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Medical Reference Services Quarterly 2023Spurred by the National Institute of Health mandating a data management and sharing plan as a requirement of grant funding, research data management has exploded in...
Spurred by the National Institute of Health mandating a data management and sharing plan as a requirement of grant funding, research data management has exploded in importance for librarians supporting researchers and research institutions. This editorial examines the role and direction of libraries in this process from several viewpoints. Key markers of success include collaboration, establishing new relationships, leveraging existing relationships, accessing multiple avenues of communication, and building niche expertise and cachè as a valued and trustworthy partner.
Topics: Humans; Data Management; Libraries, Medical; Communication; Librarians; Research Personnel
PubMed: 37459491
DOI: 10.1080/02763869.2023.2218776 -
Military Psychology : the Official... 2023This paper covers considerations in using criterion measures based on administrative data. We begin with a conceptual framework for understanding and evaluating...
This paper covers considerations in using criterion measures based on administrative data. We begin with a conceptual framework for understanding and evaluating administrative criterion measures as "objective" rather than (ratings-based) assessments of job performance. We then describe the associated advantages (e.g., availability) and disadvantages (e.g., contamination) of using administrative data for criterion-related validation purposes. Best practices in the use of administrative data for validation purposes, including procedures for (a) handling missing data, (b) performing data checks, and (c) reporting detailed decision rules so future researchers can replicate the analyses are also described. Finally, we discuss "modern data management" approaches for improving administrative data for supporting organizational decision-making.
PubMed: 37352447
DOI: 10.1080/08995605.2022.2063614 -
Burns : Journal of the International... Feb 2024While some countries collect burn clinical data as part of nonspecific trauma datasets, others have developed burn registries allowing for benchmarking of outcome and...
INTRODUCTION
While some countries collect burn clinical data as part of nonspecific trauma datasets, others have developed burn registries allowing for benchmarking of outcome and quality-of-care data. The objectives of this project are to characterize the current state of burn clinical data collection and analysis in Canada, and to explore the interest of Canadian burn centers in contributing to a nation-wide burn registry.
METHODS
A 23-item mixed methods survey was created and delivered via REDCap® to burn directors of 22 burn centers across Canada. Quantitative items were analyzed by means of descriptive statistics, and thematic analysis was used to explore qualitative data.
RESULTS
Sixteen (72 %) complete survey responses were received. All respondent units collect burn clinical data. Data are largely collected for quality improvement (69 %) and clinical research (50 %) purposes. Half of the institutions did not analyze their data, and a majority (67 %) did not benchmark their data against other datasets. The majority of respondents (93 %) demonstrated interest in contributing to a Canada-wide burn registry.
CONCLUSION
Although all respondent units are currently collecting burn clinical data, there is an opportunity to improve data analysis, benchmarking, and knowledge translation. Most centers demonstrated interest in contributing to a novel Canadian burn registry.
Topics: Humans; Data Management; Canada; Burns; Burn Units; Quality Improvement; Registries
PubMed: 37827939
DOI: 10.1016/j.burns.2023.07.003 -
Scientific Data Jun 2024The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in...
The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data.
Topics: Biomedical Research; Data Management; Information Dissemination
PubMed: 38871749
DOI: 10.1038/s41597-024-03449-z -
Reproductive Biomedicine Online Nov 2023The Internet of Things (IoT) is a network connecting physical objects with sensors, software and internet connectivity for data exchange. Integrating the IoT with... (Review)
Review
The Internet of Things (IoT) is a network connecting physical objects with sensors, software and internet connectivity for data exchange. Integrating the IoT with medical devices shows promise in healthcare, particularly in IVF laboratories. By leveraging telecommunications, cybersecurity, data management and intelligent systems, the IoT can enable a data-driven laboratory with automation, improved conditions, personalized treatment and efficient workflows. The integration of 5G technology ensures fast and reliable connectivity for real-time data transmission, while blockchain technology secures patient data. Fog computing reduces latency and enables real-time analytics. Microelectromechanical systems enable wearable IoT and miniaturized monitoring devices for tracking IVF processes. However, challenges such as security risks and network issues must be addressed through cybersecurity measures and networking advancements. Clinical embryologists should maintain their expertise and knowledge for safety and oversight, even with IoT in the IVF laboratory.
Topics: Humans; Internet of Things; Internet; Automation; Laboratories; Reproduction
PubMed: 37757612
DOI: 10.1016/j.rbmo.2023.103338 -
NEJM Evidence Aug 2023BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life,...
BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)–derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis. The model used baseline data to provide a binary output that a given patient will likely benefit from ADT or not. After the model was locked, validation was performed using data from NRG Oncology/Radiation Therapy Oncology Group (RTOG) 9408 (n=1594), a trial that randomly assigned men to radiotherapy plus or minus 4 months of ADT. Fine–Gray regression and restricted mean survival times were used to assess the interaction between treatment and the predictive model and within predictive model–positive, i.e., benefited from ADT, and –negative subgroup treatment effects. RESULTS: Overall, in the NRG/RTOG 9408 validation cohort (14.9 years of median follow-up), ADT significantly improved time to distant metastasis. Of these enrolled patients, 543 (34%) were model positive, and ADT significantly reduced the risk of distant metastasis compared with radiotherapy alone. Of 1051 patients who were model negative, ADT did not provide benefit. CONCLUSIONS: Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT. (Supported by a grant [U10CA180822] from NRG Oncology Statistical and Data Management Center, a grant [UG1CA189867] from NCI Community Oncology Research Program, a grant [U10CA180868] from NRG Oncology Operations, and a grant [U24CA196067] from NRG Specimen Bank from the National Cancer Institute and by Artera, Inc. ClinicalTrials.gov numbers NCT00767286, NCT00002597, NCT00769548, NCT00005044, and NCT00033631.)
