scholarly journals Waving away waivers: an obligation to contribute to ‘herd knowledge’ for data linkage research?

2021 ◽  
pp. 174701612110583
Author(s):  
Owen M Bradfield
Keyword(s):  
Data Linkage ◽  
Ethics Committees ◽  
Health Data ◽  
Data Driven ◽  
Health Providers ◽  
Online Data ◽  
Routinely Collected Health Data ◽  
Privacy Risks ◽  
Digital Footprints ◽  
Research Efficiency

In today’s online data-driven world, people constantly shed data and deposit digital footprints. When individuals access health services, governments and health providers collect and store large volumes of health information about people that can later be retrieved, linked and analysed for research purposes. This can lead to new discoveries in medicine and healthcare. In addition, when securely stored and de-identified, the privacy risks are minimal and manageable. In many jurisdictions, ethics committees routinely waive the requirement for researchers to obtain consent from data subjects before using and linking these datasets in an effort to balance respect for individuals with research efficiency. In this paper, I explore the ethical justification for using routinely collected health data for research without consent. I conclude that, not only is this morally justified but also that data subjects have a moral obligation to contribute their data to such research, which would obviate the need for ethics committees to consider consent waivers. In justifying this argument, I look to the duty of easy rescue, distributive justice and draw analogies with vaccination ethics.

scholarly journals The RECORD reporting guidelines: meeting the methodological and ethical demands of transparency in research using routinely-collected health data

2016 ◽  
Vol Volume 8 ◽  
pp. 389-392 ◽  
Author(s):  
Stuart Nicholls ◽  
Sinead Langan ◽  
Henrik Toft Sørensen ◽  
Irene Petersen ◽  
Eric Benchimol
Keyword(s):  
Health Data ◽  
Reporting Guidelines ◽  
Routinely Collected Health Data

Occupational groups and ischaemic heart disease in New Zealand – a longitudinal linkage study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L.A Barnes ◽  
A Eng ◽  
M Corbin ◽  
H.J Denison ◽  
A t'Mannetje ◽  
...  
Keyword(s):  
Heart Disease ◽  
New Zealand ◽  
Ischaemic Heart Disease ◽  
Cox Regression ◽  
Health Data ◽  
Funding Source ◽  
Inverse Association ◽  
Occupational Groups ◽  
Routinely Collected Health Data ◽  
Machine Operators

Abstract Background/Introduction Occupation is a poorly characterised risk factor for cardiovascular disease (CVD), with females and minority populations particularly under-represented in research. There is also a lack of longitudinal studies using detailed health data that does not rely on self-reports. Purpose This study aimed to address these gaps by assessing the association between a range of occupational groups and ischaemic heart disease (IHD) in New Zealand (NZ), through linkage of population-based occupational surveys to routinely collected health data. Half of the study population were females and 40% were indigenous Māori (who comprise 15% of the total 4.8 million NZ population), which enabled sex and ethnicity-specific aspects of the relationship between occupation and IHD to be assessed. Methods Two probability-based sample surveys of the NZ adult population (New Zealand Workforce Survey (NZWS); 2004–2006; n=3003) and of the Māori population (NZWS Māori; 2009–2010; n=2107), for which detailed occupational histories and lifestyle factors were collected, were linked with routinely collected health data available through Statistics NZ. Cox regression was used to calculate hazard ratios (HR) for “ever-worked” in any one of nine major occupational groups, with “never worked” in that occupational group defined as the reference group. Analyses were controlled for age, deprivation and smoking, and stratified by sex and ethnicity. Results The strongest associations were found for “plant/machine operators and assemblers” and “elementary workers”, particularly among female Māori (HR 2.19, 95% CI 1.16–4.13 and HR 2.03, 1.07–3.82 respectively). In contrast, inverse associations with IHD across all groups were observed for “technicians and associate professionals”, which was significant for NZWS males (HR 0.52, 0.32–0.84). There were some sex and ethnic differences, particularly for “clerks”, where a positive association was found for NZWS males (HR 1.81, 1.19–2.74), whilst an inverse association was observed for Māori females (HR 0.42, 0.22–0.82). Duration analyses (≤2 years, 2–10 years and 10+ years) showed significant dose-response trends for “clerks” in NZWS males, and “plant/machine operators and assemblers” and “elementary workers” in Māori females. Further adjustments for other potential confounders such diabetes mellitus, hypertension and high cholesterol did not affect the results. Conclusion Associations between occupation and IHD differed significantly across occupational groups and between sexes and ethnicities, even within the same occupational groups. This suggests that results may not be generalised across these groups and occupational interventions to reduce IHD risk may therefore need different approaches depending on the population and specific groups of interest. Funding Acknowledgement Type of funding source: Other. Main funding source(s): Health Research Council (HRC) of New Zealand

