bluuebunny/crossref_metadata_2025_split huggingface dataset:
International meta-analysis of 684,660 men with vasectomies: a study utilising the International Population Data Linkage Network
Authors: Randall Sean , Boyd James , Fuller Emma , Brooks Caroline , Morris Carole , Earle Craig , Ferrante Anna , Moorin Rachael , Semmens James , Holman D'Arcy 
Published: September 2018

IntroductionEvidence on the effect of vasectomy and vasectomy reversal on risk of prostate cancer is conflicting, with the issue of detection bias a key criticism. In this study we examined the effect of vasectomy reversal on prostate cancer risk in a cohort of vasectomised men.
Objectives and ApproachA proof of concept study involving the International Population Data Linkage Network which pooled aggregated result data from participating centres in Australia, Canada and the United Kingdom. De-identified linked data extractions took place at each centre. Each participating centre locally conducted Cox proportional hazards regression analysis compared the risk of prostate cancer in those with/without vasectomy reversal in a cohort of vasectomised men. These results were then combined in a meta-analysis. Evidence of a protective effect of vasectomy reversal would suggest the harmful effect of vasectomy on prostate cancer risk, while nullifying detection bias.
ResultsData were received from Australia (the states of Western Australia and New South Wales), Canada (the province of Ontario), Wales and Scotland. In total, there were 9,754 men with vasectomy reversals, and 684,660 men with a vasectomy.
The combined analysis showed no protective effect of vasectomy reversal on incidence of prostate cancer when compared to those who had vasectomy alone (HR, 95%CI: 0.92, 0.70-1.21). As such, the results align with previous studies which found little or no evidence of a link between vasectomy and prostate cancer.
Conclusion/ImplicationsThe study, originally conceived at the first IPDLN meeting in London, found no obvious protective effect of vasectomy reversal on prostate cancer in vasectomised men. The project demonstrated the utility and feasibility of collaborative studies fostered through the IPDLN, despite methodological challenges faced when aggregating international data.
Making the link: using long-term cancer survival measures linked with acute care data to plan health services.
Authors: Wright Cameron , Moorin Rachael 
Published: September 2018

IntroductionLong-term cancer survival measures have become more important as management has improved outcomes. However, we know some cancer-related acute care use persists into the long-term. This project sought to integrate cancer survival analysis and health services research, validating our modelling retrospectively, for prospective application for health service planning.
Objectives and ApproachWe used linked Western Australian cancer registry, mortality and hospitalisation data. Flexible parametric models for first-time invasive cancer diagnoses between 1/1/1997 and 31/12/2006 were used to extract marginal estimates of the cure proportion –that expected not to experience excess mortality from cancer - for those diagnosed in 1999. Fine and Gray competing risks regression was used to estimate the proportion who had died of non-cancer causes. The expected number of individuals diagnosed in 1999 still alive in 2011 was multiplied by the mean expected rate of cancer-related hospitalisations 12 years post-diagnosis (modelled for individuals diagnosed between 1/1/1997 and 31/12/2011).
ResultsCure modelling was appropriate for colorectal cancer (CRC) and melanoma. CRC cure proportions were 0.58 for ≤ 50 years at diagnosis, 0.61 for 51 – 70 years, and 0.49 for ≥71 years. For melanoma, corresponding proportions were 0.94, 0.91 and 0.83. The expected number still alive in 2011 was similar to the actual observed in the linked data for the youngest age group, with an over-estimate for older groups. The actual age-standardised, cancer-related hospitalisations in 2011 for those diagnosed with CRC or melanoma in 1999, was within the lower and upper limits of the expected number for all except melanoma diagnosed between 51 and 70 years of age. For this group, observed cancer-related hospitalisations were higher than the expected (355 versus 271 (203 – 341)).
Conclusion/ImplicationsCancer registry linked with health service use data can provide useful insights for health service planners. While a decline in cancer-related hospitalisations from diagnosis is expected, this study shows that some demand remains 12 years post-diagnosis. Further refinement of our approach will facilitate its utility in planning cancer-related acute care.
US Data Access and the Commission for Evidence-based Policymaking
Authors: O'Hara Amy 
Published: September 2018

