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 Perspectives on Linkage Involving Indigenous data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Jennifer Walker ◽  
Bonnie Healy ◽  
Chyloe Healy ◽  
Tina Apsassin ◽  
William Wadsworth ◽  
...  
Keyword(s):  
Community Engagement ◽  
First Nations ◽  
Linked Data ◽  
Data Linkage ◽  
Indigenous Health ◽  
Health Centre ◽  
Population Data ◽  
Data Access ◽  
Indigenous Populations ◽  
Data Governance

Topic: Perspectives on Linkage Involving Indigenous dataIndigenous populations across the globe are reaffirming their sovereignty rights in the collection and use of Indigenous data. The Indigenous data sovereignty movement has been widely influential and can be unsettling for those who routinely use population-level linked data that include Indigenous identifiers. Ethical policies that stipulate community engagement for access, interpretation and dissemination of Indigenous data create an enabling environment through the critical process of negotiating and navigating data access in partnership with communities. This session will be designed to create space for leading Indigenous voices to set the tone for the discussion around Indigenous population data linkage. Objectives: To provide participants with an opportunity to build on the themes of Indigenous Data Sovereignty presented in the keynote session as they apply to diverse Indigenous populations. To explore approaches to the linkage of Indigenous-identified population data across four countries, including First Nations in three Canadian regions. To share practical applications of Indigenous data sovereignty on data linkage and analysis and discussion. To center Indigenous-driven data linkage and research. Facilitator:Jennifer Walker. Canada Research Chair in Indigenous Health, Laurentian University and Indigenous Lead, Institute for Clinical Evaluative Sciences. Collaborators: Alberta: Bonnie Healy, Tina Apsassin, Chyloe Healy and William Wadsworth (Alberta First Nations Information Governance Centre) Ontario: Carmen R. Jones (Chiefs of Ontario) and Jennifer Walker (Institute for Clinical Evaluative Sciences) British Columbia: Jeff Reading (Providence Health Centre) and Laurel Lemchuk-Favel (First Nations Health Authority) Australia: Raymond Lovett (Australian National University) Aotearoa / New Zealand: Donna Cormack (University of Otago) United States: Stephanie Rainie and Desi Rodriguez-Lonebear (University of Arizona) Session format: 90 minutesCollaborators will participate in a round-table introduction to the work they are doing. Collaborators will discuss the principles underlying their approaches to Indigenous data linkage as well as practical and concrete solutions to challenges. Questions to guide the discussion will be pre-determined by consensus among the collaborators and the themes will include: data governance, community engagement, Indigenous-led linkage and analysis of data, and decision-making regarding access to linked data. Other participants attending the session will be encouraged to listen and will have an opportunity to engage in the discussion and ask questions. Intended output or outcome:The key outcome of the session will be twofold. First, those actively working with Indigenous linked data will have an opportunity for an in-depth and meaningful dialogue about their work, which will promote international collaboration and sharing of ideas. Second, those with less experience and knowledge of the principles of Indigenous data sovereignty and their practical application will have an opportunity to listen to Indigenous people who are advancing the integration of Indigenous ways of knowing into data linkage and analysis. The output of the session will be a summary paper highlighting both the diversity and commonalities of approaches to Indigenous data linkage internationally. Areas where consensus exists, opportunities for collaboration, and challenges will be highlighted.

scholarly journals Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems

2021 ◽  
Vol 5 (4) ◽  
Author(s):  
Heather L. Rouse ◽  
Rebecca J. Bulotsky Shearer ◽  
Sydney S. Idzikowski ◽  
Amy Hawn Nelson ◽  
Mark Needle ◽  
...  
Keyword(s):  
Young Children ◽  
Administrative Data ◽  
Data Model ◽  
Data Science ◽  
Population Data ◽  
Well Being ◽  
Data Systems ◽  
Individual Level ◽  
The Individual ◽  
Conceptual Data

The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exponentially affected with unknown impacts on health, education, and social-emotional well-being. Integrated administrative data systems could be important tools for understanding these impacts. This article has three aims to guide research on the impacts of COVID-19 for this critical population using integrated data systems (IDS). First, it presents a conceptual data model informed by developmental-ecological theory and epidemiological frameworks to study young children. This data model presents five developmental resilience pathways (i.e. early learning, safe and nurturing families, health, housing, and financial/employment) that include direct and indirect influencers related to COVID-19 impacts and the contexts and community supports that can affect outcomes. Second, the article outlines administrative datasets with relevant indicators that are commonly collected, could be integrated at the individual level, and include relevant linkages between children and families to facilitate research using the conceptual data model. Third, this paper provides specific considerations for research using the conceptual data model that acknowledge the highly-localised political response to COVID-19 in the US. It concludes with a call to action for the population data science community to use and expand IDS capacities to better understand the intermediate and long-term impacts of this pandemic on young children.