Topics: Male; Humans; Prostatic Neoplasms; Androgen Antagonists; Prostate-Specific Antigen; Artificial Intelligence; Hormones
PubMed: 38320143
DOI: 10.1056/EVIDoa2300023 -
Methods in Molecular Biology (Clifton,... 2024Flapjack presents a valuable solution for addressing challenges in the Design, Build, Test, Learn (DBTL) cycle of engineering synthetic genetic circuits. This platform... (Review)
Review
Flapjack presents a valuable solution for addressing challenges in the Design, Build, Test, Learn (DBTL) cycle of engineering synthetic genetic circuits. This platform provides a comprehensive suite of features for managing, analyzing, and visualizing kinetic gene expression data and associated metadata. By utilizing the Flapjack platform, researchers can effectively integrate the test phase with the build and learn phases, facilitating the characterization and optimization of genetic circuits. With its user-friendly interface and compatibility with external software, the Flapjack platform offers a practical tool for advancing synthetic biology research.This chapter provides an overview of the data model employed in Flapjack and its hierarchical structure, which aligns with the typical steps involved in conducting experiments and facilitating intuitive data management for users. Additionally, this chapter offers a detailed description of the user interface, guiding readers through accessing Flapjack, navigating its sections, performing essential tasks such as uploading data and creating plots, and accessing the platform through the pyFlapjack Python package.
Topics: Data Management; Gene Regulatory Networks; Software; Synthetic Biology
PubMed: 38468101
DOI: 10.1007/978-1-0716-3658-9_23 -
Ophthalmic Epidemiology Dec 2023Population-based prevalence surveys are essential for decision-making on interventions to achieve trachoma elimination as a public health problem. This paper outlines...
PURPOSE
Population-based prevalence surveys are essential for decision-making on interventions to achieve trachoma elimination as a public health problem. This paper outlines the methodologies of Tropical Data, which supports work to undertake those surveys.
METHODS
Tropical Data is a consortium of partners that supports health ministries worldwide to conduct globally standardised prevalence surveys that conform to World Health Organization recommendations. Founding principles are health ministry ownership, partnership and collaboration, and quality assurance and quality control at every step of the survey process. Support covers survey planning, survey design, training, electronic data collection and fieldwork, and data management, analysis and dissemination. Methods are adapted to meet local context and needs. Customisations, operational research and integration of other diseases into routine trachoma surveys have also been supported.
RESULTS
Between 29 February 2016 and 24 April 2023, 3373 trachoma surveys across 50 countries have been supported, resulting in 10,818,502 people being examined for trachoma.
CONCLUSION
This health ministry-led, standardised approach, with support from the start to the end of the survey process, has helped all trachoma elimination stakeholders to know where interventions are needed, where interventions can be stopped, and when elimination as a public health problem has been achieved. Flexibility to meet specific country contexts, adaptation to changes in global guidance and adjustments in response to user feedback have facilitated innovation in evidence-based methodologies, and supported health ministries to strive for global disease control targets.
Topics: Humans; Infant; Trachoma; Prevalence; Public Health; Data Management; World Health Organization
PubMed: 38085791
DOI: 10.1080/09286586.2023.2249546 -
The Journal of Privacy and... Dec 2023Many organizations across the world that manage restricted data have adapted the Five Safes framework (safe data, safe projects, safe people, safe setting, safe output)...
Many organizations across the world that manage restricted data have adapted the Five Safes framework (safe data, safe projects, safe people, safe setting, safe output) for their management of restricted and confidential data. While the Five Safes have been well integrated throughout the data life cycle, organizations encounter several challenges with regard to safe data management. In this paper, we review current practices for restricted data management, and discuss challenges and future directions. We focus on data use agreements, disclosure risk review, and training. In the future, organizations managing restricted data may need proactively to take into consideration reducing inequalities in access to scientific data, preventing unethical use of data, and managing various types of data.
PubMed: 38515607
DOI: 10.29012/jpc.844 -
Methods in Molecular Biology (Clifton,... 2024This chapter discusses the challenges and requirements of modern Research Data Management (RDM), particularly for biomedical applications in the context of...
This chapter discusses the challenges and requirements of modern Research Data Management (RDM), particularly for biomedical applications in the context of high-performance computing (HPC). The FAIR data principles (Findable, Accessible, Interoperable, Reusable) are of special importance. Data formats, publication platforms, annotation schemata, automated data management and staging, the data infrastructure in HPC centers, file transfer and staging methods in HPC, and the EUDAT components are discussed. Tools and approaches for automated data movement and replication in cross-center workflows are explained, as well as the development of ontologies for structuring and quality-checking of metadata in computational biomedicine. The CompBioMed project is used as a real-world example of implementing these principles and tools in practice. The LEXIS project has built a workflow-execution and data management platform that follows the paradigm of HPC-Cloud convergence for demanding Big Data applications. It is used for orchestrating workflows with YORC, utilizing the data documentation initiative (DDI) and distributed computing resources (DCI). The platform is accessed by a user-friendly LEXIS portal for workflow and data management, making HPC and Cloud Computing significantly more accessible. Checkpointing, duplicate runs, and spare images of the data are used to create resilient workflows. The CompBioMed project is completing the implementation of such a workflow, using data replication and brokering, which will enable urgent computing on exascale platforms.
Topics: Data Management; Big Data; Cloud Computing; Documentation; Movement
PubMed: 37702950
DOI: 10.1007/978-1-0716-3449-3_18