Dataset Information

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK.

ABSTRACT: Introduction:The International Methodology Consortium for Coded Health Information (IMeCCHI) is a collaboration of health services researchers who promote methodological advances in coded health information. The IMeCCHI-DATANETWORK initiative focuses on developing a multi-purpose distributed data infrastructure and common data model (CDM) to enable cross-border data sharing and international comparisons. Methods:IMeCCHI consortium partners from six different countries - Canada, Denmark, Italy, New Zealand, South Korea, and Switzerland - used a questionnaire to describe their original databases which differ in size, structure, content and coding systems. To standardize these data, they agreed on a CDM and mapped their population-based databases to meet the CDM specifications. At the end of this process, local data had a more homogenous content and structure, which made them syntactically and semantically interoperable. Data transformation was performed using a common data management software called TheMatrix. Results:The CDM encompasses four tables of structured data (person characteristics, hospitalizations, outpatient prescription medication and death), linked at the individual level through a person identifier. It can be used to answer research questions across countries using locally converted databases, which facilitates study replication in a distributed fashion. As a proof-of-concept study, an initial research question was addressed using an agreed protocol. Local data were transformed in csv files in the CDM structure and TheMatrix was tested to transform the standardized data from each partner into local analytical datasets. This allowed results to be shared between countries, whilst maintaining local control over each region's data. Conclusion:The IMeCCHI-DATANETWORK, a model of a distributed data network, demonstrated that it is feasible to analyze international data using standardized analytical methods that enable independent analyses by regions, without relocating datasets thereby protecting local confidentiality obligations. The distributed data infrastructure can produce results that can be generalized to several countries, while facilitating cross-border data sharing and international comparisons. Keywords:Common data model, international comparison, cross-border data sharing, interoperability, observational data.

SUBMITTER: Otero Varela L

PROVIDER: S-EPMC7473294 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK.

Otero Varela L L Le Pogam M-A MA Metcalfe A A Kristensen P K PK Hider P P Patel A A Kim H H Carlini E E Perego R R Gini R R

International journal of population data science 20200225 1

<h4>Introduction</h4>The International Methodology Consortium for Coded Health Information (IMeCCHI) is a collaboration of health services researchers who promote methodological advances in coded health information. The IMeCCHI-DATANETWORK initiative focuses on developing a multi-purpose distributed data infrastructure and common data model (CDM) to enable cross-border data sharing and international comparisons.<h4>Methods</h4>IMeCCHI consortium partners from six different countries - Canada, De ...[more]

PMID: 32935050

Similar Datasets

Project description:Compound (or chemical) databases are an invaluable resource for many scientific disciplines. Exposomics researchers need to find and identify relevant chemicals that cover the entirety of potential (chemical and other) exposures over entire lifetimes. This daunting task, with over 100 million chemicals in the largest chemical databases, coupled with broadly acknowledged knowledge gaps in these resources, leaves researchers faced with too much-yet not enough-information at the same time to perform comprehensive exposomics research. Furthermore, the improvements in analytical technologies and computational mass spectrometry workflows coupled with the rapid growth in databases and increasing demand for high throughput "big data" services from the research community present significant challenges for both data hosts and workflow developers. This article explores how to reduce candidate search spaces in non-target small molecule identification workflows, while increasing content usability in the context of environmental and exposomics analyses, so as to profit from the increasing size and information content of large compound databases, while increasing efficiency at the same time. In this article, these methods are explored using PubChem, the NORMAN Network Suspect List Exchange and the in silico fragmentation approach MetFrag. A subset of the PubChem database relevant for exposomics, PubChemLite, is presented as a database resource that can be (and has been) integrated into current workflows for high resolution mass spectrometry. Benchmarking datasets from earlier publications are used to show how experimental knowledge and existing datasets can be used to detect and fill gaps in compound databases to progressively improve large resources such as PubChem, and topic-specific subsets such as PubChemLite. PubChemLite is a living collection, updating as annotation content in PubChem is updated, and exported to allow direct integration into existing workflows such as MetFrag. The source code and files necessary to recreate or adjust this are jointly hosted between the research parties (see data availability statement). This effort shows that enhancing the FAIRness (Findability, Accessibility, Interoperability and Reusability) of open resources can mutually enhance several resources for whole community benefit. The authors explicitly welcome additional community input on ideas for future developments.

