bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the impact of timing of initiation of community-based palliative care on use and cost of unplanned acute care services at the end of life: A study using linked hospital and community based provider service data
Authors: Moorin Rachael , Wright Cameron , Youens David 
Published: September 2018

IntroductionExpected time to death is often used to determine eligibility to publicly funded community-based palliative care (CPC) because most acute care costs in the end-of-life period are incurred immediately prior death. We know CPC use reduces acute care costs but the impact of timing of initiation is unknown.
Objectives and ApproachWe explored the association between timing of CPC initiation and unplanned hospital use, over the final year of life for Western Australian cancer decedents who died between 1/1/2001 and 31/12/2011 using linked Cancer Registry, Mortality System, Hospital Morbidity Data Collection, Emergency Department (ED) Data Collection and CPC records. The relationship between first-time use of CPC and unplanned hospitalisations and ED presentations was evaluated using multivariable negative binomial regression and Cragg-hurdle models. The exposure was month of CPC initiation (adjusted for intensity of use); outcomes were the rate, length of stay and cost of unplanned hospitalisations and emergency department presentations.
ResultsOf the 28,331 decedents residing in the CPC catchment area, 16,439 (58%) accessed CPC, mostly (64%) in the last three months of life. Initiation of CPC prior to the last six months of life was associated with a lower mean number of unplanned hospitalisations in the last six months of life (1.4 versus 1.7 for initiation within six months of death); associated average costs were also lower ((AU$, 2012) 12,976 versus $13,959). While patients initiating CPC earlier showed a trend toward fewer hospital admissions, earlier initiation was associated with a higher cumulative and average length of stay. Indirect adjustment for admission complexity suggests that this may be due to more complicated indications.
Conclusion/ImplicationsThis study provides more detail to guide policy around timing of access to CPC. Our results argue against restricting access to the final few months of life, as earlier initiation may result in fewer and lower the cost of unplanned hospitalisations and ED presentations at the very end of life.
Using routinely collected laboratory and health administrative data to assess influenza vaccine effectiveness: introducing the Flu and Other Respiratory Viruses Research (FOREVER) Cohort
Authors: Kwong Jeff , Buchan Sarah , Chung Hannah , Campitelli Michael , Schwartz Kevin , Crowcroft Natasha , Jackson Michael , Karnauchow Timothy , Katz Kevin , McGeer Allison , McNally Dayre , Richardson David , Richardson Susan , Rosella Laura , Simor Andrew , Smieja Marek , Zahariadis George , Gubbay Jonathan 
Published: September 2018

IntroductionAnnual evaluation of influenza vaccine effectiveness (VE) is required because of frequent changes to circulating and vaccine strains. Traditionally, VE studies enroll patients who fulfill case definitions for respiratory infections and are tested for influenza. VE estimates generated from convenience samples of routinely collected specimens might be biased.
Objectives and ApproachWe assessed the validity of using data from respiratory specimens collected during clinical encounters to estimate VE. We created the Flu and Other Respiratory Viruses Research (FOREVER) Cohort by linking respiratory virus laboratory test results from 2009-2014 from 11 public health and 8 hospital laboratories across Ontario to health administrative databases, including databases with billing claims for physician- and pharmacist-administered influenza vaccines. We evaluated the presence of information and selection biases when using these data and estimated VE in community-dwelling older adults (>65) using the test-negative design under conditions that emulated the inclusion criteria in traditional VE studies.
ResultsThe FOREVER Cohort included test results from 283,711 respiratory specimens obtained from 216,730 individuals. The overall linkage proportion to health administrative databases using deterministic and probabilistic linkage methods was 97.5%. Influenza positivity for older adults with unknown lag between illness onset and specimen collection was similar to those for whom illness onset date was documented to be ≤7 days before specimen collection, suggesting minimal outcome misclassification associated with information bias. The likelihood of influenza testing was similar between vaccinated and unvaccinated individuals, suggesting an absence of selection bias that could arise when a case definition for influenza testing is not employed. Lastly, VE estimates were similar under various conditions, demonstrating the robustness of using these data, and were comparable to published estimates.
Conclusion/ImplicationsThe FOREVER Cohort can be used to estimate VE with negligible bias. Compared to traditional VE studies that are limited to recruited patients, routinely collected specimens create a larger, more generalizable sample. Linkage to health administrative databases can identify those with comorbidities and permit evaluation of VE in high-risk groups.
When does the increased mortality risk appear in rheumatoid arthritis? A distributed data analysis comparing mortality in two Canadian provinces
Authors: Widdifield Jessica , Bernatsky Sasha , Huang Anjie , Paterson Michael , Sayre Eric C , Lacaille Diane 
Published: September 2018

