bluuebunny/crossref_metadata_2025 huggingface dataset:
Visualising linked data using GIS: Western Australian Child Development Atlas
Authors: Sims Scott
Published: September 2018

IntroductionWhere people live can strongly influence their level of exposure to health-damaging factors, their vulnerability to poor outcomes, and the consequences of experiencing those poor outcomes. Geographical mapping of child outcomes is therefore an important component of monitoring the health and wellbeing of children and young people.

Objectives and ApproachThe Western Australian Child Development Atlas (CDA) maps population-level administrative, census, registry, and survey data, aggregated at various levels of geography. The project utilises geographic information system (GIS) technologies to identify and investigate spatial patterns in key health, social, learning and development indicators, overlaid by service locations.

The CDA is an online, interactive platform that provides policy developers, service providers, communities, and government with access to quality and easily comprehendible spatial data on the outcomes of children and young people. This information helps to identify geographic areas of highest need and priority, and patterns in service distribution relative to need.

ResultsThe CDA maps linked and non-linked de-identified aggregated data on children and young people (0-18 years) born or residing in Western Australia from 1990 until 2016. Key indicators from health, social, education, and welfare datasets are mapped at various levels of geography.

Using a case example of a WA community, we demonstrate how the CDA can enable policy-makers, service providers, and researchers to better identify priority areas for improved child health and wellbeing, and implement place-based approaches to service delivery.

Conclusion/ImplicationsMapping population data on children’s health and wellbeing can help identify areas of highest need and priority, and facilitate a targeted focus for service delivery within jurisdictional areas, including rural and remote regions. Outcomes can be monitored over time, enabling evaluation of the effectiveness of changes to service and policy.
Through the legal maze: An Act Respecting Research
Authors: McDonald Ted , MacKenzie Patricia , Barry Krista
Published: September 2018

IntroductionThe New Brunswick Institute for Research, Data and Training (NB-IRDT) is a recently established provincial research data centre and data custodian hosting anonymized linkable administrative data from the Government of New Brunswick (GNB) and other public bodies. GNB has committed to transferring research-relevant data from across GNB operations to NB-IRDT.

Objectives and Approach

Although NB-IRDT had received a small number of administrative data sets from the GNB Department of Health as of the end of 2016, transfers of other datasets from the Department of Health, Department of Social Development and other Departments was halted because of a series of legal opinions citing a lack of legislative authority to do so. This presentation details an innovative and transformative approach that overcame these obstacles to facilitate continued data sharing with NB-IRDT not just from those Departments but from across the spectrum of government operations.

ResultsPassed in the NB Legislature in March 2017 and proclaimed in May 2017, An Act Respecting Research modified 12 different pieces of existing legislation to define a clear legal authority through which pseudo-anonymized data from all of the Provincial Government plus numerous other public bodies could be transferred to NB-IRDT in linkable form. This included Acts as disparate as the Education Act, Mental Health Act, the Nursing Homes Act, the New Brunswick Housing Act, etc. An Act Respecting Research was the culmination of more than a year of collaborative effort between NB-IRDT and the Executive Council Office plus 14 different provincial line departments. The Act also permits the collection of the Medicare health insurance numbers by departments and public for data matching and transfer purposes.

Conclusion/ImplicationsThe Act Respecting Research is unique in Canada and would not have occurred without GNB’s commitment to the principle and practice of evidence-based policymaking. After the Act’s passage, NB-IRDT has received numerous datasets and work is ongoing on many more, from postsecondary education to road accidents and workers compensation claims.
How do socio-demographic differences in administrative records affect the quality (accuracy) of data linkage?
Authors: Randall Sean , Ferrante Anna , Boyd James , Brown Adrian
Published: September 2018

IntroductionRecord linkage is inherently uncertain, with all linkages containing some amount of false positive and false negative errors. Previous results have suggested that linkage error may not be evenly distributed throughout the population, with particular subgroups exhibiting higher rates of linkage error. Record linkage is inherently uncertain, with all linkages containing

Objectives and ApproachThis study investigated the distribution of linkage error using four large-scale Australian administrative datasets; hospital admissions datasets from Western Australia and New South Wales, and emergency presentation datasets from New South Wales and South Australia. Each dataset had been previously de-duplicated to a very high standard, with large scale manual review taking place; these results were used as our truth set.

Each dataset was linked using probabilistic record linkage with results (precision and recall) compared by gender, age, geographic indices of remoteness and socioeconomic status.

ResultsResults were highly dataset dependent. Consistent findings were lower linkage quality found for individuals living in remote locations, and lower linkage quality in those in the youngest category (those born after 1980). Some datasets showed lower linkage quality for females, for those in middle age as compared to the elderly, and for those with lower socioeconomic status. The differences in linkage quality found were typically small. Changes in threshold settings had generally no effect on the relationship between sociodemographic characteristics and linkage quality.