Developing annotation solutions for online Data Driven Learning

ReCALL ◽  
2009 ◽  
Vol 21 (1) ◽  
pp. 55-75 ◽  
Author(s):  
Pascual Pérez-Paredes ◽  
Jose M. Alcaraz-Calero
Keyword(s):  
Corpus Linguistics ◽  
Language Teaching ◽  
Language Education ◽  
Data Driven ◽  
Online Data ◽  
Analysis And Design ◽  
Language Classroom ◽  
Youth Language ◽  
User Friendly

AbstractAlthough annotation is a widely-researched topic in Corpus Linguistics (CL), its potential role in Data Driven Learning (DDL) has not been addressed in depth by Foreign Language Teaching (FLT) practitioners. Furthermore, most of the research in the use of DDL methods pays little attention to annotation in the design and implementation of corpus-based/driven language teaching.In this paper, we set out to examine the process of development of SACODEYL Annotator, an application that seeks to assist SACODEYL system users in annotating XML multilingual corpora. First, we discuss the role of annotation in DDL and the dominating paradigm in general corpus applications. In the context of the language classroom, we argue that it is essential that corpora should be pedagogically motivated (Braun, 2005 and 2007a). Then, we move on to deal with the analysis and design stages of our annotation solution by illustrating its main features. Some of these include a user friendly hierarchical and extensible taxonomy tree to facilitate the learner-oriented annotation of the corpora; real-time graphics representation of the annotated corpus matching the XML TEI-compliant (Text Encoding Initiative) standard, as well as an intuitive management of the different data sections and associated metadata.SACODEYL (System Aided Compilation and Open Distribution of European Youth Language) is an EU funded MINERVA project which aims to develop an ICT-based system for the assisted compilation and open distribution of multimedia European teen talk in the context of language education. This research lays emphasis on the functionalities of the application within the SACODEYL context. However, our paper addresses similarly the needs of potential multimedia language corpus administrators in general on the lookout for powerful annotation assisting software. SACODEYL Annotator is free to use and can be downloaded from our website.

scholarly journals Linking child travel routes and routine health data

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Amy Mizen ◽  
Sarah Rodgers ◽  
Richard Fry ◽  
Ronan Lyons
Keyword(s):  
Large Scale ◽  
Data Linkage ◽  
Routine Data ◽  
Environmental Exposures ◽  
Health Data ◽  
Walking Distance ◽  
Complete Analysis ◽  
Natural Experiments ◽  
Older Children ◽  
Household Level

ABSTRACTObjectivesLinking routinely collected health and environment data can allow for large scale evaluations of how our environment impacts our health. Our data linkage approach advances previous research where residence-based environmental exposures were anonymously linked in the SAIL databank using Residential Anonymous Linking Fields (RALFs). The dose-response relationship between exposure to food and dietary intake has not been widely investigated. Previous research found conflicting views on whether increased environmental exposure to unhealthy food contributes to higher BMIs. This may have been due to different methodological approaches, including imprecise exposures, small numbers, and the use of self-reported BMIs. ApproachThis investigation calculated food exposure environments for routes from all homes to and from school. A Geographic Information System was used to calculate the environmental exposures along all potential routes up to a maximum age-appropriate walking distance from each school. Once within the SAIL databank we selected relevant routes using linked demographic and pupil datasets. To maintain privacy, the primary (doctoral) researcher generating the environmental exposures, did not have access to the final household-level exposure data in their identifiable form. The researcher automated their method so a second researcher could run the GIS analysis. Accuracy of modelled exposures will be compared with actual routes collected from GPS traces of children walking to school. ResultsRemoving access to the final identifiable household-level route exposures enabled the primary researcher to complete analysis on the combined household and individual-level data within the secure environment. The environmental exposures were linked with routine health data from the SAIL databank; including BMI as an indicator of obesity. BMI data for 4-5 year olds, and a sample of 1300 13-14 year olds were linked to associated environmental exposures. ConclusionDepending on modelled accuracy, a GIS and data linkage approach may allow the investigation of natural experiments and intervention evaluation at the scale of the total population. This is the first step towards anonymously modelling part of the daily exposure environment using routine data. A limitation is the lack of routinely collected BMI data for older children and teenagers an age when they are more likely to have the option to choose to buy food on the school route. This work will have many potential applications, including the delivery and evaluation of multiple school and workplace commuting interventions.

scholarly journals Planting the S.E.E.D.S of Indigenous Population Health Data Linkage

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Robyn K Rowe ◽  
Jennifer D Walker
Keyword(s):  
Population Health ◽  
Indigenous Peoples ◽  
Health Care Policy ◽  
Indigenous Population ◽  
Data Linkage ◽  
Indigenous Health ◽  
Population Data ◽  
Health Data ◽  
Indigenous Populations ◽  
Data Stewardship

