bluuebunny/crossref_metadata_2025 huggingface dataset:
Association between antibiotic prescribing and deprivation in Wales: A multilevel analysis
Authors: Adekanmbi Victor , Smith Ann , Farewell Daniel , Jones Hywel , Paranjothy Shantini , Routledge Phil , Francis Nicholas
Published: September 2018

IntroductionThe most recent Welsh Antimicrobial Resistance Programme (WARP) report on antibiotic use in primary care found significant variations between Health Boards and hospitals in gross antibiotic use in 2014. The aim of this study was to evaluate the association between socioeconomic deprivation and antibiotic prescribing volumes.

Objectives and ApproachWelsh General Practitioner (GP) antibiotic prescribing data for years 2013 to 2016 for patients’ resident in Wales were extracted from the Secure Anonymised Information Linkage GP tables. Deprivation was assessed by linking prescribing events to the Welsh Index of Multiple Deprivation (WIMD) score for the patient’s neighbourhood area. The association between deprivation area and antibiotic prescribed (items per 1000 persons per day) was stratified according to the patient’s age, sex, prescription year and antibiotic class. A three-level multilevel Poisson regression model of 1.58 million patients nested within 349 GP practices, nested with 67 GP clusters, was specified to assess the associations

ResultsJust over 7.97 million antibiotic items were prescribed between 2013 and 2016. Patients in the most deprived WIMD quintile had an overall prescription rate that was 25.2% higher than those in the least deprived WIMD quintile. The final model revealed that residing in the most deprived WIMD quintile (incidence rate ratio [IRR] = 1.1769, 95% confidence interval [CI] 1.1768 to 1.1770, being female (IRR = 1,2699, 95% CI 1.2698 to 1.2700), being aged $\geq$90 (IRR = 2.0687, 95% CI 2.0683 to 2.0690), and prescription year being 2013 were associated with significantly higher rate of antibiotics prescription. There were significant primary cares clustering of antibiotics prescription in Wales.

Conclusion/ImplicationsThis study provides evidence that patients in areas of higher socioeconomic deprivation are more likely to be prescribed antibiotics in primary care in Wales. Population health prevention strategies aimed at reducing high antibiotic prescription rates should consider targeting areas of high deprivation.
Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
Authors: Hollinghurst Joe , Fry Richard , Akbari Ashley , Rodgers Sarah
Published: September 2018

IntroductionDemographic profiling is an important aspect of anonymised healthcare research to identify the population of interest. Typically, administrative data is used in conjunction with patient registers to create cohorts, but it can be a time consuming process. We describe a method using routinely collected health data to identify vulnerable populations.

Objectives and ApproachUsing existing longitudinal data and the Residential Anonymised Linking Field (RALF) we aim to identify institutions linked to vulnerable populations. We search for specific characteristics of these institutions including the age of occupants, number of current residents, and rate of change of occupants. We also aim to compare our method to a pseudonymised national registry for care homes to ensure it is accurate. This can effectively reduce the need for repeat pseudonymisation of institutions, which is both expensive and time consuming.

ResultsTo implement our method we found the most recent address for living individuals aged 65-95. This produced 202,640 residences from 1,330,335. Of the 202,640 residences, 1347 had four or more cohabitants aged 65-95, and 172 had exactly three residents with ten or more distinct individuals registered over a 10-year period. Our final synthetic dataset therefore had 1519 unique potential care homes to compare to the national registry, which contains 1525 registered care homes.

We can now link the synthetic dataset to individuals to flag their residential status, which may be a defining factor in their level of care. Furthermore, we can answer specific research questions relating to their residency, such as the time it takes to move to a care home following a hospital admission.

Conclusion/ImplicationsBy using quantifiable characteristics of care homes we were able to create a synthetic care home register by searching existing data. This is a reproducible process that would be of particular benefit for projects where a registry is not available, or where time or cost would limit the availability.
Maternal mortality of women with opioid-use during pregnancy in England: investigating bias in a cohort of linked mother-baby hospital records
Authors: Blackburn Ruth , Wijlaars Linda , Harron Katie , Guttmann Astrid , Gilbert Ruth
Published: September 2018

IntroductionOpioid-addiction is a major public health threat, with rates of drug misuse related deaths increasing in North America and England. Linkage within and between administrative data datasets is important for capturing determinants and outcomes but this vulnerable population is highly susceptible to linkage error, which can result in inaccurate estimates.