Conclusion/ImplicationsLinkage studies focussing on younger individuals and those in remote areas may have greater uncertainty regarding their results. Targeting efforts by linkage units may be required to ensure even distribution of linkage errors. Further research is required into investigating how linkage errors effect research outcomes.
Cecilia: an R package to automate data cleaning of administrative datasets
Authors: Garcia Alexandre Franco , Palfy Miro , Vasquez Stacy Ann
Published: September 2018

IntroductionData linkage has considerable potential to improve health and society. Linking vast and detailed information across multiple administrative population-scaled data sources enhances the quality of existing data, empowers population health research, and produces objective evidence to inform policy decisions. In this context, data cleaning is crucial to minimise linkage errors.

Objectives and ApproachAs dealing with the heterogeneity of administrative datasets is an acknowledged time-consuming task, the objective is creating a public and open-source R package to automate and report steps of data cleaning in a reproducible fashion.

The package automatically assesses variables and reports relevant information and issues for linkage purposes, then cleans the dataset based on problems found, reassesses the variables and reports results again.

It has a default cleaning procedure based on years of accumulated linkage knowledge and an interactive exploratory session to check variables individually. The report also includes all settings from both default and interactive session.

ResultsThe package accurately detected, cleaned and reported potential linkage problems in variables such as names, addresses and dates in so far 15 actual populational datasets from multiple sources, with a diverse range of format, content, and inconsistencies. The entire process took minutes rather than hours.

The reports correctly gathered, organised and presented all relevant information for linkage, in all distinct sections of the hyperlinked document, such as those related to the dataset, individual variables or settings used for cleaning. The different types of information included text, figures, data dictionaries, and frequency tables of detected issues, such as non-alphanumeric characters, annotation terms or suffixes and prefixes.

The output datasets had all evaluated variables with cleaned data plus extra columns containing only issues themselves or problematic records.

Conclusion/ImplicationsThe package accelerates the data cleaning of linkage variables, automating time-consuming steps, providing pertinent information for linkage as well as cleaned datasets. The complete process is time-efficient and reproducible.

As the output dataset contains variables with cleaned data and detected issues, it allows assessment of the level of cleaning performed.
Diabetic Ketoacidosis (DKA) at Diabetes Diagnosis in Children (0-18 years) in Ontario, Canada: A Population-Based Retrospective Cohort Study of Health Administrative Data
Authors: Mian Oxana , Wenghofer Elizabeth , Young Nancy , Jaakkimainen Liisa
Published: September 2018

IntroductionDiabetic ketoacidosis (DKA), a life-threatening complication of diabetes, is the leading cause of mortality and disability in children. The high cost of care for DKA and negative consequences of DKA on child’s health are known; however, the pediatric DKA trends in Ontario were not studied in the last fifteen years.

Objectives and ApproachTo examine time trends of the prevalence of pediatric DKA at diabetes diagnosis and socio-demographic characteristics associated with the DKA risk (child’s sex; age; geographic region; rural residence; material deprivation and ethnic concentration) in Ontario, Canada. Person-level de-identified data from the provincial registry for all Ontario children (0-18 years) newly diagnosed with diabetes (type 1 and 2) in 2004-2012 was linked with records in the national discharge abstract database (CIHI DAD) at the Institute for Clinical and Evaluative Sciences (ICES). SAS software (v.9.3) was used for Poisson and logistic regressions.

ResultsOf 10,617 children diagnosed with diabetes, 15.5% were diagnosed during a hospital admission for DKA. Prevalence of DKA at diagnosis did not change over the nine-year period (ptrend =0.99). There were statistically significant within-province regional differences in DKA prevalence at diabetes diagnosis, with the highest prevalence in South-Western Ontario (17.2%). Younger children (0-6 years and 7-12 years) were at higher DKA risk than 13-18 years old children (adjusted odds ratio (OR) 2.5 95% CI 2.2-2.8 and 2.1 95% CI 1.9-2.4). DKA at diabetes diagnosis was associated with material deprivation in young children (0-6 years)(OR 1.9 95% CI 1.4-2.5 for “most deprived” versus “least deprived”). In the older group (13-18 years), boys were at higher DKA risk than girls (OR 1.4 95% CI 1.1-1.7).

Conclusion/ImplicationsPrevalence of pediatric DKA at diabetes diagnosis in Ontario is among the lowest in the world; however, higher DKA prevalence among children residing in some geographic regions or most deprived neighbourhoods of the province despite the universal access to government-funded health care warrants further research.
Reducing bias in multivariate analyses due to the modifiable areal unit problem.
Authors: Tuson Matthew , Kok Mei Ruu , Yap Matthew , Vickery Alistair , Boruff Bryan , Murray Kevin , Turlach Berwin , Whyatt David
Published: September 2018

IntroductionThe Modifiable Areal Unit Problem (MAUP) arises from the aggregation of data organized by spatially defined boundaries. Aggregated values are influenced by the shape (zone effect) and scale of the aggregated units. Aggregations of the same data using different zones or scales can give different analytical results, none reliable.

