bluuebunny/crossref_metadata_2025_split huggingface dataset:
To Err is Human, all hail your Robot Overseer: automated testing as part of a robust data delivery platform.
Authors: Avery Daniel 
Published: September 2018

IntroductionWe have a large cohort study of half a million people, which continually incorporates new data through health insurance, centre for disease control records, death certificates, resurveys, and ongoing quality assurance and participant information updates. To support our researchers we need data which is correct, up-to-date, and unchanging.
Objectives and ApproachWe must provide the new data, fixes and corrections to researchers, without missing anything or introducing issues. We make sequential iterations of our data available to researchers on a biannual basis; allowing a static version that can be referenced with regards to earlier work and providing the newest version of the data for new work. Due to the very large size of the data/code base and the small size of the team managing it, delivering this without error is a struggle. To mitigate this we developed testing scripts which catch issues and flag for resolution prior to release to researchers.
ResultsWe currently have 32 tests which catch all known issues which occur during a rebuild. On any occasion where a new type of issue is encountered, tests which would catch that issue and related issues are developed. As a result our last few releases have gone far more smoothly, with few if any issues reported after a release and certainly no previously encountered issues! Examples of current tests include: detection of a failed health insurance import; that we have the same number of participants; failure to increment version number between releases; checking that disease numbers have not changed dramatically over the shared timeframe.
Conclusion/ImplicationsProducing multiple static releases is a good way to balance the needs of a researcher for both static and current data, but it does introduce opportunities for both human and computer errors. Mitigating this risk with automated testing is convenient and effective.
Power of Linked Administrative Data
Authors: Izakian Hesam , Bhatt Hitesh , Jagodzinski Robert , Twilley Leslie , Cui Xinjie 
Published: September 2018

IntroductionLinking administrative data provides valuable information about individuals using government services and can be very useful for policy-makers in improving and developing services and policies. The Child and Youth Data Laboratory (CYDL) links and analyses administrative data from Alberta Government ministries to provide evidence for policy and program development.
Objectives and ApproachData from 20 programs of six Government of Alberta ministries (Advanced Education, Education, Health, Children’s Services, Community and Social Services, and Justice and Solicitor General) were linked anonymously. The data spans six years from 2005/06 to 2010/11 and consists of almost 50 million records corresponding to over 2 million unique Albertans aged 0 to 25 years. A data visualization tool called the Program Overlap Matrix summarises the overlap rates among the programs. It is comprised of a matrix of squares, where each cell represents the overlap between two programs.
ResultsThe Program Overlap Matrix is publically available at https://visualization.policywise.com/P2matrix/. It consists of overlap rates between programs in any study year (2005/06 to 2010/11), individual years, the first year vs. future years, and the last year vs. previous years which can be used to answer many policy-related questions such as: other service use (e.g., what other services do ESL students use?), over-represented programs (e.g., in what programs are Child Care Subsidy clients over-represented?), resilience (e.g., what is the proportion of Child Intervention clients in post-secondary institutions?), transitions (e.g., what types of services do students with special needs receive as they transition to adulthood?), and time trend (e.g., what types of services did Income Support clients receive in the past?)
Conclusion/ImplicationsThe program overlap matrix is a powerful tool to discover relationships between programs. It is a useful instrument to inform public and policy-makers about the overlap rates between government programs. It can be used to answer a variety of policy-related questions.
Identifying vulnerable population groups: On-time infant vaccination coverage in Australia
Authors: Moore Hannah , Fathima Parveen , Gidding Heather , De Klerk Nicholas , Liu Bette , Sheppeard Vicky 
Published: September 2018

IntroductionImmunisation coverage is a good measure of immunisation program effectiveness. Coverage of the 3-dose infant schedule in Australia assessed at age 12 months is >90%. Timeliness is an important goal for population immunity, but on-time coverage of the 2-4-6 month schedule and coverage in specific populations is rarely reported.
Objectives and ApproachWe conducted a retrospective population-based cohort study of 1.9 million Australian births, 1996-2012 (approximately 42% of Australia’s population). Individual data from state-held birth and perinatal records were combined with Commonwealth-held immunisation and death records, through probabilistic linkage. We assessed on-time coverage across 13 demographic and perinatal characteristics of diphtheria-tetanus-pertussis vaccines (DTP) defined as vaccination 14 days prior to the scheduled due date, to 30 days afterwards.
ResultsOn-time DTP vaccination coverage in non-Aboriginal infants was 88.1% for the 2-month dose, 82.0% for 4-month dose, and 76.7% for 6-month dose; 3-dose coverage was 91.3% when assessed at 12 months. On-time DTP coverage for Aboriginal infants was 77.0%, 66.5%, and 61.0%; 3-dose coverage at 12 months was 79.3%. Appreciable differences in on-time coverage were observed across population subgroups. On-time coverage in non-Aboriginal infants born to mothers with ≥3 previous pregnancies was 62.5% for the 6-month dose (47.9% for Aboriginal infants); up to 23.5% lower than for first-borns. Infants born to mothers who smoked during pregnancy had coverage 8.7-10.3% lower than infants born to non-smoking mothers for the 4- and 6-month dose. A linear relationship was apparent with increasing socio-economic disadvantage and decreasing on-time coverage.
Conclusion/ImplicationsOn-time vaccination coverage of the 2-4-6 month schedule is only 50-60% across specific population subgroups representing a significant avoidable public health risk. Australian Aboriginal infants, multiparous mothers, and those who are socio-economically disadvantaged are key groups most likely to benefit from targeted programs addressing vaccine timeliness.
Screening Women in Glasgow: Comparing uptake across cancer screening programmes at an individual patient level
Authors: Papworth Richard , McCowan Colin , McSkimming Paula , Kotzur Marie , McConnachie Alex , MacDonald Sara , Wyke Sally , Crighton Emilia , Weller David , Campbell Christine , Steele Robert JC , Robb Katie 
Published: September 2018

IntroductionPopulation-based screening has been shown to reduce cancer specific mortality. Within Scotland, three national screening programmes exist: breast, cervical and bowel. Despite being a common and preventable form of cancer, the uptake for bowel cancer screening among women lags behind that for breast and cervical cancer.
Objectives and ApproachSince the benefits of screening accrue with participation, it is important to understand why differences in screening uptake exist. In this study, data on women aged 24-74 in the Greater Glasgow and Clyde Health Board, invited to take part in one or more screening programme during the period 2009-2013, were linked to demographic and medical data. Uptake was determined based on the presence of a screening attendance or result; the impact of age, deprivation and co-morbidity on uptake was determined using logistic regression for each individual programme, and for the cohort of women invited to participate in all three programmes.
ResultsOverall, 430,591 women were invited to take part in one or more screening programme during the study period. The uptake for bowel screening was, at 61.7%, lower than that seen in either the breast (72.6%) or cervical (80.7%) programme. Despite these differences, the same demographic factors were associated with uptake of each individual screening programme: older women and those living in affluent areas were most likely to attend. Medical factors did differentially influence uptake, those with multi-morbid illness being less likely to participate in breast and bowel, but not the cervical programme. For the 68,324 women invited to participate in all programmes, 52.1% took part in all three while 7.2% participated in none.
Conclusion/ImplicationsUptake of bowel screening was confirmed as lower than uptake of other programmes, although all were similarly impacted by demographic, clinical and socioeconomic factors. Individuals were more likely to complete bowel screening if they participate in another programme, suggesting these may serve as a vehicle for improving bowel screening uptake.
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.