bluuebunny/crossref_metadata_2025_split huggingface dataset:
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.