Project description:Tickborne diseases (TBDs) are increasingly prevalent in Illinois and the Upper Midwest region. People who work in occupations that require time outdoors in agricultural or natural settings, such as some Extension workers, are at risk of tick bites and TBDs. Additionally, Extension workers are often a primary source of information about ticks and TBDs in rural communities. However, there is limited information on the level of awareness about ticks and TBDs in the Extension community. The goals of this study were to sequentially i) determine the baseline awareness of Extension workers in Illinois about ticks and TBDs using a knowledge, attitudes, and practices (KAP) survey tool, ii) provide comprehensive training on ticks and TBDs to this demographic, and iii) measure the uptake of knowledge after the training intervention through a post-training survey. The study period was from June 2022 until May 2023. We received 233 pre-training and 93 paired post-training survey responses. Most survey respondents were Extension volunteers, identified as women, and were over 50 years old. Knowledge about ticks and TBDs varied. We identified several gaps in their current tick awareness, most importantly, in tick prevention measures, tick identification, and TBDs in general. TBD knowledge, attitude, and practice scores all significantly improved after training (p < 0.001), with a mean difference of 10.47, 1.49, and 2.64 points, respectively. Additionally, both Extension professionals (79.2 %) and Extension volunteers (66.7 %) were more likely to feel confident in engaging with their stakeholders on ticks and TBDs after participating in training. Poisson models revealed that higher attitude and practice scores and greater self-reported knowledge were the factors most significantly associated with higher TBD knowledge. We found that greater concern for ticks and TBD (attitudes) and adherence to science-based prevention and management methods (practices) were also associated with higher knowledge scores. To our knowledge, this is the first study in Illinois to capture Extension workers' awareness of ticks and TBDs. The results highlight Extension workers' interest in filling knowledge gaps through learning, and the importance of training Extension workers to disseminate reliable and updated information on ticks and TBDs to their constituents, a critical step in preventing TBDs.

Project description:BACKGROUND:Systems transformation for health promotion, involving engagement from multiple disciplines and levels of influence, requires an investment in partnership development. Integrated youth service is a collaborative model that brings organisations together to provide holistic care for youth. Frayme is an international knowledge translation network designed to support the uptake and scaling of integrated youth service. Social network analysis (SNA) is the study of relationships among social units and is useful to better understand how partners collaborate within a network to achieve major objectives. The purpose of this paper is to apply SNA to the Frayme network in order to (1) examine the level and strength of partnerships, (2) identify the strategies being employed to promote the main objectives and (3) apply the findings to current research in youth mental health and system transformation. METHODS:The PARTNER tool includes a validated survey and analysis software designed to examine partner interconnections. This tool was used to perform the SNA and 51 of the 75 partners completed the survey (14 researchers, 2 advisory groups and 35 organisations). A network map was created and descriptive frequencies were calculated. RESULTS:The overall network scores for the Frayme network were 20.6% for density, 81.5% for centralisation and 71.7% for overall trust. The Frayme secretariat received a 3.84 out of a possible 4 for value. In addition, the youth and family advisories each received a value score of 4 and all Leadership Team organisations received a score of 2.97 or above. CONCLUSIONS:The Frayme secretariat links many partners who would otherwise be disconnected and acts as a significant conduit for novel information. Frayme may have the opportunity to enhance value perceptions among broader network members by profiling individual organisations and the potential leveraging opportunities that might exist through their work. These findings increase understanding with respect to the mechanisms of network development and will be helpful to inform partnership development in the future. In addition, they contribute to the literature with respect to knowledge translation practice as well as the scaling of collaborative interventions within youth mental health.

Project description:BackgroundWhile next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community.MethodsA multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (clinical diagnostic, research or combination).ResultsOf 107 initiatives invited to participate, 59 responded (response rate = 55%). Whole exome sequencing (P = 0.03) and whole genome sequencing (P = 0.01) were utilized less frequently in clinical diagnostic than in research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common; however, other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonization were the lack of financial support (P < 0.01) and bioinformatics concerns (e.g. lack of interoperability) (P = 0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives (P = 0.01).ConclusionsThese results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need for greater harmonization of technical, ethical and data capture processes in cancer sample sequencing worldwide, in order to support effective and responsible data sharing for the benefit of patients.

Dataset Information

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK.

Publications

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets