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The National Institutes of Health (NIH) Policy for Data Management and Sharing (DMS Policy) recognizes the NIH's role as a key steward of United States biomedical research and information and seeks to enhance that stewardship through systematic recommendations for the preservation and sharing of research data generated by funded projects. The policy is effective as of January 2023. The recommendations include a requirement for the submission of a Data Management and Sharing Plan (DMSP) with funding applications, and while no strict template was provided, the NIH has released supplemental draft guidance on elements to consider when developing a plan. This article provides 10 key recommendations for creating a DMSP that is both maximally compliant and effective.
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Investigación Biomédica , Manejo de Datos , National Institutes of Health (U.S.) , Estados UnidosRESUMEN
Objective: The paper provides a review of current practices related to evaluation support services reported by seven biomedical and research libraries. Methods: A group of seven libraries from the United States and Canada described their experiences with establishing evaluation support services at their libraries. A questionnaire was distributed among the libraries to elicit information as to program development, service and staffing models, campus partnerships, training, products such as tools and reports, and resources used for evaluation support services. The libraries also reported interesting projects, lessons learned, and future plans. Results: The seven libraries profiled in this paper report a variety of service models in providing evaluation support services to meet the needs of campus stakeholders. The service models range from research center cores, partnerships with research groups, and library programs with staff dedicated to evaluation support services. A variety of products and services were described such as an automated tool to develop rank-based metrics, consultation on appropriate metrics to use for evaluation, customized publication and citation reports, resource guides, classes and training, and others. Implementing these services has allowed the libraries to expand their roles on campus and to contribute more directly to the research missions of their institutions. Conclusions: Libraries can leverage a variety of evaluation support services as an opportunity to successfully meet an array of challenges confronting the biomedical research community, including robust efforts to report and demonstrate tangible and meaningful outcomes of biomedical research and clinical care. These services represent a transformative direction that can be emulated by other biomedical and research libraries.
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Investigación Biomédica/organización & administración , Comunicación Interdisciplinaria , Bibliotecas Médicas/organización & administración , Servicios Técnicos de Biblioteca/organización & administración , Canadá , Humanos , Bibliotecólogos , Servicios de Biblioteca/organización & administración , Encuestas de Bibliotecas , Estados UnidosRESUMEN
The DigitalHub scholarly repository was developed and launched at the Galter Health Sciences Library for the Feinberg School of Medicine and the greater Northwestern Medicine community. The repository was designed to allow scholars the ability to create, share, and preserve a range of citable digital outputs. This article traces the evolution of DigitalHub's development and engagement activities, highlighting project challenges, innovations, success stories, and the team-based approach that was employed to successfully achieve project goals.
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Acceso a la Información , Internet , Bibliotecas Médicas , Vocabulario Controlado , Educación Médica , Retroalimentación , Integración de SistemasRESUMEN
BACKGROUND: Two new directors were each charged by their institutions to catalyze transformational change in their libraries and to develop dynamic and evolving information ecosystems ready for the information challenges of the future. The directors approached this transformational change using a strategic, forward-looking approach. RESULTS: This paper presents examples of actions that served as catalysts for change at the two libraries using Kotter's Eight Steps of Change as a framework. Small and large changes are critical for successfully transforming library services, resources, and personnel. CONCLUSIONS: Libraries are faced with incredible pressure to adapt to meet emerging and intensifying information needs on today's academic medical campuses. These pressures offer an opportunity for libraries to accelerate their evolution at the micro and macro levels. This commentary reports the expansion of new services and areas of support, enhancement of professional visibility of the libraries on their campuses, and overall, a more positive and productive environment at the respective institutions.
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Bibliotecas Médicas/tendencias , Servicios de Biblioteca/tendenciasAsunto(s)
Relaciones Comunidad-Institución , