bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Canadian Urban Environmental Health Research Consortium (CANUE): a national data linkage initiative
Authors: Doiron Dany , Setton Eleanor , Seed Evan , Shooshtari Mahdi , Brook Jeffrey 
Published: September 2018

IntroductionHealth and environmental exposure databases are generally siloed in different research institutions across Canada and integrating them for environmental health research is a considerable challenge. Facilitating the linkage of these databases is essential to provide new analytical opportunities and help create efficiencies for research on environmental determinants of health.
Objectives and ApproachCANUE is a Canadian Institutes of Health Research-funded platform for supporting environmental health research. CANUE collates and generates standardized environmental data on air and noise pollution, land use, green/natural spaces, climate change/extreme weather, and socioeconomic conditions for every postal code in Canada and makes them freely available to researchers. Systems and procedures are being developed by CANUE to facilitate the sharing and integration of these extensive geospatial exposures with existing observational cohorts and administrative health databases across Canada. This linkage will enable investigators to test hypotheses on the interdependent associations of environmental features with health impacts or benefits.
ResultsCANUE now hosts a dozen national exposure databases and related metadata files, and actively adds new regional and national datasets. Streamlined processes for data sharing have been developed to facilitate easy merging with health data. Substantial consultation has also taken place with a wide range of health data holders to establish appropriate processes for receiving and managing environmental data, with particular focus on addressing challenges presented by differing ethics, consent and confidentiality requirements. These processes help accelerate the research process by making analysis-ready data available to investigators, create opportunities to study how multiple environmental factors are linked to a wide range of health outcomes, and generally increase the use of health and population databases for environmental health research.
Conclusion/ImplicationsThe CANUE collaborative model illustrates how the production of policy-relevant evidence can be advanced through better coordination among environmental health researchers and linkage with health databases. CANUE is improving the scientific potential and cost-effectiveness of research in environmental epidemiology through streamlining linkage and access to standardized exposure datasets.
A comparison of methodologies: sibling identification using a relational versus a graph-based approach
Authors: Farrow James , Adams Suzi 
Published: September 2018

IntroductionThe detection of siblings is an important pre-requisite for many research problems, yet is traditionally difficult or time-consuming owing to the way linked data is conventionally stored. We compare the methodology and results for an identification of siblings by SANT DataLink using a legacy relational approach and a graph-based approach.
Objectives and ApproachAn existing project involving the identification of sibling clusters using relational techniques was replicated using the same core data in SANT DataLink’s Next Generation Linkage Managment System (NGLMS) which is graph-based. Data is stored in the NGLMS using richer relationships than just 'is W% similar to' or 'is part of group N'. Birth data was separated into children and parents and explicit child/parent relationships recorded. When coupled with electoral roll data using probabilistic and deterministic linkage, sibling structure can be identified by performing network traversal via parents, e.g.
crecord—[MOTHER]⟶mrecord—[IS_SIMILAR_TO]⟶mrecord*⟵[MOTHER]—crecord*
i.e. find the mother, find that mother’s cluster, find all children related to that cluster. The resulting records are siblings.
ResultsA graph-based approach enabled the methology of 'finding siblings' to be more clearly described and communicated by mirroring genealogical structures natively within in the data. Comparable results were achieved in a shorter time with less manual effort using the same underlying data. Generating sibling clusters from the graph-based data required less manual intervention and review as explicit PARENT/CHILD relationships were stored in the data and able to be quickly traversed to assemble familial units and thus siblings. A focus on automated linkage quality rather than manual review was facilitated by the approach. Anomalous structures requiring detailed review, such as multiple fathers and mothers of a single child, were trivially identifiable and so manual effort was focussed on actions where a higher return in terms of end-product quality could be achieved.
Conclusion/ImplicationsStoring data in a representation which more closely resembles the the underlying real-world situation allows greater fidelity with respect to data modeling. This in turn, enables the asking of richer questions and makes the answering of such questions much easier.
Evaluating hardening techniques against cryptanalysis attacks on Bloom filter encodings for record linkage
Authors: Ranbaduge Thilina , Vidanage Anushka , Vaiwsri Sirintra , Schnell Rainer , Christen Peter , Christen Peter 
Published: September 2018