IntroductionIn September 2017, the bipartisan Commission for Evidence-based Policymaking released twenty-two recommendations to improve secure data access for evidence building activities involving population-level government files. Many of the files are siloed in government agencies. The commission deliberated over eighteen months to understand the risks and barriers to broader data use.
Objectives and ApproachI will describe the Commission’s charge and review its recommendations, in context of US laws and privacy debates. I will compare the report’s recommendations and implications to laws and initiatives in other countries. The report calls for the establishment of a National Secure Data Service (NSDS), which has the potential to transform the data sharing environment for federal agencies, policy makers, and researchers. The report suggests more extensive use of differential privacy and secure multiparty computation to protect privacy. I will describe how the current environment could change depending on how the recommendations are implemented.
ResultsThe Commission was established under one administration, but the recommendations were released under another. Despite the political and budget uncertainty in Washington, a bill was introduced and passed in the House in November 2017 to implement some recommendations. I will summarize the actions to be taken if the bill becomes law, including directives on learning agendas to prioritize and coordinate evidence-building activities across government, the roles of chief evaluation and chief data officers, and formation of an advisory committee to plan a NSDS. I will describe benefits that could follow from directives in the bill, including transparency about uses of administrative data, development of guidance to assess the risk when combining data sources, and minimization of the risk of publicly releasing de-identified data.
Conclusion/ImplicationsThe US may develop a national secure data service to support evaluations and policymaking. The recommendations are akin to the UK Data Service. Some recommendations are straightforward, others need years of planning and technical breakthroughs, and all require political buy-in and funding.
People with mild cognitive impairment are at increased risk of serious injury
Authors: Harvey Lara , Toson Barbara , Brodaty Henry , Draper Brian , Kochan Nicole , Sachdev Perminder , Mitchell Rebecca , Close Jacqueline 
Published: September 2018

IntroductionData-linkage studies using administrative hospital data have shown that people with dementia have double the rate of injury-related hospitalisations and poorer health outcomes than those without. No previous research has explored whether people with mild cognitive impairment are also at increased risk of serious injury requiring hospitalisation.
Objectives and ApproachA major barrier to the use of administrative hospital data for undertaking research focusing on people with MCI is that MCI cannot be reliably identified from ICD-10 coded administrative data. To overcome this limitation, hospitalisation and death data was linked to data from participants (community-dwelling 70-90 year olds) enrolled in the population-based longitudinal Sydney Memory and Ageing Study (MAS). MAS participants underwent comprehensive neuropsychological assessments at baseline, then 2, 4 and 6 years’ follow-up to accurately determine cognitive status at each time-period. Linkage to hospital records allowed identification of injury-related hospitalisations and outcomes for the 2-year period following each assessment.
ResultsThere were 335 injury-related hospitalisations for the 867 participants; 222 (25.6%) participants had at least one injury-related hospitalisation. After adjusting for age-and-sex, participants in a state of MCI had 1.7 (95%CI 1.2-2.4) times higher odds of an injury-related hospitalisation than participants in a state of normal cognition, whilst participants with dementia had 2.3 (95%CI 1.2-4.4) times higher odds. There was no difference in odds between participants with MCI and dementia.
Of the 116 hospitalisations for people with MCI, the majority (79.3%) were due to falls. Non-fracture head injuries (25.9%), upper limb and trunk fractures (13.8% respectively) were the most common injury type. There were no differences in injury type, mean length of stay, or 30-day mortality between people with normal cognition, MCI and dementia.
Conclusion/ImplicationsOlder people with objectively defined MCI are at higher risk of injury, predominantly as a result of falls, than their cognitively intact peers. Falls-risk screening and fall prevention initiatives may be indicated for people with MCI. Further research is required to determine which cognitive domains contribute to this increased risk.
Evaluation of the Western Australian population based data linkage Intellectual Disability Exploring Answers (IDEA) surveillance system
Authors: Strobel Natalie , Bourke Jenny , Leonard Helen , Richardson Alice , Edmond Karen , McAullay Dan 
Published: September 2018