scholarly journals Vasectomy reversal and prostate cancer risk: A multi-centre collaborative demonstration project of the Intentional Population Data Linkage Network

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
James Boyd ◽  
Sean Randall ◽  
Emma Fuller
Keyword(s):  
Prostate Cancer ◽  
United Kingdom ◽  
Cancer Risk ◽  
Linked Data ◽  
Data Linkage ◽  
Prostate Cancer Risk ◽  
Population Data ◽  
Demonstration Project ◽  
The United Kingdom ◽  
Vasectomy Reversal

This first collaborative demonstration project of the International Population Data Linkage Network (IPDLN) has recently been completed. This project collated data from five data linkage centres across Australia, the United Kingdom and Canada to investigate the effect of vasectomy reversal on prostate cancer risk in vasectomized men. We discuss the study and the challenges of organising and analysing multi-centre linked data studies.

scholarly journals Twenty Years of Data Linkage in The Australian Longitudinal Study on Women’s Health

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Colleen Loos ◽  
Gita Mishra ◽  
Annette Dobson ◽  
Leigh Tooth
Keyword(s):  
Longitudinal Study ◽  
Data Collection ◽  
Women’S Health ◽  
Women's Health ◽  
Linked Data ◽  
Data Linkage ◽  
Data Access ◽  
National Study ◽  
Australian Longitudinal Study ◽  
Data Collections

IntroductionLinked health record collections, when combined with large longitudinal surveys, are a rich research resource to inform policy development and clinical practice across multiple sectors. Objectives and ApproachThe Australian Longitudinal Study on Women’s Health (ALSWH) is a national study of over 57,000 women in four cohorts. Survey data collection commenced in 1996. Over the past 20 years, ALSWH has also established an extensive data linkage program. The aim of this poster is to provide an overview of ALSWH’s program of regularly up-dated linked data collections for use in parallel with on-going surveys, and to demonstrate how data are made widely available to research collaborators. ResultsALSWH surveys collect information on health conditions, ageing, reproductive characteristics, access to health services, lifestyle, and socio-demographic factors. Regularly updated linked national and state administrative data collections add information on health events, health outcomes, diagnoses, treatments, and patterns of service use. ALSWH’s national linked data collections, include Medicare Benefits Schedule, Pharmaceutical Benefits Scheme, the National Death Index, the Australian Cancer Database, and the National Aged Care Data Collection. State and Territory hospital collections include Admitted Patients, Emergency Department and Perinatal Data. There are also substudies, such as the Mothers and their Children’s Health Study (MatCH), which involves linkage to children’s educational records. ALSWH has an internal Data Access Committee along with systems and protocols to facilitate collaborative multi-sectoral research using de-identified linked data. Conclusion / ImplicationsAs a large scale Australian longitudinal multi-jurisdictional data linkage and sharing program, ALSWH is a useful model for anyone planning similar research.

scholarly journals Adult attachment, cultural orientation, and well-being in Greece

2020 ◽  
Vol 25 (1) ◽  
pp. 178
Author(s):  
Konstantinos Kafetsios ◽  
Evangelia Kateri
Keyword(s):  
Social Relations ◽  
Adult Attachment ◽  
Large Scale ◽  
Well Being ◽  
Secure Attachment ◽  
Anxious Attachment ◽  
Individual Level ◽  
Cultural Orientations ◽  
Self Construal ◽  
Different Cultures

Social bonds and relationships are important determinants of well-being and happiness. Peoples’ propensities for relating to individual and cultural levels can partially account for variations in well-being in different cultures. The present paper examined how adult attachment orientations, a seminal aspect of relating, and independent and interdependent self-construal, a cultural category of social relations, interrelate at an individual level to explain well-being in Greece. In a large-scale community study state secure attachment and independent and interdependent cultural orientations were all positively associated with well-being. As expected, the two relating constructs intersected so that higher interdependence was associated with higher anxiety and lower avoidance in line with expectations. Importantly, the interaction between interdependence and anxious attachment accounted for an additional part of the variance in well-being: participants higher in anxiety and interdependence had higher well-being whereas the inverse was true for participants higher in anxiety and independence. These results point to culture-specific patterns in how central relating schemas contribute to well-being[1]. 

