scholarly journals Evolving population data linkage services to transform large-scale biobanking services

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Katie Irvine ◽  
Vivienna Ong ◽  
Simon Cooper ◽  
Sarah Thackway
Keyword(s):  
Longitudinal Data ◽  
Health System ◽  
Administrative Data ◽  
Large Scale ◽  
Data Linkage ◽  
Service Providers ◽  
Population Data ◽  
Research Infrastructure ◽  
Fast Tracking ◽  
Linked Administrative Data

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.

scholarly journals Population Data BC: Supporting population data science in British Columbia

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Tavinder Kaur Ark ◽  
Sarah Kesselring ◽  
Brent Hills ◽  
Kim McGrail
Keyword(s):  
Linked Data ◽  
Large Scale ◽  
Data Science ◽  
Data Linkage ◽  
Population Data ◽  
Cost Effective ◽  
Data Access ◽  
Well Being ◽  
Third Party ◽  
Individual Level

BackgroundPopulation Data BC (PopData) was established as a multi-university data and education resourceto support training and education, data linkage, and access to individual level, de-identified data forresearch in a wide variety of areas including human and community development and well-being. ApproachA combination of deterministic and probabilistic linkage is conducted based on the quality andavailability of identifiers for data linkage. PopData utilizes a harmonized data request and approvalprocess for data stewards and researchers to increase efficiency and ease of access to linked data.Researchers access linked data through a secure research environment (SRE) that is equipped witha wide variety of tools for analysis. The SRE also allows for ongoing management and control ofdata. PopData continues to expand its data holdings and to evolve its services as well as governanceand data access process. DiscussionPopData has provided efficient and cost-effective access to linked data sets for research. After twodecades of learning, future planned developments for the organization include, but are not limitedto, policies to facilitate programs of research, access to reusable datasets, evaluation and use of newdata linkage techniques such as privacy preserving record linkage (PPRL). ConclusionPopData continues to maintain and grow the number and type of data holdings available for research.Its existing models support a number of large-scale research projects and demonstrate the benefitsof having a third-party data linkage and provisioning center for research purposes. Building furtherconnections with existing data holders and governing bodies will be important to ensure ongoingaccess to data and changes in policy exist to facilitate access for researchers.

scholarly journals Measuring Dementia Incidence Within A Cohort Of 267,153 Older Australians Using Routinely Collected Linked Administrative Data

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Heidi J Welberry ◽  
Henry Brodaty ◽  
Benjumin Hsu ◽  
Sebastiano Barbieri ◽  
Louisa R Jorm
Keyword(s):  
Administrative Data ◽  
Observational Studies ◽  
Data Linkage ◽  
Aged Care ◽  
Incidence Rates ◽  
Residential Aged Care ◽  
Care Needs ◽  
Dementia Incidence ◽  
Linked Administrative Data ◽  
Administrative Datasets

IntroductionThere is no gold standard method for monitoring dementia incidence in Australia. Routinely collected linked administrative data are increasingly being used to monitor endpoints in observational studies and clinical trials and could benefit dementia research. Objectives and ApproachThis study examines dementia incidence within different Australian administrative datasets and how characteristics vary across datasets for groups detected as having dementia. This was an observational data linkage study based on a prospective cohort of 267,153 people in New South Wales, Australia from the 45 and Up Study. Participants completed a survey in 2006-2009 and dementia was identified using linked pharmaceutical claims (provided by Services Australia), hospitalisations, assessments of aged care eligibility, care needs at entry to residential aged care and death certificates. Data linkage was undertaken by the Centre for Health Record Linkage (CHeReL) and the Australian Institute of Health and Welfare. Age-specific and age-standardised incidence rates, incidence rate ratios and survival from first dementia diagnosis were calculated. ResultsAge-standardised dementia incidence was 16.9 cases per 1000 person years (PY) for people aged 65 years and over. Estimates for those aged 80-89 years were closest to published incidence rates (91% of rates for high-income countries). Relationships with dementia incidence were inconsistent across datasets for characteristics including sex, relative socio-economic disadvantage, support network size, marital status, functional limitations and diabetes. Median survival from first pharmaceutical claim for an anti-dementia medicine was 3.7 years compared to 3.0 years from first aged care eligibility assessment, 2.0 years from a dementia-related hospitalisation and 1.8 years from first residential aged care needs assessment. Conclusion / ImplicationsPeople identified with dementia in different administrative datasets have different characteristics, reflecting the factors that drive interaction with specific services. Bias may be introduced if single data sources are used to identify dementia as an outcome in observational studies.