IntroductionDue to privacy concerns personal identifiers used for linking data often have to be encoded (masked) before being linked across organisations. Bloom filter (BF) encoding is a popular privacy technique that is now employed in real-world linkage applications. Recent research has however shown that BFs are vulnerable to cryptanalysis attacks.
Objectives and ApproachAttacks on BFs either exploit that encoding frequent plain-text values (such as common names) results in corresponding frequent BFs, or they apply pattern mining to identify co-occurring BF bit positions that correspond to frequent encoded q-grams (sub-strings). In this study we empirically evaluated the privacy of individuals encoded in BFs against two recent cryptanalysis attack methods by Christen et al. (2017/2018). We used two snapshots of the North Carolina Voter Registration database for our evaluation, where pairs of records corresponding to the same voter (with name or address variations) resulted in files with 222,251 BFs and 224,061 plain-text records, respectively.
ResultsWe encoded between two and four of the fields first and last name, street, and city into one BF per record. For combinations of three and four fields all plain-text values and BFs were unique, challenging any frequency-based attack. For hardening BFs, different suggested methods (balancing, random hashing, XOR, BLIP, and salting) were applied.
Without any hardening applied up to 20.7% and 5% of plain-text values were correctly re-identified as 1-to-1 matches by both the pattern-mining and frequency-based attack methods, respectively. No more than 5\% correct 1-to-1 re-identification matches were achieved with the frequency-based attack on BFs encoding two fields when either balancing, random hashing, or XOR folding was applied; while the pattern-mining based attack was not successful in any correct re-identifications for any hardening technique.
Conclusion/ImplicationsGiven that BF encoding is now being employed in real-world linkage applications, it is important to study the limits of this privacy technique. Our experimental evaluation shows that although basic BFs without hardening technique are susceptible to cryptanalysis attacks, some hardening techniques are able to protect BFs against these attacks.
Proof of Concept for a Privacy Preserving National Mortality Register
Authors: Schnell Rainer , Borgs Christian 
Published: September 2018

IntroductionNational mortality registers are essential for medical research. Therefore, most nations operate such registers. Due to the administrative structure and data protection legislation, there is no such registry in Germany. We demonstrate that a national mortality registry is technically feasible under the given constraints with privacy preserving record linkage (PPRL).
Objectives and ApproachGetting the legal permission to operate a national mortality registry for research will be easier if the linkage can be done without revealing personal identifiers by using PPRL. To estimate precision and recall of different encodings, we used two settings: (1) matching a local mortality registry (n = 14,003) with mortality data of a university hospital (n = 2,466); (2) matching 1 million simulated records from a national database of names with a corrupted subset. This corresponds to a match of all deceased persons with the deceased persons in the largest federal state (n = 205,000).
ResultsLinkage results for clear-text identifiers show very high recall and precision. Bloom-Filter based encryptions yield comparable results. Neither precision nor recall declines more than 2%. Phonetic codes yield high precision but low recall. Some variants of Bloom Filter-based encodings yield better results than probabilistic linkage on clear-text identifiers. This is mainly due to the rarely mentioned detail of using different passwords for different identifiers in the same Bloom Filter. Therefore, implementation details of Bloom Filters are more important than commonly thought. Overall, we recommend the use of salted Bloom Filter-based methods with different passwords for different identifiers to increase security and to prevent all known attacks on identifier encryptions.
Conclusion/ImplicationsAlthough most PPRL techniques would yield acceptable results in the given setting of a national register, salted Bloom filter encodings are more secure against attacks while still showing high precision and recall. Therefore, we consider a national mortality register using only encrypted identifiers of deceased persons as feasible.
Creating a Community of Practice to Support Data Linkage Across Government Agencies
Authors: Nelson Amy Hawn 
Published: September 2018

IntroductionSince 2008, our team has studied sites with strong track records of integrating cross-sector data to address complex social problems. We have identified best practices and are supporting 16 sites with individualized technical assistance and participation in a learning community to facilitate data sharing that leads to actionable intelligence.
Objectives and ApproachThis presentation will provide an overview of our findings in studying established integrated data systems from across the United States, and a summary of our efforts in supporting the development of new integrated data systems (IDS). Specifically, we will answer:

What are the core features of integrated data systems (IDS) needed to support data linkage across government agencies?
How can sites develop these core features to facilitate data sharing, and ultimately, actionable intelligence?
What are the common roadblocks to successfully sharing data across agency siloes?
How can these roadblocks be addressed to create a sustainable data sharing ecosystem?