IntroductionThe IDEA system is a population-based data linkage system for intellectual disability (ID), which combines data from two government departments. Due to recent policy changes the future of the IDEA system is unknown. Understanding the IDEA system's strengths and limitations will provide data custodians with the opportunity to re-design the system.
Objectives and ApproachAn evaluation of the IDEA surveillance system was undertaken to assess the quality, efficiency and usefulness of the system. The primary objectives were to evaluate systematically and objectively the attributes of the system and provide recommendations to data custodians and stakeholders to strengthen the surveillance system.
The evaluation was based on the methods from the 2001 U.S. Centers for Disease Control and Prevention guidelines on evaluation of public health surveillance systems. We assessed the following system attributes: usefulness, simplicity, flexibility, data quality, acceptability, representativeness, timeliness, and stability. This was completed by process observation, semi-structured interviews and data analysis.
ResultsOur results found the IDEA system was flexible, acceptable, representative, timely and stable. Given data linkage process and maintaining confidentiality the data linkage process was considered relatively simple. We compared individuals in the IDEA surveillance system to a sub-group of individuals, cerebral palsy with ID, to the mandatory reporting surveillance system WARDA-CP. There were 582 individuals identified in the WARDA-CP surveillance system as having cerebral palsy and ID. Of those identified 501 (86.1%) were also in the IDEA database and 81 (13.9%) were not. There were little differences in WARDA-CP cases that were not identified in the IDEA system between Indigenous status, sex and place of residence.
Conclusion/ImplicationsThe IDEA system has successfully been used to understand prevalence rates and inform resource allocation. Advocacy organisations could play an important role in the sustainability of the system. Additional variables or enhanced surveillance for functional capacity could strengthen the system and provide important information to inform policy and practice.
Leveraging best practices in data governance: An organization-wide data inventory and mapping project to support a five year data strategy
Authors: Travers Joseph , Campitelli Crystal , Light Richard , De Sa Eric , Stabile Julie , Iron Karey 
Published: September 2018

IntroductionThe professional regulation sector is moving toward risk-informed approaches that require high quality data. A key component of a corporate 2017 Data Strategy is the implementation of a data inventory and mapping project to catalogue, centralize, document and govern data assets that support regulatory decisions, programs and operations.
Objectives and ApproachIn a data rich organization, the goals of the data inventory are to: enhance authoritative data that support programs; identify data duplications/gaps; identify data sources, owners and users; and, apply consistent data management and standards organizationally. Routinely used data assets outside the large enterprise workflow system (excel/word files; databases; paper collections) were catalogued. Using data governance principles and a facilitated questionnaire, departmental data stewards were interviewed about their generated data. Questions included data purpose/sources/types/formats/owners, retention rates, analytical products, gaps and visions for a desired data state. A data mapping methodology highlighted data set and variable connections within and across departments.
ResultsTo date, over 40 staff members in 10 departments were identified as data content experts. In addition to data in the corporate enterprise system, over 80 unique datasets were identified. In 1 large department, over 2,000 data elements across 26 datasets were inventoried. Data mapping analysis revealed thematic data domains, including member demographics, outcomes, certifications, tracking and financial data, collected and held in multiple formats ((Microsoft Access, Excel, Word), SPSS, PDF, e-mails and paper documents). While 72% of the data elements were formatted numerically, approximately 8% were free text. Significant data redundancies across staff members and departments were revealed, as well as unstandardized variable naming conventions. Gaps analysis highlighted need for standardized, electronic data, where not available and data management training.
Conclusion/ImplicationsCustomized data mapping reports to data users will facilitate the development of local, standardized departmental data hubs that will centrally link to a centralized data repository to facilitate seamless organization-wide analytics, improvements in current data management practices and greater data collaboration with the ultimate goal of supporting risk-informed approaches.
Improving the Measurement of Health System Performance across the Rural-Urban Continuum
Authors: Degani Naushaba , Gushue Sharon , Yurkiewich Alex , Buajitti Emmalin , Kumar Matthew , Campitelli Michael , Rosella Laura 
Published: September 2018