IntroductionRheumatoid arthritis (RA) is chronic inflammatory arthritis. For decades studies showed that RA patients died earlier than their general population counterparts. Some inception cohorts have failed to detect an increased mortality risk, possibly due to limited follow-up or to improvement in mortality risk in cohorts of more recent onset.
Objectives and ApproachWe evaluated mortality risk in RA patients and estimated when the increased risk appears. Using a common protocol, we conducted distributed analyses using administrative data, of incident RA patients in British Columbia (BC) and Ontario (ON) over 2000-2015. We identified all RA patients (using validated criteria), and identified non-RA comparators, matched 1:2 on age, sex and index years. Adjusted hazard ratios (HRs) were estimated using multivariable Cox regression, controlling for comorbidities and other factors. To estimate when the increased risk appeared we included an interaction with follow-up time, to detect if and how the HR varied by RA duration.
ResultsAmong 13834 RA patients in BC (27668 comparators), 66% were female with a mean age of 58 years at cohort entry. Among 27405 RA patients in ON (54810 comparators), 70% were female with a mean age of 56 years. The prevalence of individual comorbidities was comparable across RA cohorts. During follow-up, 23% of RA patients in each province died, with corresponding crude mortality rates of 2.3 deaths per 100 person-years in both provinces. Multivariable analyses detected an increased mortality risk in RA by 6 years of follow-up, with a linear relationship suggesting further increase over time. By 10 years, the adjusted HR was 1.14 (95% CI 1.07,1.22) in BC and 1.13 (95% CI 1.08,1.18) in ON.
Conclusion/ImplicationsIn 2 large Canadian RA inception cohorts, a small increased mortality risk appeared after 6 years of RA duration and increased to a 14% (in BC) and 13% (in ON) increased mortality risk after 10 years, suggesting increased efforts to prevent disease progression and optimizing comorbidity management are needed.
Supporting the timely, easy and cost effective access to high-quality linked data via the Custodian-Controlled Data Repository
Authors: Schneider Matthias , Radbone Chris , Stanley Andrew , Woollacott Anthony , Churches Timothy , Farrow James , Basso Paul , Hardin Tina , McNamara Martin , Harrison James 
Published: September 2018