ResultsAgencies collect vast amounts of data, yet struggle to assess program impacts due to data siloes. The ability to link data across agencies to develop potential policy and service improvements is difficult, and at times, impossible. This technical assistance supports a different approach.
Our Integrated Data System (IDS) Learning Community initiative is an 18-month engagement for sites selected through a competitive process. As of September 2018, sites will be 11 months into the IDS development process. This presentation will discuss site-based approaches to facilitate data sharing, with an emphasis on governance, foundational agreements, data management and security, and stakeholder driven processes that ensure ethical use of data. This discussion will include progress to date, common challenges and solutions to developing an IDS.
Conclusion/ImplicationsWhile there is broad agreement in the value of integrating data across domains, developing the capacity and skills necessary to link administrative data for policy evaluation and research remains an elusive goal. Initial results indicate that an individualized yet collaborative technical assistance approach is successful in developing data integration capacity.
Utilization of Radiotherapy for Bladder Cancer: Evolving referral and practice patterns in the general population
Authors: Wei Shelly , Booth Christopher , Siemens Robert 
Published: September 2018

IntroductionDefinitive treatment for muscle invasive bladder cancer (MIBC) includes either cystectomy or radical radiotherapy (RT). Despite the growing evidence suggesting that cystectomy and RT may offer comparable survival benefit, utilization of RT and referral rate to radiation oncology (RO) have historically been low in routine practice.
Objectives and ApproachThe aims were to describe the use of RT and RO referral patterns in the contemporary era. A retrospective cohort study was conducted by linking administrative treatment records with the Ontario Cancer Registry to identify all patients who received treatment with curative intent for bladder cancer in Ontario from 1994-2013. Physician billing records were linked to identify RO consultation before radical treatment. Practice patterns in the contemporary era (2009-2013) were compared with data from 1994 to 2008. Multilevel (patient-, surgeon- and hospital-level) logistic regression models were used to examine sociodemographic and organizational variation in referral to RO.
ResultsIn total, 7461 patients underwent cystectomy or RT for bladder cancer in Ontario from 1994-2013; 5574 (75%) had primary cystectomy and 1887 (25%) primary had RT. Use of RT decreased from 43% in 1994 to 23% in 2008 and remained stable during 2009-2013 (23%). RO referral rate among all cases decreased from 46% in 1994 to 30% in 2008; however, the rates began to rise in the contemporary era from 31% in 2009 to 37% in 2013. A similar trend was seen in preoperative referral rate among patients treated with cystectomy (11% in 1994-1998, 9% in 1999-2008, and 14% in 2009-2013). Patient, surgeon, and hospital-level factors associated with preoperative referral to RO include older age, year of cystectomy, higher surgeon case volume, and teaching hospital.
Conclusion/ImplicationsA minority of patients underwent curative intent therapy for bladder cancer received RT. Recent data suggest that referral rates to RO are increasing; future data will identify the extent to which this has altered practice. Collaborative efforts promoting multidisciplinary care and RO consultation at the urologist and hospital-level are warranted.
Linkage of whole genome sequencing with administrative health, and electronic medical record data for the study of autism spectrum disorder: Feasibility, Opportunities and Challenges
Authors: Brooks Jennifer , Anagnostou Evdokia , Rahman Farah , Tu Karen , Uruthiramoorthy Lavnaya , Nylen Kirk , McLaughlin John , Schull Michael , Bronskill Susan 
Published: September 2018

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) that presents with a high degree of heterogeneity (e.g., co-occurrence of other NDDs and other co-morbid conditions), contributing to differential health system needs. Genetics are known to play an important role in ASD and may be associated with different disease trajectories.
Objectives and ApproachIn this proof of principle project, our objective is to link >2,200 children with a confirmed diagnosis of a NDD from the Province of Ontario Neurodevelopmental (POND) Study to administrative health data and electronic medical record (EMR) data in order to identify subgroups of ASD with unique health system trajectories. POND includes detailed phenotype and whole genome sequencing (WGS) data. Identified subgroups will be characterized based on clinical phenotype and genetics. To meet this goal, consideration of WGS-specific privacy and data issues is needed to implement processes which are above and beyond traditional requirements for analyzing individual-level administrative health data.
ResultsLinkage of WGS data with administrative health data is an emerging area of research. As such it has presented a number of initial challenges for our study of ASD. Privacy concerns surrounding the use of WGS data and rare-variant analysis are of particular importance. Practical issues required the need for analysts with expertise in administrative data, EMR data and genetic analyses, and specialized software and sufficient processing power to analyze WGS data. Transdisciplinary discussions of the scope and significance of research questions addressed through this linkage were crucial. The identification of genetic determinants of phenotypes and trajectories in ASD could support targeted early interventions; EMR linkage may inform algorithms to identify ASD in broader populations. These approaches could improve both patient outcome and family experience.
Conclusion/ImplicationsAs the cost of genetic sequencing decreases, WGS data will become part of the routine clinical management of patients. Linkage of WGS, EMR and administrative data has tremendous potential that has largely not been realized; including population-level ASD research to improve our ability to predict long-term outcomes associated with ASD.
Data Linkages to Study Pharmaceutical Health Services Delivery: Three Applied Examples
Authors: Johnson Karin , Xu Lanlan , Kiptanui Zippora , Gill Christine , Triebwasser Corey , Emery Danielle , Perlman Evan , Harris Ilene 
Published: September 2018