Objectives and ApproachWe investigated neonatal abstinence syndrome (NAS) as a marker of opioid-use in pregnancy, using linked mother-baby records to identify maternal opioid-use based on NAS in the baby’s record. Maternal all-cause mortality was compared for mothers with and without a NAS-pregnancy. Bias was assessed through comparison of linked and unlinked NAS baby characteristics. De-identified national hospital inpatient data – including postcode-district and GP surgery-code – were used for deterministic and probabilistic linkage of mothers and babies born in England 2002-2013. Linked national mortality data captured maternal deaths

ResultsLinkage between maternal and baby records was possible for 96% of all live births in England, but for only 88% of study/cohort babies with NAS (n=18,087). NAS babies with unlinked records represented a more vulnerable population with longer hospital stay (median 12 versus 7 days, p<0.001), low birthweight (44% <2500g versus 27%, p<0.001) and discharge to social services (13% versus 8%, p<0.001) than NAS babies who could be linked to maternal records. Non-linkage may plausibly be driven by mismatching or missing identifiers reflecting adoption and out-of-home care arrangements for the baby, potentially also indicating greater maternal adversity. Within the linked cohort (comparing 13,581 women with a NAS baby and 4,205,941 women without a NAS baby), the crude hazard ratio for all-cause mortality was 12.1 (11.1-13.2).

Conclusion/ImplicationsReview of unlinked records suggests evidence of linkage bias, with the implication that our results may underestimate the risk of death among women with opioid-use. Complementary linkages, drawing on other data - such as birth records where the mother is named - could help address non-linkage driven by out-of-home care.
Evaluating the impacts on health outcomes of Welsh Government funded schemes designed to improve the energy efficiency of the homes of low income households: A comparison of individual level and area based schemes.
Authors: Morrison-Rees Sian , Lowe Sarah
Published: September 2018

IntroductionLiving in a cold and/or damp house can damage health. To reduce fuel poverty in Wales, the Welsh Government developed domestic energy efficiency schemes - an individual-level scheme, Warm Homes Nest and an area-based scheme, Warm Homes Arbed. Both schemes provide improvements to those most likely affected by fuel poverty.

Objectives and ApproachOverall aim: to evaluate the health impacts of Welsh Government funded schemes designed to reduce fuel poverty. Presented objective: to investigate the relative impact of the individual-level and area-based schemes on the health of recipients.

A longitudinal dataset was created using the anonymised residence that received improvements linked to residents’ health measures (hospital admissions, GP prescriptions and clinical diagnoses) using routine health records held in the SAIL Databank at Swansea University.

We used difference-in-difference (DID) estimations to compare any changes in recipient health before and after intervention with any concurrent change in health in those yet to receive the intervention.

ResultsAn analysis of the Warm Homes Nest Scheme, published in 2017 and presented at the IPDLN 2017 conference found a positive impact of the scheme on the health of recipients.

This presentation will describe the further analysis (concluding shortly) comparing the area-based Arbed scheme with both the recipients of the individual-level Nest scheme and groups in comparable need that had not yet received the intervention. We will present results focussing on the relative impacts of the two schemes on cardiovascular, respiratory and general health.

Conclusion/ImplicationsProviding home energy efficiency interventions has the potential to benefit population health; however, there is a scarcity of evidence comparing different methods of implementing schemes. Our findings will inform more effectively-focussed home energy efficiency schemes and potentially thus improve the health of people living in Wales.
Is educational attainment associated with acute exposure to air pollution and pollen, and is it worse for pupils with asthma and seasonal allergic rhinitis?
Authors: Mizen Amy , Lyons Jane , Akbari Ashley , Berridge Damon , Carruthers David , Davies Gwyneth , Dearden Lorraine , Doherty Ruth , Mavrogianni Anna , Lake Iain , Rodgers Sarah
Published: September 2018

IntroductionThere is a lack of evidence of the adverse effects of air pollution and pollen on cognition for people with air quality related health conditions. This study explored the effects of air quality and respiratory health conditions on educational attainment for 18,241 pupils across the city of Cardiff, United Kingdom.

Objectives and ApproachAnonymised, routinely collected health and education data were linked at the household and school level with modelled high spatial resolution pollution data, and daily pollen measurements using the Secure Anonymised Information Linkage (SAIL) databank. This created 7 repeated cross-sectional cohorts (2009-2015). Multilevel linear regression analysis examined whether exam performance was associated with health status and/or air quality levels averaged at school and home locations during revision and examination periods. We also investigated the combined effects of air quality and associations with educational attainment for pupils who were treated for asthma and/or Severe Allergic Rhinitis (SAR), and those who were not.

ResultsThe cohort contained 9337 males and 8904 female pupils. There were 871 treated for asthma, 2091 for SAR, and 634 treated for both. Asthma was not associated with exam performance (p=0.700). However, SAR was positively associated with exam performance (p 2) was negatively associated with educational attainment (p = 0.002). Other indicators of air quality (pollutants: Ozone, Particulate Matter - PM2.5, and pollen) were not associated with educational attainment (p> 0.05). Exposure to NO2 was negatively associated with educational attainment irrespective of treatment for asthma or SAR. There was no combined effect of air quality on the variation in educational attainment between those who are treated for asthma and/or SAR and those who were not.