Objectives and ApproachUsing population-level administrative health data in Western Australia, the objectives were to: accurately measure the association between health service utilization and demographic, socio-economic, and service accessibility variables; and develop models to accurately forecast areas of high health service utilization into the future.

Multiple zone designs and aggregation scales were used to examine the impact of MAUP in association studies. These zone designs and scales were then used in all-subset model selection processes, combined with repeated k-fold cross-validation, to generate forecast maps of areas having high future rates of health service utilization.

ResultsThe impact of the MAUP and methods to reduce this bias in association studies will be presented, for both simple and complex model designs. Maps indicating gradients of predicted probabilities of high rate of health service demand in the future can be used to optimize the placement of services, through the use of catchment areas based on road-network travel distance and population distributions.

Conclusion/ImplicationsThe impact of the MAUP on the analysis of spatially-aggregated data has been considered intractable. However, methods to reduce the impact of the MAUP can improve policy and planning decisions based on such studies.
Evolving population data linkage services to transform large-scale biobanking services
Authors: Irvine Katie , Ong Vivienna , Cooper Simon , Thackway Sarah
Published: September 2018

IntroductionMany population data linkage centres have been established to provide a mechanism for making linked administrative data available to approved third parties within robust governance frameworks. While current models support a wide variety of research, modifications are required for linked administrative data to better position biobanking research infrastructure.

Objectives and ApproachWe have sought to reconfigure population data linkage services to enhance the value of a newly established state-of-the art population and disease biobank embedded within a state based pathology network, equipped with robotic technology, with the capacity to store and process more than 3 million samples from participants consenting to data linkage and future unspecified research.

ResultsThree data service streams have been developed: longitudinal data linkage, cohort management and targeted recruitment. Traditional infrastructure for population data linkage will support the longitudinal data linkage stream, making data and biospecimens available for research, without direct patient identifiers. Technical and governance changes are necessary to enable the rapid release of contemporaneous patient and health system data for cohort management and recruitment purposes. The cohort management stream seeks to significantly reduce the manual follow-up of administrative data. The newly developed targeted recruitment service will leverage on the jurisdictional data holdings and structure of the health system and pathology network, to identify optimal sites and service providers for patient recruitment at scale, in an expedited manner.

Conclusion/ImplicationsModest changes to population data infrastructure have significant potential to enhance biobank research infrastructure. By fast tracking biospecimen accrual for diseases of population subgroups of strategic importance, this new service is intended to promote biobank viability, accelerate the pace of clinical trials recruitment and improve patient access to trials.
Describing hospital utilisation and associated factors following stroke using linked clinical registry and hospital administrative data.
Authors: Andrew Nadine , Kilkenny Monique , Sundararajan Vijaya , Kim Joosup , Thrift Amanda , Johnston Trisha , Grimley Rohan , Gattellari Melina , Katzenellenbogen Judith , Lannin Natasha , Boyd James , Flack Felicity , Chen Ying , Cadilhac Dominique
Published: September 2018

IntroductionSurvivors of stroke have complex needs from ongoing disabilities and have increased risk of cardiovascular diseases. The societal costs are therefore substantial. Person-level longitudinal data on the longer-term hospital utilizations of patients with stroke in Australia, and the factors that may influence usage in this setting, are rarely reported.

Objectives and ApproachWe used person-level linkages between the Australian Stroke Clinical Registry (AuSCR: 2009-2013) and hospital admission and Emergency Department (ED) data from four states to examine determinants of hospital utilisation following stroke. The index event was the first event recorded in AuSCR. The rate of hospital contacts/person/year was calculated from contacts 30-365 days post-discharge. Disability was determined from responses to EQ-5D-3L data collected at 90-180 days post-stroke. Comorbidities were identified using ICD-10 discharge diagnosis codes (5 year look back including the index event). Negative binomial regression was used adjusting for patient clustering by hospital and pre-stroke contacts and stratified by disability.

ResultsAmong 10,082 adults with acute stroke (55% male, median age 74 years, 81% ischaemic, 14% hemorrhagic, 5% undetermined, 44% with disability) from 39 hospitals, 57% had a hospital admission or ED contact in the first 30-365 days post-hospital discharge, with median contacts/person/year post-stroke of 1.09 (Q1, Q3: 0, 3.27) compared to a pre-contact rate of 0 (Q1, Q3: 0, 2.18). The strongest associations with subsequent hospital contacts were prior contacts (IRR:1.10, 95%CI:1.07, 1.13), not able to walk on admission (stroke severity) (IRR:1.19, 95%CI 1.07, 1.31) and having a higher comorbidity index score (IRR:1.18, 95%CI:1.14, 1.22). Within stratified cohorts younger age was associated with increased contacts in those with disability (

Conclusion/ImplicationsIn a large linked cohort of patients we have demonstrated the substantial ongoing burden that stroke imposes on hospital systems, particularly regarding survivors with other comorbidities and younger survivors with disability. Knowledge of disability and comorbidity burden may assist with targeting community and hospital interventions to reduce post-stroke hospital usage.
Population Analysis of the Settlement Movement in Western Canada
Authors: Antonie Luiza , Baskerville Peter , Grewal Gary , Turcotte Benjamin
Published: September 2018

IntroductionThe Canadian settlement of the west, via granting free homesteads, is perhaps one of the largest public policy undertakings in the nation's history. However, little is known about the homesteaders themselves, where they came from, how long they stayed and the settlement environment that was created at the time.