scholarly journals Population Data Science: The science of data about people

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Kim McGrail ◽  
Kerina Jones
Keyword(s):  
Data Science ◽  
Data Linkage ◽  
Positive Impact ◽  
Population Data ◽  
Population Level ◽  
Multiple Sources ◽  
Science Field ◽  
Data Intensive ◽  
Collective Work ◽  
The Impact

IntroductionSocietal and individual benefits of data-intensive science are substantial but raise challenges of balancing individual privacy and public good, while building appropriate governance and socio-technical systems to support data-intensive science. We set out to define a new field of inquiry to move collective interests forward. Objectives and ApproachOur objectives were: 1. To create a concise definition of the emerging field of Population Data Science; 2. To highlight the characteristics and challenges of Population Data Science; 3. To differentiate Population Data Science from existing fields of data science and informatics; and 4. To discuss the implications and future opportunities for Population Data Science. Objectives 1 and 2 were met largely through International Population Data Linkage Network (IPDLN) member engagement, Objective 3 was evaluated via literature review, and Objective 4 was achieved through iterative and collective work on a peer-reviewed position paper. ResultsWe define Population Data Science succinctly as the science of data about people. It is related to, but distinct from, the fields of data science and informatics. A broader definition includes four characteristics of: i) data use for positive impact on individuals and populations; ii) bringing together and analyzing data from multiple sources; iii) identifying population-level insights; and iv) developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few individuals or organisations possess all of the requisite knowledge and skills comprising Population Data Science, so this is by nature a multi-disciplinary “team science” field. There is a need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. Conclusion/ImplicationsThese implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, will catalyze significant advances in our understanding of society, health, and human behavior and increase the impact of our research.

scholarly journals The International Population Data Linkage Network – Banff and Beyond

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
William A Ghali ◽  
Michael J Schull
Keyword(s):  
Executive Committee ◽  
Data Science ◽  
Data Linkage ◽  
South Australia ◽  
Population Data ◽  
Governance Structure ◽  
Social Program ◽  
Research Network ◽  
Foundational Work ◽  
Poster Presentations

We write to you, here in the pages of the International Journal of Population Data Science, for the second time in our capacity of co-directors of the International Population Data Linkage Network (IPDLN – www.ipdln.org). Time has certainly passed quickly since our first communication, where we introduced ourselves, and discussed planned initiatives for our tenure as leads of the IPDLN. Our network’s scientific community is steadily growing and thriving in an era of heightened interest around all things ‘data’. Indeed, there is great enthusiasm for all initiatives that explore ways of harnessing information systems and multisource data to enhance collective knowledge of health matters so that better decisions can be made by governments, system planners, providers, and patients. Never before have such initiatives attracted more attention. It is in this context of heightened interest and relevance around IPDLN and its science that we prepare to convene in Banff, Alberta, Canada for the 5th biennial IPDLN Conference – September 11-14. The conference, to be held at the inspiring Banff Centre (www.banffcentre.ca), is almost sold out, with only limited space remaining for late registrants. A tremendous program has been created through the oversight of Scientific Program co-chairs, Drs. Astrid Guttman and Hude Quan. A compelling roster of plenary lectures from Drs. Diane Watson, Jennifer Walker, and Osmar Zaïane is eagerly anticipated, as are topical panel discussions, an entertaining Science Slam session, and a terrific social program. These sessions will be surrounded by rich scientific oral and poster presentations arising from the more than 450 scientific abstracts submitted for review. We are so pleased to see this vibrant scientific engagement from the IPDLN membership and students, and look forward to hosting all delegates in Banff. The Banff conference will also be the venue at which we announce the new Directorship of the IPDLN for the next two years (2019 and 2020). As co-directors, we engaged with a number of individuals and organizations with interest in leading the IPDLN. In the end, two compelling Directorship applications were submitted – one a joint bid from Australia’s Population Health Research Network and the South Australia Northern Territory DataLink, and the other from the US-based Actionable Intelligence for Social Policy. IPDLN members submitted votes on these strong leadership bids through an online voting process, and while the excellence and appeal of both bids was apparent in strong voter support for both, a winning bid has been confirmed, and it will (as mentioned) be announced at the upcoming September conference. As we look forward to the Banff meeting with great anticipation, we are compelled to acknowledge the growing IPDLN legacy created by past directors. We are particularly indebted to our immediate predecessor, Dr. David Ford, and his team at Swansea University. Their work in hosting the 2016 IPDLN conference has been an inspiration to us in the planning of this year’s conference, and their crucial and foundational work in creating an IT platform for the IPDLN website, the membership database, and the new International Journal for Population Data Science has brought the IPDLN to a new level of organizational sophistication. Over the last 18 months, our co-directorship teams from the Institute for Clinical Evaluative Sciences in Ontario and the O’Brien Institute for Public Health at the University of Calgary have built on the foundation established by prior directors to update/enhance the IPDLN website and membership database. The IPDLN has more members than ever before representing a greater number of countries, and we have a more formalized governance structure with the creation of an Executive Committee that will include immediate past-Directors in order to better ensure continuity. A new Executive Committee will be elected by the IPDLN membership following the Banff conference. The waiting is almost over and IPDLN 2018 is upon us! Our scientific domain has never had the prominence or level of anticipation that we currently see. And the IPDLN has grown in its size, vibrancy and scientific scope. The opportunities for us are boundless, and the timing of our upcoming conference could not be better. We are honoured, with our respective organizations, to have had this opportunity to serve as co-directors over the past two years, and look forward to seeing many of you very soon. For those of you who are unable to travel to Canada’s Rocky Mountains this year, we look forward to connecting with you at a later time in the IPDLN’s continuing upward journey.