Conclusion/ImplicationsIrrespective of health status, exposure to NO2 was negatively associated with educational attainment. Treatment seeking behaviour may be a possible explanation for the positive association between SAR and educational attainment. For a more accurate reflection of health status, health outcomes not subject to treatment seeking behaviour should be investigated.
Access to palliative care in Canada
Authors: Johnson Tracy , Cheng Clare , Lawand Christina , Kelly Maureen
Published: September 2018

IntroductionMany Canadians prefer to remain in the community at end-of-life, and to die at home. To do so, early and integrated palliative care (PC) is needed to provide individuals with care and support services across care settings. Measuring access to PC can help to evaluate progress over time.

Objectives and ApproachThis presentation will show findings from our study on whether Canadian decedents had access to PC in the last year of life. Data from physician billings, drug claims, home care, long-term care and acute care were linked to identify decedents and PC service use. These data were also used to examine how PC may affect, or be affected by other interactions with the health system, including inpatient alternate level care days, admissions from long-term care, emergency department visits and stays in intensive care units. Gaps in data availability and quality will also be highlighted.

ResultsAbout 70% of decedents were identified using administrative health data, although there were variations across jurisdictions due to differences in data availability and quality (9%-81%). For decedents identified across care settings, few received PC in the community in their last year of life, ranging from 4% in long-term care to 12% in home care. More decedents were identified as palliative in acute care (44%) but only one-third received PC in another setting despite multiple interactions with the health system in the last year of life. Those who had integrated, community-based PC were less likely to have a stay in an intensive care unit, and more likely to die in the community. However, few Canadian decedents had access to this type of care.

Conclusion/ImplicationsData linkage identified opportunities for earlier integration of PC and improved care transitions. However, lack of common definitions of PC across sectors and jurisdictions, limitations in data availability and issues in PC coding were identified. Improvements in PC data are required to evaluate progress for the future.
Priorities for future research: the community adding value to linked data research
Authors: McKenzie Anne , Holland Maria , Harrison Hayley , O'Donnell Melissa , Preen David B
Published: September 2018

IntroductionWhilst there is limited published information on the benefits of engaging the public in linked data research, our presentation will add to international knowledge about the benefits of involving the community in a priority setting exercise for future research areas in a new linkage project.

Objectives and ApproachWe’ll co-present with a consumer about our experiences of the community having a role in linked data research over the past 20-years. Community members have provided input into: research projects; feedback to government agencies; submissions to federal/state governments; issues about access to data; and priorities for research.

In 2017 community members prioritised broad research areas for a new project involving cross-agency linkage, investigating pathways to wellbeing and social-outcomes across the life-course to improve outcomes and identify cost-efficiencies. Community members completed a survey to rank the broad themes and then attended a workshop to discuss the themes and identify gaps or new ideas.

ResultsFollowing the workshop all suggestions made on the day were themed into broad areas and then circulated to the attendees to rank in order of importance. These community activities identified the top ten priorities, as shown below, as being the most important areas for future research:

Aboriginal Health and Wellbeing

Children in Care

Disability

Education

Families

Health

Homelessness

Refugees

Alcohol and other drugs

Fetal Alcohol Spectrum Disorders

The community input has provided valuable insights about ‘what is important to them’ and informed the development of the proposal for this new cross-agency project. It also had a positive impact on the community member’s perception of, and support for, this potential new research.

Conclusion/ImplicationsThe 20 years’ experience gained by the WA Consumer and Community Health Research Network in Western Australia has led to the development of a range of methods for involving the community in linked data research. These methods enable us to clearly demonstrate benefits and value of consumer and community involvement.
Changes in Development Among Kindergarten Children in Ontario 2012-2015: Linking Developmental, Sociodemographic, and Policy Implementation Data
Authors: Webb Simon , Janus Magdalena , Duku Eric , Gaskin Ashley , Offord Amanda
Published: September 2018

IntroductionIn Ontario kindergarten children, measures of early child development (ECD) indicate worsening outcomes over the last two provincial measurements (2012-2015), particularly among indicators of early physical, emotional and social development. This is despite significant investments in early childhood in the province through the roll-out of universal full day kindergarten.

Objectives and ApproachOur objective is to uncover correlates of change in the measures of ECD using the Early Development Instrument (EDI) between 2012 and 2015, particularly in relation to the average home/neighbourhood environments of students where school-level outcomes declined. This analysis links individual EDI data in Ontario, with 2016 DA-level Canadian Census data aggregated to the school level. The EDI is a kindergarten teacher-completed questionnaire measuring school readiness across five domains of child development. The schools are classified into groups based on whether they experienced statistically meaningful change in the domains of the EDI over the observed timeframe.