IntroductionWhile linkage units perform population data linkage with high efficiency, other parts of the workflow from custodians to researchers remain largely outside the control of linkage operators. Most importantly, resource constraints at data custodians often limit quality control (QC) efforts and lead to delays in the data delivery to researchers.
Objectives and Approachovercome these challenges, we have created the Data integration Unit (DIU) to undertake content data management and delivery in conjunction with the custodians who remain the principal data curators. Data is managed in the Custodian-Controlled Data Repository (CDDR) a highly secure virtual repository for data storage, analysis and access, established and operated by the DIU. Stringent controls for user access and data flows ensure that data is provided safely by custodians. Overseen by the custodians, DIU staff undertake QC activities, and integrate and deliver multiple datasets for approved linkage projects.
ResultsLong-term data storage in the CCDR decreases data custodian workloads by reducing the frequency of content data provision to periodic updates. Feedback loops built into the QC process allow custodians to improve their datasets by learning from data issues identified by the DIU.
Extensive QC undertaken by DIU staff on individual datasets and data validation across multiple datasets held in the CCDR ensure that the quality of data provided to researchers is improved. Moreover, DIU staff dedicated to data integration provide faster content data delivery to researchers. Lastly, the CCDR reduces the number of custodians researchers need to liaise with for data provision.
Conclusion/ImplicationsOperational since February 2018, the DIU has delivered content data for several linkage projects, based on key datasets stored in the CCDR. The incorporation of additional datasets is currently negotiated.
Recognising recent developments in secure analytics infrastructure, the further evolution of the CCDR towards a cloud-based model is anticipated.
Automated Referral to Cardiac Rehabilitation following Coronary Artery Bypass Grafting is associated with limited improvements in program completion: a large cohort study
Authors: Liu Hongwei , Wilton Stephen , Southern Danielle , Knudtson Merril , Maitland Andrew , Hauer Trina , Arena Ross , Stone James , Aggarwal Sandeep , Martin Billie-Jean 
Published: September 2018

IntroductionCardiac Rehabilitation (CR) reduces residual cardiovascular risk among patients who have received coronary artery bypass grafting (CABG) surgery. However, many patients do not attend and some are never referred. It is unclear whether automated referral is associated with improved CR completion rates.
Objectives and ApproachGeographically inclusive databases were linked to assess the impact of automated referral on rates of referral to and completion of CR post-CABG. Automated referral to CR post-CABG was instituted in Calgary on July 1, 2007. All subjects receiving CABG in Calgary between January 1, 1996 and March 31, 2016 were enrolled in the study. The Alberta Provincial Project for Outcome Assessment in Coronary Heart disease (APPROACH) database, TotalCardiology-Rehabilitation (TC-R) database, and provincial vital statistics were linked using the unique Provincial Health Number available for each patient. The association between CR referral, completion, and survival was assessed using proportional hazard models.
ResultsThere were 28,100 patients referred to the CR program, of which 26,411 were linked to the APPROACH database for a 93.99\% linkage rate. After excluding patients who did not receive CABG, a total of 8,118 patients were identified as the study population [mean age 66.2 (SD 10.2) years, 18.9\% female] during the study period: 5,103 prior to implementation of automated referral, and 3,015 post-automation. Rates of referral increased from 39.5\% prior to automation to 75.0\% post-automation (p
Conclusion/ImplicationsAutomated referral to CR is associated with increased referral rates but less dramatic increases in CR completion rates post-CABG. Given the significant improvement in survival associated with CR completion, further work is needed to improve CR referral, and more importantly, CR completion rates.
Integrating Ontario Health and Social Services Data to for Research and Policy Development
Authors: Flora Mandeep , Ratnasingham Sujitha , Tefera Aki , Victor J. Charles , Schull Michael 
Published: September 2018

IntroductionIntegrating health and social services data is critical to understanding social determinants of health and responding to public expectations for evidence-based policies amidst changing demographics and fiscal constraint.
While academia has long understood the importance of social determinants of health, real and perceived obstacles have slowed their evaluation in Ontario.
Objectives and ApproachThis report describes how the Institute for Clinical Evaluative Sciences (ICES) and the Ministry and Community and Social Services (MCSS) have partnered to bring social services data and health data together to better understand the Ontario population and better support decision makers across various sectors.
We present how ICES and MCSS tackled barriers to data access and cultural challenges to data sharing in the Ontario context, provide an overview of their unique data and research partnership - including the new collaboration research and data access platforms created, highlight research findings to date, and identify key topics of interest moving forward.
ResultsOver the last decade, ICES and MCSS have led the way in Ontario linking health administrative and social services data. An initial single year linkage enabled the success of the Health Care Access Research and Developmental Disabilities project. This cross-sectoral initiative provided a clearer sense of how people with developmental disabilities experienced health care in Ontario.
Building on this work, ICES and MCSS recently expanded their partnership bringing together 15 years of social services and health data through a broader data sharing agreement. This agreement allows greater data access to researchers. In addition, ICES and MCSS have been successful in creating a new integrated research platform that will increase the depth and quality of health and social services research and policy evaluation in Ontario.
Conclusion/ImplicationsA broader collaborative research community will now be able to answer questions of interest, do self-directed integrated data analytics and leverage respective program data expertise to tackle joint research projects. Importantly, MCSS analytics teams will now also have access to linked data on this platform to conduct their own research.
Challenges of identifying children with Cystic Fibrosis to explore inequalities in social and health outcomes, using multiply linked data sources.
Authors: Griffiths Rowena , Akbari Ashley , Schlueter Daniela , Taylor-Robinson David , Tucker David 
Published: September 2018