scholarly journals The Population Health Research Network - Population Data Centre Profile

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Felicity Flack ◽  
Merran Smith
Keyword(s):  
Population Health ◽  
Health Research ◽  
Data Linkage ◽  
Population Data ◽  
Data Access ◽  
Research Network ◽  
Data Centre ◽  
Wide Range ◽  
Unique Approach ◽  
Data Collections

The Population Health Research Network (PHRN) is an Australian data linkage infrastructure capable of securely and safely linking and integrating data collections from a wide range of sources. It is an example of a national data linkage infrastructure in a country with a federated system of government. This population data centre profile describes Australia’s unique approach to enabling access to linked data from single jurisdictions and from multiple jurisdictions. It covers the background to the establishment of the PHRN as well as information about how it operates today including operating models, governance, data, data linkage and data access. Some of the challenges of data linkage across jurisdictions are also discussed.

scholarly journals Population Data Centre Profile: SA NT DataLink (South Australia and Northern Territory)

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Matthias Schneider ◽  
Christopher Gordon Radbone ◽  
Stacy Ann Vasquez ◽  
Miroslav Palfy ◽  
Andrew Kristjan Stanley
Keyword(s):  
Service Use ◽  
Data Linkage ◽  
South Australia ◽  
Population Data ◽  
Data Access ◽  
Ethics Committees ◽  
Data Repository ◽  
Strict Adherence ◽  
Clinical Registries ◽  
Human Research Ethics

ApproachUniquely governed by a broad range of consortium partners, SA NT DataLink’s business model operates with flexibility to adapt to researcher priorities and government requirements. Its Data Linkage Unit routinely links data from over 50 sources with more than 57 million records on approximately 2.9 million individuals. It arguably provides the broadest range of linked data sources in Australia, focusing on administrative datasets and clinical registries from various health and human services domains. Operating in strict adherence with the separation principal, SA NT DataLink’s Data Integration Unit separately manages anonymised clinical and service use data in collaboration with the respective data custodians through the Custodian Controlled Data Repository, allowing approved analysts to efficiently access high quality linked anonymised data. To protect individual privacy throughout the process of data linkage and data provision, SA NT DataLink’s processes align with state, territory and federal privacy legislations. Operating consistently with National Health and Medical Research Council guidelines, linkage projects are subject to approvals by the relevant data custodians and approved Human Research Ethics Committees. Noteworthy OutputsSA NT DataLink has provided linkage services to over 160 data linkage projects, informing nationally significant research and policy initiatives, including initiatives to improve indigenous children’s hearing and child development. ConclusionTo respond to a changing data linkage landscape, SA NT DataLink is continuously reviewing and improving its systems, linkage processes and governance, addressing administrative, funding, data access, social licence and data linkage challenges and opportunities to meet increasing demand and new business developments.

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.

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