ResultsThe changes observed at the provincial level were consistent with those observed at the school level. Developmental vulnerability increased overall, in the Physical Health and Well-being, Social Competence and Emotional Maturity domains. Vulnerability decreased in the Language and Cognitive Development and Communication Skills and General Knowledge domains. While the analyses are still ongoing, preliminary findings suggest that schools with a higher proportion of children from high immigrant, and high income neighbourhoods tended to improve more than other schools. These along with some other socioeconomic neighbourhood characteristics identify sub-groups of schools that tended to see more positive or negative change on average across the five domains. We will supplement these findings using the time of introduction of the free full-day kindergarten program in each school.

Conclusion/ImplicationsThe presentation breaks down recent trends in kindergarten school readiness to identify schools that did better or worse than average based on socioeconomic and demographic characteristics. The analysis will also incorporate the timing of the introduction of full-day kindergarten into each school, providing insight into the effects of the program.
Comparing two asthma diagnoses using a prospective cohort of young children
Authors: Omand Jessica , Maguire Jonathon , O'Connor Deborah , Parkin Patricia , Birken Catherine , Thorpe Kevin , Zhu Jingqin , To Teresa
Published: September 2018

IntroductionAsthma is the most common chronic illness of childhood and places a large burden on the health care system. Asthma prevalence is commonly measured in national surveys by questionnaire. In Ontario, the Ontario Asthma Surveillance Information System (OASIS) developed a validated health claims diagnosis algorithm using health administrative data.

Objectives and ApproachThe primary objective of this study was to measure the agreement between the health claims diagnosis algorithm (OASIS diagnosis algorithm) and questionnaire diagnosis (TARGet Kids! diagnosis) of asthma in children younger than 6 years of age. Secondary objectives were to identify concordant and discordant pairs, and to identify factors associated with disagreement.

A comparison study including 3368 children participating in the TARGet Kids! practice based research network between 2008 and 2013 in Toronto, Canada. OASIS diagnosis algorithm and TARGet Kids! diagnosis asthma cases were compared using kappa statistic, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

ResultsPrevalence of asthma was estimated to be 15% by the OASIS diagnosis algorithm and 7% by TARGet Kids! diagnosis. The Kappa statistic was 0.47 (95% CI: 0.42 – 0.51), sensitivity 82\%, specificity 90%, PPV 38% and NPV 98% for OASIS diagnosis algorithm using TARGet Kids! diagnosis as the criterion standard. There were 3011 concordant pairs (2820 true negatives and 191 true positives) and 357 discordant pairs (315 false positives and 42 false negatives). Statistically significant factors associated with false positives included: male sex, higher zBMI and history of allergy. No statistically significant factors associated with false negatives were identified.

Conclusion/ImplicationsOASIS diagnosis algorithm had high sensitivity, specificity, and NPV but low PPV relative to TARGet Kids! diagnosis of asthma. Although, the OASIS diagnosis may identify more asthma cases in young children, its diagnostic properties are similar in older children and it may be a useful tool for longitudinal asthma surveillance.
25-hydroxyvitamin D and health service utilization for asthma in early childhood
Authors: Omand Jessica , To Teresa , O'Connor Deborah , Parkin Patricia , Birken Catherine , Thorpe Kevin , Maguire Jonathon
Published: September 2018

IntroductionAsthma is the most common chronic illness of childhood and a common reason for hospital admission. Studies suggest that low vitamin D levels may be associated with health service utilization (HSU) for childhood asthma.

Objectives and ApproachThe primary objective was to determine if vitamin D serum levels in early childhood were associated with HSU for asthma including: a) total HSU, b) hospital admissions, c) emergency department visits and d) outpatient sick visits. Secondary objectives were to determine whether vitamin D supplementation in pregnancy or childhood were associated with HSU for asthma. Prospective cohort study of children participating in the TARGet Kids! practice based research network. HSU was determined by linking each child's provincial health insurance number to health administrative databases. Multivariable quasi Poisson and logistic regression were used to evaluate the associations.

Results2926 healthy children ages 0-6 years had 25-hydroxyvitamin D data available and were included in the primary analysis. Mean (IQR) 25-hydroxyvitmain D level was 84 nmol/L (65-98 nmol/L), 218 and 1267 children had 25-hydroxyvitamin D levels <50 nmol/L and <75 nmol/L, respectively. In the adjusted models, there were no associations between 25-hydroxyvitamin D (continuously or dichotomized at 50 and 75 nmol/L), vitamin D supplementation in pregnancy or childhood and HSU for asthma.

Conclusion/ImplicationsHigher vitamin D blood values do not appear to be associated with HSU for asthma in this population of healthy urban children.
The Shape of the Socioeconomic Gradient: Testing to Functional Form of the Relationship between Socioeconomic Status and Early Child Development
Authors: Webb Simon , Janus Magdalena , Duku Eric , Forer Barry , Minh Anita , Brownell Marni , Muhajarine Nazeem , Guhn Martin
Published: September 2018

IntroductionThe literature provides abundant evidence of socioeconomic gradients in health outcomes. However, it is unclear, and particularly understudied in early child development research, whether these observed gradients are linear, whether they diminish as socioeconomic status (SES) increases, and if they ultimately reverse in slope at the highest SES values.