Objectives and ApproachThis research adopts a detailed population analysis of the settlement movement in Western Canada. In addition to outlining the social and economic characteristics of the homesteaders, the project answers the following central question: Did it create a stable society of settlers or did it create a field for speculative investment?

The data consist of machine readable individual level databases containing detailed information on and stories from circa 170,000 Alberta homesteaders. These homesteaders will be individually linked to three twentieth century Canadian censuses and the Canadian Pacific Railway's land records to provide an unprecedented holistic analysis of Alberta's early European population.

ResultsWe report on the linkage methodology used to integrate all these data sources. In addition, we discuss any particular issues we encountered given the nature of the historical data. We describe the data cleaning and standardization that was undertaken to facilitate the linkage process. We present and discuss the linkage results obtained, how much of the population was linked and what are the characteristics of those we couldn’t link.

We expect that this research will shed new light on persistence rates, trajectories of family composition, nature of labour market adjustment, degrees of social/gender inequality and impacts on regional development. The results will challenge many myths concerning homesteaders and their impact on western Canada and in the process provoke renewed discussion of western Canadian history.

Conclusion/ImplicationsThe research will inform and be informed by work currently being undertaken on migration patterns at the international level. Finally the research has implications for understanding the legacies of rapid population movements, state formation, public policy and national identities in the present.
Harmonization of data from cohort studies– potential challenges and opportunities
Authors: Dahal Kamala Adhikari , Patten Scott , Williamson Tyler , Patel Alka , Premji Shahirose , Tough Suzanne , Letourneau Nicole , Giesbrecht Gerald
Published: September 2018

IntroductionPooling data from cohort studies can be used to increase sample size. However, individual datasets may contain variables that measure the same construct differently, posing challenges in the usefulness of combined datasets. Variable harmonization (an effort that provides comparable view of data from different studies) may address this issue.

Objectives and ApproachThis study harmonized existing datasets from two prospective pregnancy cohort studies in Alberta Canada (All Our Families (n=3,351) and Alberta Pregnancy Outcome and Nutrition (n=2,187)). Given the comparability of the characteristics of the two cohorts and similarities of the core data elements of interest, data harmonization was justifiable. Data harmonization was performed considering multiple factors, such as complete or partial variable matching regarding question asked/responded, the response coded (value level, value definition, data type), the frequency of measurement, the pregnancy time-period of measurement, and missing values. Multiple imputation was used to address missing data resulting from the data harmonization process.

ResultsSeveral variables such as ethnicity, income, parity, gestational age, anxiety, and depression were harmonized using different procedures. If the question asked/answered and the response recorded was the same in both datasets, no variable manipulation was done. If the response recorded was different, the response was re-categorized/re-organized to optimize comparability of data from both datasets. Missing values were created for each resulting unmatched variables and were replaced using multiple imputation if the same construct was measured in both datasets but using different ways/scales. A scale that was used in both datasets was identified as a reference standard. If the variables were measured in multiple times and/or different time-periods, variables were synchronized using pregnancy trimesters data. Finally, harmonized datasets were then combined/pooled into a single dataset (n=5,588).

Conclusion/ImplicationsVariable harmonization is an important aspect of conducting research using multiple datasets. It provides an opportunity to increase study power through maximizing sample size, permitting more sophisticated statistical analyses, and to answer novel research questions that could not be addressed using a single study.
Data linkage to national Australian health insurance data to investigate exposure to environmental hazards: the example of residential asbestos
Authors: Anderson Phil , Korda Rosemary , Law Hsei Di , Kirk Martyn , Guiver Tenniel
Published: September 2018

IntroductionThe enrolment data for Medicare, the Australian universal health insurance provider, covers almost the entire population. Medicare data are commonly used for data linkage, usually to access national medical and pharmaceutical data. However, the enrolment data also enable the identification of geographical cohorts for studies analysing exposure to environmental hazards.

Objectives and ApproachOne example of this was the ACT Asbestos Health Study examining the health risks associated with living in houses insulated with loose-fill asbestos in the Australian Capital Territory. The Medicare Enrolment File contains the personal details and addresses of all people enrolled since 1984, including all updates to these details. We linked these data to a register of ~1100 affected properties, with subsequent linkage to the national death index and the Australian Cancer Database. We estimated Standardized Incidence Ratios (SIR) for selected cancers in people living in these houses to obtain a measure of exposure to environmental risk within the population.