IntroductionWe report on key performance indicators to highlight quality and variation in health care. Given Ontario’s diverse geography, we have prioritized improving measurement across the rural-urban continuum. This will improve our ability to discern the impact of geography on health care and health status to inform planning and decision making.
Objectives and ApproachBuilding on previous work to advance measurement of equity in health care, we struck a technical working group of experts to review methods for stratifying health system performance data by geographic location in the Ontario context. These methods were applied to a set of key performance indicators. The working group’s review of the results of this analysis will lead to recommendations for the best method to refine and standardize how geographic location is measured and stratified. This will improve our ability to discern the impact of geography on health system performance and health status for our suite of public-reporting products.
ResultsThe technical working group identified three methodologies for consideration that used linked postal code data: Population Centre (POPCTR), Statistical Area Classification (SAC) and a hybrid POPCTR/SAC methodology. These methods were tested against a set of key performance indicators across dimensions of quality including timeliness, effectiveness, population health and health outcomes. The results show that, in the health system performance dimensions of effectiveness and timeliness, as well as for a subset of health outcomes, there is variation in performance across the urban-rural continuum, though not always in a linear way. This may reflect differences in health care access, health risk factors, sociodemographic or socioeconomic characteristics across the urban-rural continuum. More definitive conclusions and recommendations will be available when the working group meets to review the results.
Conclusion/ImplicationsIdentifying a robust methodology for measuring performance across geographic locations will improve our ability to discern the impact of geography on health care including where geography may impact access and effectiveness of services as well as health outcomes. This information will enable better health system planning and decision-making.
Ensemble-based Classification Models for Predicting Post-Operative Mortality Risk in Coronary Artery Disease
Authors: Brobbey Anita , Faris Peter , Nettel-Aguirre Alberto , Williamson Tyler , Wiebe Samuel , Peng Mingkai , Quan Hude , Sajobi Tolulope T 
Published: September 2018

IntroductionThere has been an increased demand for more accurate prediction tools to aid clinical decision-making regarding disease diagnosis prognosis for coronary artery disease(CAD) patients. Patients undergoing CABG surgery are older and a larger number have had previous heart surgery. Consequently, mortality after CABG is expected to increase despite procedural advances.
Objectives and ApproachThis study aims to compare the predictive performance of random forest(RF) and logistic regression(LR) classifiers for predicting 30-day and 1-year post-operative mortality risk in CAD patients who underwent CABG. Data was obtained by linking the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease(APPROACH) registry, a prospective longitudinal data of patients undergoing cardiac catheterization in Alberta, Canada, to vital statistics database. All patients who underwent first-time isolated CABG between January 1, 2007 and December 31, 2012 were included in the analysis. Area under the receiver operating curve(AUC) was used to compare the predictive performance of LR and RF regression.
ResultsOf the 4,908 eligible subjects who underwent isolated CABG during the study period, mortality estimates of 30-day and 1-year post CABG surgery were 1.59% and 3.85%, respectively. Descriptive analysis revealed that age, sex, hypertension, dialysis, cerebrovascular disease, chronic obstructive pulmonary disease, and chronic heart failure were associated with 30-day and 1-year mortality. The accuracy of the LR and RF regression classifiers in predicting 30-day mortality were 74.1, and 99.7%, respectively. While the accuracy of the former and latter classifiers in predicting 1-year post CABG mortality were 74% and 97.4%, respectively.
Conclusion/ImplicationsThis study shows that RF classifier results in better predictive accuracy than LR in predicting post-operating mortality risk in CAD patients. Machine learning models are potentially usefully for developing clinical prediction models that can be used to aid the monitoring of post-discharge outcomes in the management of cardiovascular diseases.
Can mental health related hospital visits be relied upon for suicide prevention?
Authors: Boctor Kerstina , Harder Douglas , Letwiniuk Liz , Marcoux Gene , Langhorst Kristi , Inch Roxanne , Lapointe Candace , Balbuena Lloyd 
Published: September 2018