IntroductionCystic fibrosis (CF) is the most common life-limiting inherited disease in white populations, with most patients dying prematurely from respiratory failure. As it is rare, it is important to reduce misclassification. We therefore aimed to assess how well CF children could be identified across routine data in Wales.
Objectives and ApproachData from the Secure Anonymised Information Linkage (SAIL) databank, identified children with CF from 1998 to 2016, within hospital, General Practice (GP), and the Welsh Congenital Abnormality Register (CARIS), which uses new born screening to identify congenital abnormalities, including CF. The International Classification of Diseases (ICD10) E84 was used to identify CF children in both hospital and CARIS data, with READ codes used in the GP data (approximately 80% coverage of Wales). The data was linked using anonymised linking fields and matching rates analysed, as unmatched records in linked data can reduce the utility of the data for epidemiological studies.
Results352 cases were identified in total, with 158 matched across all three datasets over an 18 year period (9-19 cases per year). The Welsh rate from the disease registry is 12–14. Since CF is a severely debilitating condition, a greater match was expected. This prompted further investigation of cases which appeared in only one dataset, as these seemed least likely to be true cases. In the ‘CARIS only’ data, 79% of the admissions, were found coded for respiratory, digestive and health complications not for an E84 CF condition. In the 43 cases in ‘GP only’ data, and the 19 in ‘hospital only’ data the events indicated the possible late presentation of CF by older children or children with very mild CF phenotypes.
Conclusion/ImplicationsCases of rare diseases like CF can be identified in routine data. Linking across multiple datasets, particularly with specialist datasets like CARIS, help identify potentially misclassified cases. This increases confidence in the data. Future work will include the CF registry, permitting checks against a gold standard data resource.
Dementias Platform UK (DPUK) Data Portal - World-leading infrastructure facilitating innovative multi-modal research
Authors: Orton Christopher , Gallacher John , Lyons Ronan , Ford David , Thompson Simon , Mackay Clare , Williams Julie , Bauermeister Sarah , Menzies Georgina , South Matthew , Biddle Justin , Bale Michael , North Laura 
Published: September 2018

IntroductionModern team science requires effective sharing of data and skills. The DPUK Data Portal is a collection of tools, datasets and networks that allows for epidemiologists and specialist researchers alike to access, analyse and investigate cohort and different modalities of routine data across UK and international sources.
Objectives and ApproachThe Portal is housed on an instance of UKSeRP (UK Secure eResearch Platform), that allows customisable infrastructure to be used for multi-modal research (thus far live in genetics, imaging and clinical data) for researchers across the world using remote access technology whilst allowing governance to remain with the data provider. A central team at Swansea University is responsible for data curation and processing, and runs an access procedure for researchers to apply to use data from multiple sources to be analysed in a central analysis environment. Other modalities are similarly hosted, with input from partner sites in Cardiff and Oxford.
ResultsDPUK facilitates data access and research on 49 cohorts, 40 UK-based and 9 international. The centralised repository model including remote access and ability to store and make available different modalities of data, from phenotypic data, to genetic and imaging data, has allowed DPUK to begin to support research of varying topics, from those studying cognitive decline and Dementia as a disease, to those maturing analytical models. By providing access to data platforms specialising in genetics, imaging and routine clinical data, as well as to specialists in disease and biology to aid with its understanding, DPUK has realised a large-scale research exercise combining major data modalities on a central platform, and allow access to such rich data across the world under an umbrella of robust governance.
Conclusion/ImplicationsGlobally, cohorts are pooling data, expertise and desire to enrich their own aims in partnership with a federated research community to enable in-depth scrutiny of the biological origins of dementia and the development and evaluation of novel approach to disease prevention and cure.
The Effect of Surgical Site Infection on Cost and Utilization Following Primary Knee Replacement in Nova Scotia 2005-2014
Authors: Lethbridge Lynn , Dunbar Michael 
Published: September 2018

