), polygenic risks scores for schizophrenia, as well as pathogenic/non-pathogenic duplications or deletions of chromosome spanning more than 500kb or 1Mb. For the e-cohort, 29,797 individuals were found having a psychosis diagnosis from primary and secondary care between 2004 to 2013. Social demographic data for both cohorts were also analysed based on sex, age, area deprivation, urbanicity, and employment status.

Conclusion/ImplicationsThis unique platform pooled data together from multiple sources; linking clinical, psychological, biological, genetic, and health care factors to address assorted research questions. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned.
A National Concept Dictionary
Authors: Azimaee Mahmoud , Victor J. Charles , Vermeulen Marian , Smith Mark
Published: September 2018

Overall objectives or goalMost of the organizations that use population administrative data for research purposes have internal repository of validated definitions and algorithms of their own. Many of these concepts and definitions are applicable or at least adaptable to other organizations and jurisdictions. A comprehensive National (and potentially International) Concept Dictionary could help investigators to carry out methodologically sound work using consistent and validated algorithms using a shared pool of knowledge and resources.

The Institute for Clinical Evaluative Sciences (ICES) in Ontario, Canada has recently modernized its internal Concept Dictionary by adopting standard templates based on the Manitoba Centre for Health Policy (MCHP) Concept Dictionary, reviewing and updating existing content and tagging the concept entries with appropriate MeSH terms and data sources, and adding standard computer code (e.g., SAS coding) where appropriate. A SharePoint® web-based application has been developed to provide advanced tagging, searching and browsing features.

We envision a wiki-based Concept Dictionary hosted on a cloud-based environment with very granular access controls to provide enough flexibility for each participating organization to control their own content. This means each organization will be able to decide on how to share their own concepts (or part of them) with the public or internal users.

All content will be tagged with MeSH terms and as well with the organization’s name that initially posts each entry. Other organizations which find the same concept applicable to their own use can tag the same entry with their organization name or refer to a secondary adapted entry if adaptation to fit their data and methodologies is required.

The Search feature will allow refining the search criteria by MeSH terms, data sources, and also organization/jurisdiction name.

Multiple layers of access controls will allow each organization to have their own groups of users with different standard privileges such as Local Administrators, Authors and Approvers (or Publishers).

The Approver (Publisher) users within each organization can publish each entry for internal or public view. This way, for example, a definition/algorithm can be viewable only within the organization until the validation process is complete, and then the entry can be made publically available, while some sections, such as computer code, can remain restricted to the organization.

We will discuss challenges in developing and maintaining such a platform including the costs, governance, intellectual property rights, copyrights and liabilities for the participating organizations.

The intended output or outcomeWe aim to use this opportunity to form a working group from the interested organizations that are ready to participate and commit in developing this collaborative platform. After the conference, there will be follow up sessions with the members of the working group to plan and develop the online application.
Interaction between mother’s age and schooling at birth on under-five mortality
Authors: Aguiar Fernanda , Guimarães Patricia , Guillen Luis Carlos , Camargo Kenneth , Sobrino Rejane
Published: September 2018

IntroductionPregnancy at age extremes and low maternal schooling are associated with under-five mortality. However, we found no study in the literature that evaluated the interaction between mother’s age and schooling on under-five mortality measured in both multiplicative and additive scales.

Objectives and ApproachTo analyze the interaction between mother’s age and schooling on under-five mortality in a birth cohort in Rio de Janeiro City (Brazil) (N=153,527 live births). We carried out a non-concurrent cohort study using probabilistic record linkage of birth and death records for Rio de Janeiro (Brazil). The association between under-five mortality according to mother’s age (15-19, 20-34 and 35 years or more) and schooling (less than 4 years; 4 to 11 years and 12 or more years of schooling) were estimated using generalized linear models with binomial distribution and Neperian logarithm function. The interaction was evaluated in both scales.

ResultsThe under-five mortality rate was 14.0 per thousand live births. Higher rates were observed among women with less than 4 years’ schooling and in age extremes. When compared with women aged 20 to 34 years and with more than 12 years’ schooling, these women had the following risk ratios: 15 to 19 years – RR = 3.66 (95% CI 2.39; 5.62); 35 years or more – RR = 2.74 (95% CI 1.83; 4.11). We did not observe statistically significant interactions in the additive and multiplicative scales.

Conclusion/ImplicationsAlthough we did not observe an interaction between mother’s age and schooling, under-five mortality was more frequent among women with less the four years’ schooling, especially at the age extremes, suggests these are more vulnerable groups that demand greater attention in care.
Harnessing the Power of Administrative Data to Create a Provincial-Level Child Heath Profile and Birth Cohort in New Brunswick (NB) and Prince Edward Island (PEI)
Authors: Tranchant Carole , Montelpare William , Bélanger Mathieu , Miedema Baukje , Sénéchal Martin
Published: September 2018

IntroductionEarly-life prevention of chronic diseases is crucial to a healthy adulthood. However, evidence is often lacking to assess the effectiveness of early intervention programs, partly because of failure to make use of existing data. This project aims to capitalize on existing administrative data in two provinces to address this gap.

Objectives and ApproachTo identify and evaluate selected administrative databases (AD) from NB and PEI to create an intra-provincial Child Health Profile (CHP) and establish the foundation for a population-based birth cohort database in each province using existing administrative data. Integrated knowledge translation (iKT) was implemented to facilitate the continuous involvement of knowledge users and stakeholders, including provincial government managers/decision-makers, data custodians, health practitioners, parents and community organizations. Consultations were held to identify the AD of interest and develop a roadmap for the CHP. For each dataset, a list and description of data and analytical variables was produced and data access requested.

ResultsNot all AD identified are equally complete and accessible to researchers. Data access, preparation and linkage are challenging but feasible. This process was facilitated by iKT, which also contributes to capacity building. Several AD, mainly healthcare AD, including the Healthy Toddler Assessment and NutriSTEP, are currently accessible. An analytic framework was developed for pulling the data together and planning their analyses to produce the CHP. Based on the data currently accessible, the first CHP will focus on data at birth and at 18 months. Other databases (e.g., preschooler assessments) may be included subsequently. Work is underway to create workable datasets from which the CHP and roadmap for the birth cohort are being developed. This approach is scalable and can be extended to other jurisdictions.

Conclusion/ImplicationsSelect AD in NB and PEI are rich resources for establishing a comprehensive CHP and population-based birth cohort database in each province. These new tools will enable various stakeholders to monitor and report on child health over the long term, and to evaluate current practices and future health interventions.