scholarly journals Challenges and Principles to guide the linkage of government administrative data: Experiences from the Tassie Kids project

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Joel Stafford
Keyword(s):  
Administrative Data ◽  
Data Linkage ◽  
Design Principles ◽  
Data Sets ◽  
Personal Privacy ◽  
Policy And Practice ◽  
Key Policy ◽  
Linked Administrative Data ◽  
Data Design

Background with rationale An overarching concern influencing models of data linkage for public good is the maintenance of personal privacy. This concern is at times so strong that it prevents or slows the progress of achieving worthwhile linked administrative datasets across allied government departments, and even between distinct units within a single department. Where linkage has succeeded it has generally produced data sets that, by design, are difficult or impossible to re-identify, therefore meeting the requirement to guard privacy at the costs of the resulting data’s value to government decision makers. Main Aim The main aim of this paper is to convey criteria to inform data linkage policy and practice in government that maintains a central role for privacy, but which can better deliver on the promise of high value data for policy. Methods/Approach This paper is informed by the Tassie Kids project, a longitudinal linked administrative data study using an embedded researcher model underway in Tasmania, Australia. Among other outcomes, the project was designed to assist allied government agencies to identify key policy leverage points across multiple services. Using the Tassie Kids project as a case study this paper asks why allied departments don’t routinely link administrative data. Several important linked administrative data design principles are drawn from discussion of this question. Results The paper explains the practice implications of these design principles relevant to policy analysis and information management units in government. Conclusion The paper concludes with the suggestion that high value linked administrative data is data that maximises its representation of the dynamic mechanisms that affect the outcomes desired by government, while simultaneously minimising the data’s distance from its point of origin.

scholarly journals Consent to Data Linkage in LSAC

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Dinusha Bandara ◽  
Michelle Silbert ◽  
Galina Daraganova
Keyword(s):  
Longitudinal Study ◽  
Longitudinal Data ◽  
Administrative Data ◽  
Policy Development ◽  
Data Linkage ◽  
Income Support ◽  
Parental Consent ◽  
Consent Rate ◽  
Study Child ◽  
Pharmaceutical Benefits Scheme

IntroductionLinking the existing longitudinal data assets with administrative datasets provide the opportunity to transform longitudinal data into valuable assets to inform research and policy development. Objectives and ApproachThis paper will focus on Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) data linkage landscape and consents which are invaluable for the development of evidence-based health-social-economic policies. ResultsLSAC is Australia’s first nationally-representative longitudinal study of child development. Since 2004, two cohorts of 5,000 children and their parents have been interviewed every two years (B (baby) cohort and K (kindergarten) cohort). Over the years, multiple data linkage has been undertaken based on either parental consent or study child consent. In 2004 parents were asked to consent on behalf of the study child to link Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS)/Repatriation Pharmaceutical Benefits Scheme (RPBS) and Australian Childhood Immunisation Register (ACIR) administrative data to LSAC. The consent rate was 93% was for MBS, PBS and ACIR. Nearly 90% of B cohort parents provided consent to link Australian Early Development Census (AEDC)/National Assessment Program – Literacy and Numeracy (NAPLAN) and 95.4% of K cohort parents provided consent to link NAPLAN.Then ten years later, children in the K cohort were asked to consent to MBS/PBS and income-support administrative data. The rates were 86.6% for MBS, 85.4% for PBS and 81.2% for income-support administrative data. Parental consent to link their MBS, PBS and income-support administrative data was also sought and these rates varied between 60% to 88%. Conclusion/ImplicationsThe discussion will focus on differences in consent rates by time of consent, consenting individual and type of administrative data to be linked. Challenges and considerations that researches should be aware of when designing the linkage consent methodology will also be discussed.

scholarly journals Deriving household composition using population-scale electronic health record data—A reproducible methodology

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248195
Author(s):  
Rhodri D. Johnson ◽  
Lucy J. Griffiths ◽  
Joe P. Hollinghurst ◽  
Ashley Akbari ◽  
Alexandra Lee ◽  
...  
Keyword(s):  
Administrative Data ◽  
Data Linkage ◽  
Population Level ◽  
Household Composition ◽  
Electronic Health Record Data ◽  
Household Level ◽  
Relative Age ◽  
Level Data ◽  
Address Data ◽  
Linked Administrative Data

Background Physical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data. Methods Using existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures. Results Two relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures. Conclusions Improved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual’s home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community.