IntroductionThe increasing accessibility of data through digitization and linkage has resulted in Indigenous and allied individuals, scholars, practitioners, and data users recognizing a need to advance ways that assert Indigenous sovereignty and governance within data environments. Advances are being talked about around the world for how Indigenous data is collected, used, stored, shared, linked, and analysed. Objectives and ApproachDuring the International Population Data Linkage Network Conference in September of 2018, two sessions were hosted and led by international collaborators that focused on regional Indigenous health data linkage. Notes, discussions, and artistic contributions gathered from the conference led to collaborative efforts to highlight the common approaches to Indigenous data linkage, as discussed internationally. This presentation will share the braided culmination of these discussions and offer S.E.E.D.S as a set of guiding Indigenous data linkage principles. ResultsS.E.E.D.S emerges as a living and expanding set of guiding principles that: 1) prioritizes Indigenous Peoples’ right to Self-determination; 2) makes space for Indigenous Peoples to Exercise sovereignty; 3) adheres to Ethical protocols; 4) acknowledges and respects Data stewardship and governance, and; 5) works to Support reconciliation between Indigenous Peoples and settler states. S.E.E.D.S aims to centre and advance Indigenous-driven population data linkage and research while weaving together common global approaches to Indigenous data linkage. Conclusion / ImplicationsEach of the five elements of S.E.E.D.S interweave and need to be enacted together to create a positive Indigenous data linkage environment. When implemented together, the primary goals of the S.E.E.D.S Principles is to guide positive Indigenous population health data linkage in an effort to create more meaningful research approaches through improved Indigenous-based research processes. The implementation of these principles can, in turn, lead to better measurements of health progress that are critical to enhancing health care policy and improving health and wellness outcomes for Indigenous populations.

scholarly journals Involving the Public in Data Linkage Research

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Mhairi Aitken ◽  
Annette Braunack-Mayer ◽  
Felicity Flack ◽  
Kimberlyn M McGrail ◽  
Michael Burgess ◽  
...  
Keyword(s):  
Public Engagement ◽  
Health Research ◽  
Consensus Statement ◽  
Data Linkage ◽  
Health Data ◽  
Advisory Council ◽  
Research Network ◽  
Plain Language ◽  
The Public ◽  
Data Intensive

Introduction“The Consensus Statement on Public Involvement and Engagement with Data-Intensive Health Research”, recent data breaches, and growing public awareness and controversy associated with secondary use of health data all highlight the need to understand what data sharing the public will support, under what circumstances, for what purposes and with whom. Objectives and ApproachThis symposium explores methods and findings from public engagement at all stages of data linkage research, beginning with short presentations (~6-8 minutes) on recent work: Mhairi Aitken: Consensus Statement - principles and an application using deliberative workshops to explore public expectations of public benefits from data-intensive health research Annette Braunack-Mayer/Felicity Flack: Surveys and citizens’ juries: Sharing government data with private industry Kim McGrail/Mike Burgess: Public deliberations on cross-sector data linkage, and combining public and private sources of data Alison Paprica: Plain language communication informed by Health Data Research Network Canada’s Public Advisory Council. Half the session will be spent interacting with the audience through live polling. The moderator will post a series of poll question such as “What is the most important thing for meaningful public engagement?” to prompt audience thinking on the topic. After the audience responses are revealed, panelists will share their own views about what they think is the best answer, and the main reason(s) behind their choice. The last 10-15 minutes of the session will be reserved for Q&A and dialogue with the audience. ResultsWe anticipate that this approach will surface emerging and tacit knowledge from presenters and the audience, and augment that through generative discussion. Conclusion / ImplicationsSession attendees will leave with a better understanding of the current state of knowledge and ways to talk about that understanding with other researchers, policy makers and the public.

scholarly journals Application of A Framework to Guide Policy on Healthcare Resource Allocation Decisions to Data Linkage Projects

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Ian Olver
Keyword(s):  
Resource Allocation ◽  
Data Linkage ◽  
Health Data ◽  
Decision Makers ◽  
Data Sets ◽  
Policy Decisions ◽  
The Public ◽  
Health Resource Allocation ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

IntroductionData linkage of population data sets often across jurisdictions or linking health data sets or health data with non-health data often involves balancing ethical principles such as privacy with beneficence as represented by the public good. Similar ethical dilemmas occur in health resource allocation decisions. The NHMRC have published a framework to guide policy on health resource allocation decisions that could be applied to ensure the justification of data linkage projects that is defensible as in the interest of the public good. Objectives and ApproachThe four main conditions for legitimacy of policy decisions about access to healthcare in a democracy with a public health system and limited resources wereexamined for their relevance to decisions about the use of public data and linking data sets. ResultsPublic policy decisions must be defensible and responsive to the interests of those affected. Decision-makers should articulate their reasoning and recommendations so that citizens can judge them. While the context of policy decisions will differ, their legitimacy depends upon (1) the transparency of the reasoning which should be free from conflicts of interest, the basis for decisions recorded and report widely, (2) the accountability of the decision-makers to the wider community, (3) the testability of the evidence used to inform the decision-making, which usually means that it will stand up to independent review and(4) the inclusive recognition of those the decision affects which often requires that the implications for disadvantaged groups are considered, even if they can’t always be accommodated. These conditions are interrelated but ensure that the good of society in general and not just specific dominant groups are accommodated. Conclusion / ImplicationsIt these principles are applied to decisions about data linkage projects they have clear applicability in society accepting data linkage projects having balanced the good against the ethical risks involved.

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