ResultsAfter intensive cleaning and standardisation, nearly all (99.8%) of the affected addresses were linked. There were over one million people who had at least one ACT address between 1983 and 2013, and 2% of these had lived at an affected address and classified as exposed. The adjusted incidence of mesothelioma in exposed males was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02–5·24), and there were some statistically significant results. The study population, number of deaths and cancers of interest were validated against the ACT census and registry figures. There were some limitations in coverage due to the period of available data, the frequency of address updates, and records with postal rather than residential addresses, but these were tested by sensitivity analyses.

Conclusion/ImplicationsThe study demonstrates the power of data linkage to (a) obtain a measure of exposure to an environmental risk within a population, and (b) obtain outcomes for the resulting case and control cohorts. This method could be applied in other risk studies where exposure is based on geography.
Emergency Department Use in Patients with Cancer: A Population-Based Study
Authors: Wang Grace , Bakal Jeff , McRae Andrew , Quon Harvey
Published: September 2018

IntroductionEmergency Department (ED) visits in cancer patients represent a significant burden to both patients and the health care system. Emergency Care of cancer patients is complex compared to the population. There is lack of knowledge regarding the pattern and reasons for ED visits in this population.

Objectives and ApproachWe sought to identify factors and patterns associated with ED use among cancer patients, in the first year after diagnosis. Adult cancer patients diagnosed between 2011 and 2013 were identified from the Alberta Cancer Registry. This was linked with cancer related treatments extracted from medical records system at provincial cancer centers. ED visits and outpatient clinics were acquired from National Ambulatory Care Reporting System (NACRS). Databases were linked by unique patient identification number. Previous cancer patients were defined by having at least one cancer related diagnosis in NACRS before. The other patients were treated as non-cancer patients.

ResultsCancer patients accounted for 6.7% of ED visits and 10\% of ED hours. They had higher male percentage (53% vs. 49%), higher admission rate (23% vs. 10%), ambulance usage (20% vs. 12%) and longer stay (LOS) (171 vs. 131 mins) compared to non-cancer patients. 24% of cancer patients had 4 or more ED visits/year and accounted for 59% of visits. Lung and liver cancer patients had higher ED utilization than patients with other cancers. Breast cancer patients had more after-treatment-ED-visits (41% within a week vs. 26% in lung cancer). Use of ED was highest within 1 month of diagnosis for all types except breast cancer, which was highest at 2 months after. Differences were observed between urban and rural area for numbers reported above.

Conclusion/ImplicationsThese data suggest high ED utilization by cancer patients, and variation in utilization by cancer type. Identifying the timing and risk factors of ED visit for each cancer type, especially on frequent ED users presents opportunities to improve care in oncology clinics and ED.
Do callers of young children with fever follow the self-care recommendations given by a nursing triage line?
Authors: Manji Sofiya , Garner Charlene , Steinlicht Delores , Edwards Sarah , McDonald Sheila
Published: September 2018

IntroductionThe management of fever can be a stressful situation for caregivers of young children. Accessing emergency departments and urgent care centres (ED/UCCs) due to concerns about fever and the potential consequences of child fever is common, despite fever rarely being considered a medical emergency.

Objectives and ApproachDetermine the non-compliance rate with public health advice for self-care at home for young children (3-35 months) with a fever. Non-compliance was defined based on the presence of a record of healthcare use within 72 hours following a call to a nurse telephone triage line, Health Link (HL), and receiving a self-care recommendation. Callers between October 2015-March 2016 were identified and linked with four databases: registry files, National Ambulatory Care Reporting System; Inpatient-Discharge Abstract Database and Physician Claims (N = 879). Overall non-compliance rate and descriptive analysis by child age, caregiver age, geography, and call time were completed.

ResultsThe overall non-compliance rate with HL advice was 35.6%. Among callers, 17.5% visited an ED/UCC, 1.1% had an inpatient hospital admission, and 21.3% visited a physician’s office. Among the patients that utilized health care services after the HL call, 13.6% only visited ED/UCC, 18% only visited a physician’s office, and 4% utilized more than one type of health care service. Callers in rural and rural remote areas had lower odds of visiting a physician’s office compared to the urban areas (p-value <0.01). No significant differences were found by child age, caregiver age or time of call.

Conclusion/ImplicationsFindings of this study suggest that approximately one-third of callers are not following the telephone triage advice, potentially leading to unnecessary increased burden on the healthcare system. Further study is warranted to examine reasons for non-compliance. Strategies to increase compliance in caregivers should be explored.
Adherence And Persistence To Antidepressant Medication During Pregnancy: Does It Differ By The Class Of Antidepressant Medication Prescribed?
Authors: Dahal Kamala Adhikari , Patten Scott , Lee Sangmin (Sarah) , Metcalfe Amy
Published: September 2018

IntroductionPregnant women are often concerned about the impact of antidepressant medication use on their pregnancy, such as congenital abnormalities. This concern may vary in a way that depends on the class of antidepressant medication prescribed.