IntroductionSurgical site infection (SSI) following joint replacement results in considerable disease burden. Costs include longer wait times for initial joint replacements which, in Nova Scotia (NS), are the longest in the country. Despite the widespread consequences, costs and utilization following knee replacement have not been comprehensively measured in Canada previously.
Objectives and ApproachThe objective was to measure costs and health care utilization of SSI following knee replacement through linked administrative data sources. The study cohort was constructed using procedure codes from hospital discharge data. Diagnostic variables were examined to determine the occurrence of infection within one year of discharge. A non-infected control group matched on age, sex and comorbidities was also selected. Costs and utilization from inpatient, day surgery, clinic and physician claims data were totaled over two years following discharge. Resource weights multiplied by standard cost was used to measure hospital costs while outpatient costs were government approved payments to physicians.
ResultsOver the 2005-2014 period, there were 204 infected cases for an overall 1-year rate of 1.8%. Non-infected controls visited a physician or were admitted to the hospital 21 times in the two year period following surgery compared to infected cases who averaged 40 (p-value
Conclusion/ImplicationsCosts attributable to infection following primary knee replacement are substantial in NS affecting both inpatient and outpatient services. With an increased focus on program evaluation by policy-makers, infection control administrators should include regular monitoring of the direct and indirect costs of SSI on a system-wide basis using linked administrative data.
Breast cancer care in Alberta: a Patients perspective
Authors: Crocker Alysha , Anderes Susan , Verbeek Linda , Chobanuk Janice , Olson David W , Kortbeek John , Elwi Adam , Dean Stafford , Estey Angela , Quan May Lynn 
Published: September 2018

IntroductionEach year in Alberta, over 2,300 women are affected by breast cancer. In Alberta, a multi-year Breast Health Initiative is underway to improve breast cancer care; reduce wait times, coordinate care, and enhance patient experience. Patient reported experience measurements are important to inform and advance patient and family-centred care.
Objectives and ApproachThe aim is to assess breast cancer patients’ experiences at two survey points; after surgeon consult and after breast surgery. Patients meeting inclusion criteria; highly suspicious of cancer on imaging result (i.e. BI-RADS 5), referral to Calgary or Edmonton breast program, English speaking, and having an email address are recruited by RN coordinators or nurse navigators. Automated survey invitations from REDCap are used. Seven days after the surgeon consult the first survey is sent and seven days after breast surgery the second survey is sent.
ResultsPatient recruitment began November 27, 2017 and January 2, 2018 for Edmonton and Calgary, respectively. As of February, 2018, 45 patients had been recruited. Of these, the first survey was sent to 34 (i.e. seven days post surgeon consult) and 19 (56%) had completed the survey. All those eligible (18) agreed to participate in the upcoming second survey. Of those, six had provided their surgery date and the second survey which both were completed. Recruitment is ongoing until the conference, at that time there will be sufficient numbers to report findings.
Conclusion/ImplicationsPatient and family-centred care is an element of high-quality healthcare which AHS has identified as a priority. These results will report on the breast cancer patients’ perspectives and generate important information for clinicians and administrators to use for decision making and quality improvement of health services.