Objectives and ApproachWe linked neighbourhood-level Census and Tax Filer data with Early Development Instrument (EDI) data across Canada. The EDI is a kindergarten teacher-completed measure of five domains of early child development. We used this linked database to statistically compare and choose the most appropriate functional form of the relationship between each of the EDI domains (dependent variables), and the Canadian Neighbourhoods and Early Child Development (CanNECD) study's SES index (predictor) in regression models. Model comparison approaches included: visual checks of lines fitted using Generalized Additive Models, Akaike and Bayesian Information Criterions, Ramsay’s RESET, J and Cox tests.

ResultsThe results indicate the optimal functional form of the gradient varies across domains of the EDI. The best model for the Physical Health and Well-Being domain was quadratic, suggesting there may be some reversal in slope at higher values of SES. The best models for the Social Competence and Language and Cognitive Development domains were logarithmic, indicating diminishing returns to SES but with no slope reversal. The best model for the Emotional Maturity domain was linear, suggesting the gradient was consistent across all values of SES. The best fit for the Communication Skills and General Knowledge domain was a cubic ‘S’ curve, suggesting the curve is positive and concave for lower levels of SES but curves upwards beyond a certain SES threshold.

Conclusion/ImplicationsThe results demonstrate the importance of examining functional forms when modeling socioeconomic gradients. Assuming linear relationships between SES and health outcomes (early child development, in this case) may distort and bias the true nature of the relationships, thus leading to misinterpretations, especially at the highest and lowest values of SES.
Exploring public attitudes towards data sharing and linkage in health and social care
Authors: Hobbs Jo , Tully Mary , Ali Iqra
Published: September 2018

IntroductionThe devolvement of health and social care in Greater Manchester, England provides the private and public sectors with a unique opportunity to build comprehensive information sharing agreements. Shared information governance is key to enabling the rapid sharing of data which will underpin our ability to radically transform population health.

Objectives and ApproachIn 2013 the UK Government introduced a data sharing opt-out programme called Care.data. This programme aimed to extract data at GP level and anonymise data which could then be shared amongst those inside and outside the NHS. This programme was greeted with widespread public mistrust and abandoned in 2016. Care.data demonstrated that public concerns can de-rail efforts to improve data sharing. The key objective for this piece of work was to use public engagement activities as a means of identifying and unpicking public concerns about data-linkage and sharing as part of wider efforts to establish a social license in health.

ResultsDiscursive responses were analysed using thematic analysis and word frequency analysis. Combining thematic analysis and word frequency analysis helped to unpack the data by facilitating the identification and perceived importance of broad themes and sub-themes.

To date, analysis has identified a number of ‘Global Themes’ and 'Sub-themes' which will need to be addressed before we can establish a social license in health and social care with the public:

Global Themes related to:

Trust/mistrust

Privacy and confidentiality/breaches of privacy and confidentiality

Sub-themes related to:

Security of systems

Rest of the world security

What a third party might do with health data

Data ownership

Health data being used for private and or commercial profit

How others perceive you

Access to future treatment

Conclusion/ImplicationsOur deliberative discussions indicated concerns across culture and ethnic groups that data-sharing and linkage might be used to ‘gate-keep’ future access to treatment. Given that congruent social licenses are built on legitimacy, credibility and trust further work is required to allay public fears regarding future access to treatment.
Incidence of First Abortions: Integration of Administrative and Survey Data within a Joint Cohort Life Table Model
Authors: Dutey-Magni Peter , Gilbert Ruth
Published: September 2018

IntroductionIntegration of administrative and survey data to address sources of error is a fast-growing area of research. This paper examines the case of abortion, where survey data are susceptible to self-report bias, while administrative data provide crude but comprehensive and relatively unbiased information.

Objectives and ApproachAlthough abortion is a common and legal procedure, information is lacking on the proportion of women having one or more abortions during their lifetime. A Bayesian joint cohort life table model estimates age-specific rates of incidence of a first abortion for cohorts of women born between 1936 and 2003 an residing in England and Wales. The model is fitted using (1) waves II and III of the British National Surveys of Sexual Attitudes and Lifestyles (NATSAL) and (2) administrative counts of first ever abortions published by the UK's Office for National Statistics and Department of Health.

ResultsModel parameters controlling for underreporting indicate that survey reports are plausible for abortions occurring before the age of 20 years. Beyond that age, the model shows a fast increasing propensity to underreport abortions depending on the age at which they occurred. Underreporting also appears to be higher in NATSAL III. The study produces corrected estimates of the overall lifetime prevalence of an abortion in England and Wales, which is higher than previously thought.