IntroductionEven among people with mental disorders, relatively few die of suicide. However, a large proportion of people dying from suicide have seen a physician in the year before death. This raises the question whether focusing on hospital visits for suicide-related outcomes is a viable suicide prevention strategy.
Objectives and ApproachOur objective was to examine whether a hospital visit for a mental disorder or prior suicide attempt preceded suicide death. We requested Saskatchewan’s provincial coroner for records of people dying of suicide in the Saskatoon Health Region catchment area for the years 2012 to 2016. The coroner’s list was linked with hospital and community mental health databases. Patient charts and medical abstracts in both settings were reviewed for risk factors.
ResultsThere were 143 suicide deaths in the time period and the yearly incidence was higher in Saskatoon as compared with the national average. Only 38 percent were seen previously in any Saskatoon hospital for a mental disorder (11 percent for a self-harm diagnosis). The chart review confirmed several known psychological and social risk factors. Having a history of depression or psychosis and alcohol and/or drug use were common. Many decedents also had disadvantaged socio-economic backgrounds characterized by vulnerable housing and being on social assistance.
Conclusion/ImplicationsWith only 38 percent of decedents being seen in hospital, community-based mental health care and data are important for suicide prevention. Suicide prevention efforts can be aided by facilitating the linkage of community and medical records to better track patients as they move between care settings.
Code List Library: A Solution to Improve Research Repeatability, Transparency, and Efficiency by Curating Lists of Clinical Codes
Authors: Thayer Daniel , Bown David , Leake Thomas , Jones Jonathan-Lee , Noyce Richard , Brooks Caroline , Ford David 
Published: September 2018

IntroductionSets of clinical codes that define conditions and events of interest are a key knowledge product in health data research. Documenting such lists is essential for transparency and repeatability, and there is great potential benefit in their sharing and reuse. We designed and implemented software to address these goals.
Objectives and ApproachOur goals were threefold:

Provide a graphical user interface (GUI) to allow easier creation of code lists, for less technical users.
Allow clear documentation of code lists, preserving the history of their creation and capturing metadata about their meaning, provenance, and use.
Facilitate programmatic access, so that the software is not just documentation but can be integrated into data preparation and analysis.

To these ends, we developed a web application using Python and PostgreSQL that allows creating, editing, and accessing via a GUI, as well as a REST API for integration into SQL, R, and other environments.
ResultsThe software allows users to view and create lists through a familiar web paradigm. Lists can be built by identifying codes in a variety of ways, including keyword searches, regular expressions, and more complex rules. A change history is stored.
Information such as a description, whether there was clinical reviewed, and relevant publications is captured.
The REST API allows access and use in a variety of settings. We have implemented a DB2 SQL interface to enable code lists to be used within database queries, and other interfaces such as an R package are planned for the future.
It will be used within the SAIL Databank initially, with a public version for sharing across institutions planned. The code will be open source to enable further development.
Conclusion/ImplicationsWe expect this tool to facilitate faster, higher-quality, more reproducible research in Wales and beyond. Hopefully it will be not just a standalone effort, but one small piece in a set of better tools and methods that will enable our field to truly realized the benefit of large linked datasets.