IntroductionThe safe, effective, and efficient use of pharmaceutical health services is a critical area of public health and social policy. Implementation and monitoring studies often use single data sources but require diverse data elements pertaining to patients and health services. Linking multiple data sources may enable more comprehensive studies.
Objectives and ApproachThe objective of this presentation is to describe three applied pharmaceutical health services projects in the United States that use data linkage to support program monitoring. A conceptual model was defined including the following key domains: (1) contextual determinants; (2) pharmacy service availability and coverage by payers; (3) receipt/use of services by patients; and (4) outcomes such as clinical outcomes, patient satisfaction and healthcare costs. Applied studies were selected to illustrate data linkage across different domains. For each study, we present the data sources used and the domains addressed by each data source. We also describe the linkage process.
ResultsStudy 1 assesses distance between patients and pharmacies in-network for health plans. It determined pharmacy address and patient ZIP code using several Medicare datasets and calculated driving distance using geocoding software.
Study 2 measures if patients targeted for services receive an intervention designed to prevent adverse drug events and improve patient health outcomes while reducing healthcare costs. Targeted beneficiaries are determined using Medicare administrative data and delivery of services is assessed based on a custom-developed encounter data set, linked by beneficiary.
Study 3 examines the association between prescription drug formulary design, medication use, and cost and health outcomes. For this, formulary data are obtained from a commercial source and utilization/outcomes data from commercial claims data. These datasets are linked by payer.
Conclusion/ImplicationsMany data sources are available for pharmaceutical health services research studies and linkage can be made at the patient, region, or payer level to support program monitoring and evaluation. Data linkage enables the inclusion of multiple domains, although multiple linkages and/or custom data may be needed for more complex studies.
The Effect of Medication Adherence on the Disease Course in Pregnant Women with Inflammatory Bowel Disease
Authors: Lee Sangmin (Sarah) , Seow Cynthia , Dahal Kamala Adhikari , Metcalfe Amy 
Published: September 2018

IntroductionMedical therapy to maintain disease remission is important in pregnant women with inflammatory bowel disease (IBD), as disease flares can predispose adverse materno-fetal outcomes. However, women with IBD are more concerned about medication exposure on their newborn during pregnancy, and often discontinue their medications.
Objectives and ApproachWe assessed the rate of disease flare on medication adherence pattern during pregnancy for women with IBD. Validated case definition was used to identify women with IBD from the Albertan’s hospitalization, emergency room, and physician claims databases (2010-2016). Pharmaceutical Information Network provided the dispensed medications. Adherence to medication was defined by medical possession ratio (MPR)≥0.8. Women with two consecutive prescriptions and MPR≥0.8 during pre-conception were included. Disease flare was defined by ≥1 hospitalization or emergency visit for IBD, or ≥1 prescription for steroids/rectal therapy. Chi-square tests and log binomial regression were used; covariates included age, drug class, and IBD subtypes.
ResultsOf the 370 women identified with IBD, 170 (45.9%) women were adherent to maintenance IBD medications in the one year prior to pregnancy. During pregnancy, 47 (27.6%; 95% CI: 21.4% to 34.9%) women, who demonstrated adherence in the pre-conception period, discontinued or were not adherent to their IBD medications, and 67 (39.4%; 95% CI: 32.3% to 47.0%) women had a disease flare during pregnancy. There was no significant difference between adherence to medication during pregnancy and a disease flare during pregnancy (p=0.38). In comparing women who were not adherent or discontinued their medication to those that were adherent, the adjusted relative risk ratio for a disease flare during pregnancy was 1.22 (95% CI: 0.81 to 2.04).
Conclusion/ImplicationsThe rate of disease flare during pregnancy was not significantly different for women with IBD that were adherent or not-adherent to their IBD medications during pregnancy. Future analysis will assess the rate of disease flare on medication adherence pattern prior to pregnancy.