Conclusion/ImplicationsJoint modelling of survey and administrative data can provide robust statistics, while reducing the need for record linkage where it is not feasible or acceptable. This approach is relevant in other contexts to correct the bias of particular population datasets, when audit data exist (e.g. underascertained diagnoses/causes of death).
Using linked health data in international comparisons of infectious disease burden
Authors: Reeves Rachel
Published: September 2018

Linking population-level health databases – such as those on hospital admissions, GP consultations, prescriptions, maternal and perinatal data, and laboratory data – provides great opportunities to explore the epidemiology and burden of infectious diseases. Furthermore, comparing the epidemiology and burden of infectious diseases on an international scale is crucial in designing and implementing national and global prevention and control measures. However, substantial differences between countries in national health systems (including thresholds for hospital admission), as well as varying availability and quality of routinely collected data, can pose challenges when using linked population-level health databases to compare estimates of infectious disease burden between countries.

This session aims to highlight and discuss the opportunities and challenges of international comparisons of infectious disease burden using linked population-level health data. This session will facilitate discussion of the methodological, ethical and resource challenges when using linked health data to produce internationally comparable estimates of the burden of infectious diseases. We will use as an example the ongoing work of the REspiratory Syncytial virus Consortium in Europe (RESCEU) – a large-scale collaborative project producing evidence to inform policymaking and regulatory decisions on novel respiratory syncytial virus (RSV) vaccines and therapeutics. The RESCEU project involves at least seven European countries each using linked routinely collected health data to produce national estimates of the health and economic burden of RSV, by age and risk group, for comparison. The results will highlight target populations for future vaccines and therapeutics, and provide a baseline estimate of the pre-vaccine era burden of disease that can be used to measure future vaccine impact. We will share the challenges faced in the RESCEU project with regards to using linked health data in international comparative work. We will then discuss, with relevance to other ongoing or future projects, how these challenges may be overcome.

This session will generate ideas for procedures and tools for international comparative work using routinely collected data to investigate infectious diseases. This session will provide the opportunity to network with other researchers working in this area. We aim to facilitate the generation and dissemination of ideas for current and future projects, and therefore this session is likely to identify areas for potential future international collaborative work.
Data Linkage Methods in Manitoba
Authors: Turner Ken , Walld Randy , Derksen Shelley
Published: September 2018

IntroductionAt the Manitoba Centre for Health Policy (MCHP), we have been performing data linkage for over 25 years. Over time, the Manitoba Population Research Data Repository (MPRDR) has expanded to over 80 datasets. Data linkage methods are key to bringing all this data together for population-based research.

Objectives and ApproachThe presentation will include a detailed description of the individual steps involved in the data linkage process and provide information about the methods developed and knowledge gained over time at MCHP. We will present different scenarios linking health, education, social and justice data and the choices that are made prior to and during data linkage. The data linkage process and linkage methods, including data validation techniques, will be illustrated with examples from our work.

ResultsThe presentation will describe the different types of data we have in the MPRDR and illustrate how the data are processed in a de-identified manner so that privacy and confidentiality are maintained.

The presentation will provide details on the data linkage methods used, dependent on the type of data sources being linked. This involves identifying and describing a 5-step data linkage process, including:

pre-processing (gaining knowledge about the data and cleaning/standardization techniques);

searching for and selecting the appropriate linkage variables;

applying different linkage techniques (e.g.: deterministic, probabilistic, “fuzzy matching” and manual review) to the data,

“rules” for deciding when data linkage should occur, and

reporting and Interpreting linkage outcome metrics and quality.

Conclusion/ImplicationsOur ability to link different data sources provides the capacity to study questions and complex issues related to health, social, education and justice from a population perspective. The techniques and methods described in this presentation should be applicable to other organizations linking administrative data.
Record linkage of pharmacovigilance and registration databases: a study of biological medicines in Brazil
Authors: Soares Monica , Moreira Antonio , Osorio-de-Castro Claudia , Coeli Claudia
Published: September 2018

IntroductionBiologic medicines have revolutionized the treatment of many serious and chronic illnesses and they present important challenges for approval and post-market surveillance of drug safety. Pharmacovigilance is an important strategy for monitoring adverse drug events in the post-market. Drug registration is an essential element of medicine regulation.

Objectives and ApproachBrazilian Health Regulatory Agency, ANVISA, is responsible for drug registration and surveillance. In this work we describe the process of linkage of databases covering registration, post-approval changes, and pharmacovigilance of biological medicines in Brazil.

2.429,556 registration dossiers included in the comprehensive national drug registration database, DATAVISA, and 93,391 reports of adverse drug events in the pharmacovigilance database, NOTIVISA, were analyzed for completeness and non biologic dossiers were filtered out. Deterministic linkage technique was used to connect DATAVISA and NOTIVISA data.

ResultsOf the DATAVISA dossiers, 188,830 were registrations and 2,240,726 records were post-approval changes. After filtering out the non-biologic dossiers, 48,144 post-approval changes dossiers for biologic drugs were obtained. Aggregation of 48,144 post-approval biologic products dossiers resulted in 663 product-manufacturer pairs. For pharmacovigilance data, aggregation produced 5,874 pairs. Registration and post-approval changes merging from aggregated pairs resulted in 577 pairs. Trios with pharmacovigilance data resulted in 147 matches. These 147 pairs respond for 5.468 identified adverse drug events reports. Adverse drug events reports of biological medicines account for around 5,0 \% of NOTIVISA.

Conclusion/ImplicationsRegulatory actions should be implemented to stimulate adverse events reports of biological products. A single database with registration, post-approval changes and pharmacovigilance data was produced. Data linkage permitted analysis of biological medicines in the post-market and can provide important information to evaluate risk in drug development.
Improving the Coding Completeness of Hypertension in Inpatient Administrative Health Data Using Machine Learning Methods
Authors: D'Souza Adam , Liang Zhiyang , Williamson Tyler , Smith Tony , Quan Hude , Peng Mingkai
Published: September 2018

IntroductionThe Discharge Abstract Database (DAD) associates ICD-10-CA diagnosis codes with inpatient care episodes at acute-care facilities. Codes are assigned by human coders, based on chart review. Coding guidelines stipulate mandatory coding of major and fatal conditions but only optional coding of secondary conditions, which results in undercoding for many conditions.

Objectives and ApproachThis research evaluates machine learning approaches for identifying and completing records with missing codes, to improve data quality. The Alberta Hospital DAD for 2013-14 was used in this study. We assumed that the existing ICD-10-CA codes in the DAD are correct, and used them as training examples. Several ML classifiers, including logistic regression and random forest, were used to develop models to assess the coding probability, using existing codes and demographic information. 3300 chart-review records were used as the reference standard. We focused on hypertension-related codes. Validity of raw diagnosis codes in the DAD was used as the baseline.

ResultsA record is deemed to have a missing hypertension diagnosis code if the predicted probability is high, but without the diagnosis codes having been assigned by the coders. In the baseline, the original hypertension codes have high PPV (ranging from 0.902 for the age group 35-54 to 1.000 for the age group 18-34) but low sensitivity (ranging from 0.200 for the age group 18-34 to 0.565 for the age group 75+). The most successful models that we have tested so far have provided improvements of 2-6% in the sensitivity, while maintaining the PPV. More improvement is generally seen for the younger age groups. Initial experiments indicate greater improvements in sensitivity may be possible for other conditions, such as peptic ulcer disease and cerebrovascular disease.

Conclusion/ImplicationsMachine learning approaches can be useful and cost-effective for improving data quality in DAD. While the improvements in sensitivity relative to the baseline are modest at present, further experiments with different models and feature sets are warranted. Experiments with other conditions may also be fruitful.
Inferring sensitivity and specificity of phenotyping algorithms using positive and negative predictive value in validation study in observational health data
Authors: Peng Mingkai , Gini Rosa , Williamson Tyler
Published: September 2018

IntroductionIn observational health data, phenotyping algorithms are needed to process raw information into clinically relevant features. Validation studies traditionally estimate sensitivity and specificity by comparing the phenotyping algorithm with a reference standard on a population sample. There are challenges to conduct validation studies for conditions with low prevalence.

Objectives and ApproachWe propose a novel and efficient method for conducting validation studies to indirectly estimate the sensitivity and specificity. We simulated datasets with different levels of disease prevalence and phenotyping algorithms with different sensitivities and specificity. We applied both the traditional (direct) and new (indirect) method on simulated data to estimate the sensitivity and specificity and compare the performance of the two methods. We also designed a gate to exclude true negatives to improve study efficiency on conditions with low prevalence and sensitive analysis was conducted on the imperfect gate.

ResultsThe new (indirect) method provided better or comparable accuracy in estimating both sensitivity and specificity compared to the traditional (direct) method. Applying a gate enabled us to conduct validation study in conditions with very low prevalence. An imperfect gate results in the overestimation of sensitivity but has minimal effect on specificity.

Conclusion/ImplicationsThe new (indirect) method provides an alternative way to conduct validation studies in observational health data with improvement in estimating accuracy.
Welsh Government Flying Start Programme Evaluation Using Linked Data
Authors: Lowe Sarah , McGuinn Laura , Quintela Marcos , Player Luke
Published: September 2018

IntroductionFlying Start (FS) is the Welsh Government’s (WG) flagship Early Years programme for families with children aged less than 4 years of age. Running since 2006, the four entitlements are:

Free part-time childcare for 2-3 year olds

Enhanced Health Visiting

Parenting support

Speech, language, and communication support

Objectives and ApproachCurrently, while we know which areas in Wales are receiving FS support, individual-level data on which child received what entitlements is not available. This means that area-level outcomes can be used as proxy indicators but the individual impact of receiving FS support cannot be examined. This project describes the issues around collecting individual-level data in deprived Welsh regions, a pilot project to facilitate this collection and will report some emerging findings from the analysis of pilot data.