Objectives and ApproachThis study examined the rate of adherence and persistence to antidepressants based on the class of antidepressants prescribed during pregnancy This is a retrospective cohort study using population-based administrative data in Alberta– linking delivery record, hospitalization data, physician claims data, emergency department data, and prescription medication data. The eligible study population included women with depression who gave birth between 2012-2015, and were adherent (medication possession ratio ≥80%) to ≥ 2 consecutive antidepressant prescriptions during the preconception year (n=1,865). The rates of adherence and persistence (prescription refill gap ≤30 days) were calculated by medication class and were compared using chi-square tests.

ResultsDuring pregnancy, 834 (44.7%) women completely stopped taking antidepressants. Among those taking antidepressants, the overall rate of adherence was 62.6% (95% CI: 59.4%, 65.7%). The rate differed significantly by medication class (p<0.0001), with rate of 75.1% (95% CI: 68.3%, 80.9%) for serotonin-norepinephrine inhibitors, 60.9% (95% CI: 57.2%, 64.5%) for selective serotonin reuptake inhibitors, 42.9% (95% CI: 19.9%, 69.2%) for non-selective monoamine reuptake inhibitors, and 37.5% (95% CI: 22.4%, 55.4%) for the atypical antidepressants. Similarly, 40.7%, (95% CI: 37.5, 44.0) of women were persistent to antidepressants up to the full pregnancy period – similar to the adherence pattern, the rate differed significantly by medication class.

Conclusion/ImplicationsAdherence to and persistence in using antidepressants is low during pregnancy and it varies by medication class, possessing to the worsening of depression symptoms. This could be improved by conducting more research on drug safety during pregnancy and translating research evidence into treatment decision and correcting mothers’ misperceptions towards antidepressants.
Training Coding Specialists for the Future: Methods and Materials for the Beta Version of ICD-11
Authors: Eastwood Catherine , Southern Danielle , Boxill Alicia , Maciszewski Malgorzata , Quan Hude , Cullen Denise , Penchoff Margaret , Ghali William
Published: September 2018

IntroductionIn June 2018, the World Health Organization (WHO) will release the 11th Version of International Classification of Diseases (ICD-11). New training methods and materials are required. As a WHO Collaborating Center, with Canadian Institute for Health Information (CIHI) members, we trained 6 coding professionals for testing ICD-11 coding processes.

Objectives and ApproachThe objective was to achieve a high level of inter-rater reliability using ICD-11 for acute care chart coding. We used Adult Learning principles with CIHI members and 6 certified coding specialists to co-create presentations, practice materials, and decision trees to teach knowledge and skill with ICD-11 tooling and content. Training involved 14 hours of interactive learning plus additional practice hours. A bank of questions and coding scenarios tested knowledge and application of ICD-11 terminology and principles. Coding was undertaken on a set of 3000 randomly selected inpatient Calgary hospital discharges as part of a large CIHR funded ICD-11 field trial.

ResultsThe coding team achieved an average score of 84% on the ICD-11 coding quiz and 0.65 (0.33 -1.0) agreement on parent code of main condition for the coding quiz scenarios.  60 inpatient charts were coded by more than one coder to test inter-rater reliability.  Agreement was ≧ 0.80 for the majority of parent codes for main condition. Coding differences may be due to unfamiliar code choices or training gaps. New code descriptions in ICD-11 enhance code selection. Challenges included training while codes were being built in the ICD-11 browser, and minimal coding rules or standards.

Conclusion/ImplicationsRecommendations include more code descriptions in the browser and rules in a reference guide, teaching from simple to complex conditions, and multiple scenarios with ‘gold standard’ codes for practice. Reference Guide, Coding Tool, and Browser recommendations have been shared with members of the WHO Morbidity and Quality & Safety Advisory groups.
Effect of the Look-back period for the estimation of the incidence rates using administrative data
Authors: Kim Mira , Chae Kyung-Hee , Jung Chai Young , Chung Youn-Jee , Lee Minkyoung , Kim Hyun-Kyung , Hwang Hye-Jin , Choi Hyun-Hee , Kim Mee-Ran , Kim Sukil
Published: September 2018

IntroductionAdministrative data are widely used to estimate epidemiologic indicators. The look-back period is needed to define baseline population for the incidence. However, short look-back period is known to overestimate incidence of diseases misclassifying prevalent cases to incident cases. A short look-back period with longer observation period causes misclassification more inconsistent.

Objectives and ApproachThe purpose of the study is to estimate the incidence rate of uterine leiomyoma by adjusting the misclassification error. We selected 319,608 women aged 15- 54 in 2002 from Korean National Health Insurance Service (KNHIS) cohort data. 34,445 cases were identified during 2002 - 2013. We applied 1-year look-back period as of 2003 and the actual look-back period increases with year, which incurs inconsistent misclassification error. Multiple regression model was used to estimate the number of incidence cases of the 11th look-back year for each year. Annual and adjusted annual incidence rates of uterine leiomyoma were calculated and compared.