scholarly journals Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249088
Author(s):  
Fadzai Chikwava ◽  
Reinie Cordier ◽  
Anna Ferrante ◽  
Melissa O’Donnell ◽  
Renée Speyer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Longitudinal Data ◽  
Administrative Data ◽  
Child Protection ◽  
Data Linkage ◽  
Open Science ◽  
Population Based ◽  
Science Framework ◽  
Meta Analyses ◽  
Almost All

Introduction Over the past decade there has been a marked growth in the use of linked population administrative data for child protection research. This is the first systematic review of studies to report on research design and statistical methods used where population-based administrative data is integrated with longitudinal data in child protection settings. Methods The systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. The electronic databases Medline (Ovid), PsycINFO, Embase, ERIC, and CINAHL were systematically searched in November 2019 to identify all the relevant studies. The protocol for this review was registered and published with Open Science Framework (Registration DOI: 10.17605/OSF.IO/96PX8) Results The review identified 30 studies reporting on child maltreatment, mental health, drug and alcohol abuse and education. The quality of almost all studies was strong, however the studies rated poorly on the reporting of data linkage methods. The statistical analysis methods described failed to take into account mediating factors which may have an indirect effect on the outcomes of interest and there was lack of utilisation of multi-level analysis. Conclusion We recommend reporting of data linkage processes through following recommended and standardised data linkage processes, which can be achieved through greater co-ordination among data providers and researchers.

scholarly journals COVID-19 and doctor emigration: the case of Ireland

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Niamh Humphries ◽  
Jennifer Creese ◽  
John-Paul Byrne ◽  
John Connell
Keyword(s):  
Health System ◽  
Large Scale ◽  
Qualitative Interviews ◽  
Snowball Sampling ◽  
Contact Potential ◽  
Work From Home ◽  
Travel Restrictions ◽  
Hospital Doctors ◽  
June July ◽  
Global Travel

Abstract Background Since the 2008 recession, Ireland has experienced large-scale doctor emigration. This paper seeks to ascertain whether (and how) the COVID-19 pandemic might disrupt or reinforce existing patterns of doctor emigration. Method This paper draws on qualitative interviews with 31 hospital doctors in Ireland, undertaken in June–July 2020. As the researchers were subject to a government mandated work-from-home order at that time, they utilised Twitter™ to contact potential respondents (snowball sampling); and conducted interviews via Zoom™ or telephone. Findings Two cohorts of doctors were identified; COVID Returners (N = 12) and COVID Would-be Emigrants (N = 19). COVID Returners are Irish-trained emigrant doctors who returned to Ireland in March 2020, just as global travel ground to a halt. They returned to be closer to home and in response to a pandemic-related recruitment call issued by the Irish government. COVID Would-be Emigrants are hospital doctors considering emigration. Some had experienced pandemic-related disruptions to their emigration plans as a result of travel restrictions and border closures. However, most of the drivers of emigration mentioned by respondents related to underlying problems in the Irish health system rather than to the pandemic, i.e. a culture of medical emigration, poor working conditions and the limited availability of posts in the Irish health system. Discussion/conclusion This paper illustrates how the pandemic intensified and reinforced, rather than radically altered, the dynamics of doctor emigration from Ireland. Ireland must begin to prioritise doctor retention and return by developing a coherent policy response to the underlying drivers of doctor emigration.

scholarly journals How Does Administrative Data Compare with Census Data for the Measurement of Internal Migration? The Case of Northern Ireland, 2001–2011

2021 ◽  
Author(s):  
Brian Foley ◽  
Tony Champion ◽  
Ian Shuttleworth
Keyword(s):  
Administrative Data ◽  
Internal Migration ◽  
Census Data ◽  
Local Population ◽  
Population Data ◽  
Population Estimates ◽  
Demographic Groups ◽  
Small Areas ◽  
Intercensal Period ◽  
Statistical Agencies

AbstractThe paper compares and contrasts internal migration measured by healthcard-based administrative data with census figures. This is useful because the collection of population data, its processing, and its dissemination by statistical agencies is becoming more reliant on administrative data. Statistical agencies already use healthcard data to make migration estimates and are increasingly confident about local population estimates from administrative sources. This analysis goes further than this work as it assesses how far healthcard data can produce reliable data products of the kind to which academics are accustomed. It does this by examining migration events versus transitions over a full intercensal period; population flows into and out of small areas; and the extent to which it produces microdata on migration equivalent to that in the census. It is shown that for most demographic groups and places healthcard data is an adequate substitute for census-based migration counts, the exceptions being for student households and younger people. However, census-like information is still needed to provide covariates for analysis and this will still be required whatever the future of the traditional census.

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