ResultsFollowing from previous studies funded by the ESRC and WG (e.g. Supporting People Data Linking Feasibility Study), a Dataflow Development Project (DDP) has been launched to install Secure Anonymised Information Linkage (SAIL) appliances into 6 pilot Local Authorities in Wales. The SAIL appliance technology will provide Local Authorities with the ability to link individual-level data within a Local Authority or between Local Authorities and to securely anonymise data into the SAIL Databank or ADRC-W.

The DDP will test acquiring the individual level FS data from pilot Local Authorities into SAIL. The project aims to evaluate FS by linking the FS cohort to a range of outcomes including health, education and social care. We will report emerging findings from the analysis of pilot data.

Conclusion/ImplicationsThere is grow interest in using linked administrative data to evaluate government initiatives, and mounting enthusiasm in Local Government. If successful, this model is likely to be adopted by related WG programmes; improving the evidence base, facilitating effective evaluation, and adding to the data available for re-use in Wales.
How do we enhance linked administrative data based chronic disease surveillance in Canada? Results of an environmental scan.
Authors: Duchen Raquel , Lix Lisa , Reimer Kim , Widdifield Jessica , Butt Debra , Smith Mark , Katz Alan , Bartholomew Sharon , Toews Jennette , McRae Louise , Jaakkimainen Liisa
Published: September 2018

IntroductionThe Canadian Chronic Disease Surveillance System (CCDSS) is a collaboration of provincial and territorial surveillance systems which generates estimates of chronic diseases using linked population-level administrative health databases and standard case definitions. We conducted an environmental scan of administrative data validation studies and identified opportunities for CCDSS case definition enhancement.

Objectives and ApproachThe purpose of this project is to develop a methodology for and conduct an environmental scan, identifying opportunities for enhancing the CCDSS. This multifaceted approach consists of the following elements: 1) key informant interviews and stakeholder consultations to identify new and existing priority conditions for updating/validating within the CCDSS, and new areas of conceptual and methodological relevance for administrative data disease surveillance, 2) a systematic literature review of PubMed, Ovid and Embase from 2013-2017 using MeSH terms and a librarian peer-reviewed search strategy, and 3) a review of the grey literature.

ResultsKey stakeholders identified the following priorities for validation work and/or case definition enhancement: diabetes, mood and anxiety disorders, schizophrenia, obesity, hypertension, chronic obstructive pulmonary disease, osteoarthritis, stroke, early-onset dementia, rheumatoid arthritis and gout. Scientific and grey literature reviews of validation work for these conditions examined the following concepts/methods: 1) evaluating validity of disease-specific case definitions over time, and in different ages, sub-populations and settings, 2) defining incidence versus prevalence using linked administrative data, 3) determining opportunities and constraints of using linked administrative data to conduct surveillance on diseases that are chronic versus episodic in nature and defining active versus lifetime prevalence, and 4) assessing the feasibility of using new sources of data for linkage to enhance case definition validity.

Conclusion/ImplicationsUtilization of linked administrative databases for chronic disease surveillance has expanded across many jurisdictions since the inception of the CCDSS. As disease estimates generated in this manner are increasingly being relied upon by policy makers working to enhance public health, the methodological opportunities and constraints identified here require consideration.
Public views and recommendations on the use of linked data for research: preliminary results from a public deliberation engagement
Authors: Teng Jack , McGrail Kim , Bentley Colene , Burgess Michael , O'Doherty Kieran
Published: September 2018

IntroductionThe use of linked data for research is increasing, including in complexity of requests. Rules around access to and use of data necessarily trade-off risks related to privacy to achieve social benefits. Including informed and civic-minded public recommendations that consider different perspectives on privacy and benefit will improve related policy.

Objectives and ApproachPopulation Data BC is conducting a deliberative public engagement regarding the use of complex linked data for research. Members of the public will be provided with written materials and hear speakers outlining considerations from multiple perspectives in data access and use, including benefits for health research, risks to privacy, and implications for disability and minority groups. Participants in the deliberation will then discuss questions about the use of linked data and ideas around principles for that use in small and large groups, and develop recommendations for data sharing policies.

ResultsWe will be sharing our preliminary analysis of the public deliberation results at the conference. The public deliberation encourages the participants to develop policy recommendations that respect diversity of perspectives while negotiating constructive advice. It asks the group to make recommendations and to identify and explore issues on which the group has persistent disagreement. We will discuss insights into how the public values the use of data linkage and under what conditions such use becomes problematic. For example, we are hoping to gain insight about how publics determine if a project is in the public interest, or conversely, how a project may pose unacceptable harm.

Conclusion/ImplicationsChanges in available data and increasing ability to link data makes it essential to include public views in systems of data access governance. Understanding the hopes and concerns of the public regarding the use of linked data for research will help develop data access regulations that reflect wide public interests.