ResultsThe annual number of patients(X1) is linearly related with the number of misclassification cases, and the number of misclassification cases are logarithmically associated with the look-back periods(X2). The regression equation was 0.07217 (y= 0.07217+ 0.00003213* X1 + 0.07992*ln(X2), R2=94.3). Crude incidence rate of uterine leiomyoma during the study period was 11.7% (35,992 cases) and adjusted rate was 10.5% (32,477cases). The annual incidence and adjusted annual incidence increased by 2.29 times and 2.86 times between 2003 and 2013, respectively. With look-back period of 11 years, 4,588(53.8 %) patients with uterine leiomyoma were estimated to have prior history of the disease.

Conclusion/ImplicationsWe proposed an adjustment for the misclassification error according to look-back periods. The method is applicable to estimate various healthcare events such as disease incidences and healthcare usage. Although the regression model showed very strong R-squared, follow-up study after several years is needed to validate the study results.
Partial Agreements in Probabilistic Linkages
Authors: Brown Adrian , Randall Sean , Ferrante Anna , Boyd James
Published: September 2018

IntroductionRecord linkage units around the world use probabilistic linkage techniques for routine linkage of large datasets. It is widely known how probabilities are converted to agreement and disagreement weights for each field, yet there has been little exploration of the methodology to optimally convert field similarity scores into partial weights.

Objectives and ApproachString similarity comparators such as Jaro-Winkler are commonly used in traditional linkage, other comparators such as the Sorenson Dice coefficient, Jaccard similarity and Hamming distance are used in alternative privacy-preserving record linkage techniques. Determining partial weights to apply at each level of similarity is a non-trivial task. However, both types of linkages would greatly benefit from similarity to weight functions for each field that maximises the accuracy of the linkage.

We evaluated several methods for computing partial agreement weights and applied these to synthetic datasets with varying levels of corruption. We then evaluated the methods on real administrative datasets.

ResultsExact comparisons can miss matches where typographical errors or misspellings produce small changes in value. Similarity comparisons can reduce the number of missed matches, but may also increase the number of incorrect matches.

Various results of the partial agreement methods on Jaro-Winkler, Sorenson Dice coefficient, Jaccard similarity and Hamming distance comparators will be presented. A generic function to convert similarity values to weights, created from synthetic data, can be used on most datasets with a greatly improved result in linkage quality. However, maximising the linkage quality requires the creation of similarity-to-weight functions that are optimised for each dataset.

Conclusion/ImplicationsAccuracy in record linkage is vital for the correct analysis of linked data. It is even more critical in privacy-preserving record linkage where the ability for clerical review is limited. Optimised functions for converting similarities to partial weights can significantly improve the quality of linkage and should not be overlooked.
Public Cloud: The Future of Record Linkage?
Authors: Brown Adrian , Randall Sean , Ferrante Anna , Boyd James
Published: September 2018

IntroductionBusinesses worldwide are increasingly adopting the storage, compute and analytical services provided by cloud computing. Yet, few operational linkage units are keeping pace with this world of technological change - most use legacy systems approaching their limits with the rapidly increasing size and range of datasets now required for linkage.

Objectives and ApproachTo meet the demands of linkage for the near future, it is important that new solutions for linkage consider the services provided by public cloud infrastructure for compute, storage and analytics. We examined Platform as a Service (PaaS) offerings for use in the development of a cost-effective cloud model for scalable, privacy-preserving record linkage (PPRL). PPRL techniques were adapted to maximise the quality of linkage and to automate as much of the process as possible. Finally, a prototype was created to demonstrate the capabilities and potential of the model.

ResultsWe present our cloud model for PPRL, a platform for record linkage that provides rapid scaling of resources to meet demand, and the results of how our prototype performed on massive datasets.

Conclusion/ImplicationsThe application of record linkage using relatively inexpensive cloud infrastructure represents a significant step towards providing an efficient and scalable record linkage service to researchers and government. Larger datasets can be linked efficiently, including national or cross-jurisdictional datasets, with little investment in private infrastructure, and improved turnaround times for researchers.
Linking Antimicrobial Resistance Surveillance Data to Provincial Hospital Records: A Descriptive Study of Patient and Facility-level Characteristics
Authors: Lee Seungwon , Ronksley Paul E , Garies Stephanie , Quan Hude , Faris Peter , Li Bing , Henderson Elizabeth
Published: September 2018

IntroductionAntimicrobial resistance (AMR) is an emerging phenomenon where microorganisms develop resistance against treatment antimicrobials, resulting in ineffective clinical interventions. The recent development of AMR surveillance systems at global and national stages highlights the growing importance of this topic from a public health perspective.

Objectives and ApproachThe objective was to link standardized population-based hospital AMR surveillance data with hospitalizationrecords to inform patient safety practices in Alberta, Canada. Incident inpatient cases of Methicillin-Resistant Staphylococcus aureus (MRSA),identified by Alberta Health Services Provincial Infection Prevention and Control(IPC) Surveillance from five acute care facilities in the Calgary zone (April 2011 to March 2016),were deterministically linked to the Discharge Abstract Database using Provincial Healthcare Number and gender. The incident cohort was stratified into hospital-acquired (HA-MRSA) and community-acquired MRSA (CA-MRSA) cases. Descriptive statistics were used to describe the patient outcomes and facility characteristics of these two groups.

