Exploring barriers and solutions in advancing cross-centre population data science

Jones, Kerina; Heys, Sharon; Daniels, Helen; Ford, David

doi:10.23889/ijpds.v4i1.1109

Cited by 3 publications

(8 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This proposition resonates with the San Francisco Declaration on Research Assessment 174 . Further recommendations of how this may be realised are described by Jones et al 71,175 , including the recommendations of DataCite Collaboration 176 . Additional guidance is provided by the Joint Declaration of Data Citation Principles (JDDCP) 177 .…”

Section: Incentivisation Of Data Contributors and Usersmentioning

confidence: 99%

Considerations for an integrated population health databank in Africa: lessons from global best practices

et al. 2021

View full text Add to dashboard Cite

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

show abstract

Section: Incentivisation Of Data Contributors and Usersmentioning

confidence: 99%

Considerations for an integrated population health databank in Africa: lessons from global best practices

et al. 2021

View full text Add to dashboard Cite

show abstract

“…A recent paper explored challenges associated with cross-centre or multi-jurisdictional research [ 5 ]. The challenges identified, consistent with previous literature [5, 8, 24], can be generalized into three categories: (i) data access challenges, (ii) analytical challenges (including data organization and comparability), and (iii) culture of academia and data governance challenges.…”

Section: Challenges Associated With Multi-jurisdictional Researchmentioning

confidence: 99%

“…Each jurisdiction is responsible for the administration of its health program, so there is no requirement that the data be collected or stored in a standard way across jurisdictions (and sometimes even within jurisdictions). This leads to differences in the way data are structured and variables are defined and in the availability of data across jurisdictions, all of which make it difficult to make appropriate comparisons [ 5 ]. For example, some jurisdictions limit the number of diagnoses collected in physician billing data which results in “missing” diagnoses, or payment policies might influence physicians to record more of some diagnoses than others; and differences in the number of digits collected for physician billing claims between provinces mean analysts need to develop creative ways to ensure consistency in outcomes [ 24 ].…”

Section: Challenges Associated With Multi-jurisdictional Researchmentioning

confidence: 99%

“…One approach to health research that has contributed significantly to health improvements over the past 30 years focuses on the use of population-level data routinely collected when individuals interact with the health system, which contain individual-level information on healthcare services use (e.g., hospitalizations, prescription drug dispensations) and demographics [3,4]. Using these data for multi-jurisdictional research, defined as research that accesses data from more than one jurisdiction, can overcome some of the limitations of single jurisdiction studies (e.g., studying rare conditions, or comparing health care system outcomes), but it does not come without challenges [5][6][7][8]. Addressing the challenges is acknowledged as a necessary step towards facilitating this type of research as various countries are developing the infrastructure to overcome them [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research

Dahl

Katz

McGrail

et al. 2020

IJPDS

View full text Add to dashboard Cite

Administrative health data is recognized for its value for conducting population-based research that has contributed to numerous improvements in health. In Canada, each province and territory is responsible for administering its own publicly funded health care program, which has resulted in multiple sets of administrative health data. Challenges to using these data within each of these jurisdictions have been identified, which are further amplified when the research involves more than one jurisdiction. The benefits to conducting multi-jurisdictional studies has been recognized by the Canadian Institutes of Health Research (CIHR), which issued a call in 2017 for proposals that address the challenges. The grant led to the creation of Health Data Research Network Canada (HDRN), with a vision is to establish a distributed network that facilitates and accelerates multi-jurisdictional research in Canada. HDRN received funding for seven years that will be used to support the objectives and activities of an initiative called the Strategy for Patient-Oriented Research Canadian Data Platform (SPOR-CDP). In this paper, we describe the challenges that researchers face while using, or considering using, administrative health data to conduct multi-jurisdictional research and the various ways that the SPOR-CDP will attempt to address them. Our objective is to assist other groups facing similar challenges associated with undertaking multi-jurisdictional research.

show abstract

“…Despite the increased availability of data and interest from funding bodies, there remain challenges for data access, storage and sharing, and difficulties in conducting crossnational research [2,[8][9][10][11]. In addition, accessing data from multiple data providers remains a challenge with different applications, requirements and governance across providers [9].…”

Section: Introductionmentioning

confidence: 99%

Identifying researcher learning needs to develop online training for UK researchers working with administrative data: CENTRIC training

Lugg-Widger

Munnery

Townson

et al. 2022

IJPDS

View full text Add to dashboard Cite

BackgroundThe use of administrative data in health and social science research continues to expand, with increased availability of data and interest from funders. Researchers, however, continue to experience delays in access, storage and sharing of administrative data. Training opportunities are limited and typically specific to individual data providers or focussed on the analytical aspects of working with administrative data. The CENTRIC study was funded by the Information Commissioners Office, with the aim of developing a broader training curriculum for researchers working with administrative data in the UK. MethodsA mixed-methods design informed curriculum content, including surveys with researchers, focus group discussions with data providers and workshops with members of the public. Researchers were identified from relevant administrative data networks and invited to participate in an online survey identifying training needs. Data providers were approached with a request to input to a face-to-face or online meeting with two members of the research team about their experiences of working with researchers. Data were analysed within the broad framework of the interview schedule, free text responses in the survey were analysed thematically. Results107 researchers responded to the online survey and four data providers participated in the focus groups. We identified five main themes, relating to research training needs for UK researchers working with administrative data: communication; timelines; changes & amendments; future-proofing applications; and, the availability of training and support. Data providers either provided additional evidence on these learning needs or ways to address identified challenges. Six modules were developed addressing these training needs. Quotes from the survey and focus groups are used anonymously in the online training modules. ConclusionThe CENTRIC online training curriculum was launched in September 2020 and is available, free of charge for UK researchers. CENTRIC specifically addresses commonly identified training needs of researchers working with administrative data.

show abstract

Exploring barriers and solutions in advancing cross-centre population data science

Cited by 3 publications

References 18 publications

Considerations for an integrated population health databank in Africa: lessons from global best practices

Considerations for an integrated population health databank in Africa: lessons from global best practices

The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research

Identifying researcher learning needs to develop online training for UK researchers working with administrative data: CENTRIC training

Contact Info

Product

Resources

About