ResultsA total of 2550 unique patients, representing 93.5% of the surveillance cohort, were successfully linked to hospitalization records. A total of 1259 patients belonged to HA-MRSA categories and 1291 patients belonged to CA-MRSA categories. Patients with HA-MRSA had longer hospital stays, were older, were more likely to have prior hospitalizations, had higher Charlson Comorbidity Scores, and were more likely to die in hospital when compared to patients with CA-MRSA. HA-MRSA results emphasized the important roles of in-hospital patient safety practices whereas CA-MRSA results alluded to the impact of community public health and primary care services onthe risk of hospitalization, although detected CA-MRSA numbers were likely underestimated due to selection bias within our linked cohort.

Conclusion/ImplicationsThis is first Canadian study describing HA-MRSA and CA-MRSA using linked population databases. It offers a glimpse into the intricate relationship between patient health and our healthcare system. This knowledge represents an important step forwarding building IPC strategies for managing AMR and improving outcomes in Alberta and in Canada.
Using linked data and family studies to understand multigenerational causes of low birthweight among Australian Aboriginal infants
Authors: Gibberd Alison , Simpson Judy , McNamara Bridgette , Eades Sandra
Published: September 2018

IntroductionLow birthweight is common among Aboriginal infants. Birthweight is correlated across generations due to the transmission of genetic and environmental factors. Another cause may be fetal programming, where a fetus’ response to a hostile environment leads to poor adult health and, in turn, a poor uterine environment for her offspring.

Objectives and ApproachIdentifying a causal relationship between maternal birthweight and offspring birthweight is difficult. However, we can gain insights by approaching the question from several different angles, including family studies involving both parents and cousins who share maternal grandparents. Family studies using linked data are possible with data from Western Australia (WA), the only Australian state with a database of family relationships.

We used linked birth, hospital, mental health, and family relationship records of 12,865 Aboriginal singletons born 1998 to 2011 in WA whose mother also linked to a WA birth record from 1980 onwards, and their parents’ records.

Results17% of births were small for gestational age. Using a linear regression model with a generalised estimating equation approach for offspring birthweight z-score (BWZ), the coefficient for maternal BWZ was 0.17 (95% CI: 0.14, 0.20), compared to 0.13 (95% CI: 0.10, 0.16) for paternal BWZ. The difference in coefficients (0.03 [95% CI: -0.01, 0.08]) provides only limited support for the fetal programming hypothesis. Other associations with offspring BWZ were much larger, including maternal smoking (-0.39 [95% CI: -0.45, -0.34]). After restricting the sample to cousins with shared maternal grandparents (fixed-effects model), the mother-offspring association was fully attenuated (-0.01 [95% CI: -0.07, 0.05]), suggesting transmission of maternal genetic and environmental factors alone can explain the association, though the 95% confidence interval was wide.

Conclusion/ImplicationsIf fetal programming is an important cause of low birthweight, Aboriginal people would be disproportionately affected, following generations of low birthweight and chronic disease. However, the family studies indicate fetal programming has a limited role compared to other risk factors in the current pregnancy.
An effective privacy enhanced interface to support record linkage decisions
Authors: Kum Hye-Chung , Ilangovan Gurudev , Li Qinbo , Li Yumei , Ragan Eric
Published: September 2018

IntroductionPrivacy enhanced technologies (PET) are those that measure and protect privacy by preventing unnecessary use of personal data without loss of the functionality of the information system. In practice, implementing such a system requires fine-grained access control so that access can be granted in smaller chunks of data.

Objectives and ApproachIn record linkage, PET to date has mostly meant separation of identifiers and sensitive information to allow access to only the necessary part. Moving beyond this current norm, we have designed a privacy enhanced interface to support linkage that discloses only the needed information at the sub variable level, when needed to make good decisions, to reduce exposure of personally identifiable information (PII). The system allows for access to PII both at (1) cell level (e.g., only names of needed people are released) or (2) sub-cell level (e.g., only part of a name, suffix or characters, is released).

ResultsIn a user study (N=104) where participants tried to link complicated situations (e.g. twins, Sr/Jr, change of last name) using the interface, we found that users given fully masked data, 0% of information disclosed, were still able to get 75% accuracy using supplemental visual markup. The markups depict data discrepancies such as swapped first and last names, transposed characters, different characters and missing data. More importantly, with this effective interface, we found that there were no statistical difference in accuracy of linkage (84%) or time taken between users with access to all data and those with access to only 30% of the data. We have released a tutorial where users can experience balancing between information disclosure and accuracy of results on sample data.

Conclusion/ImplicationsPrivacy is a major public concern when PII is legitimately accessed to link data. Our study demonstrates that a well-designed privacy enhanced interface can significantly reduce exposure of PII to people when resolving ambiguous linkages without compromising linkage quality. This research points to a new direction for PET in record linkage beyond encryption.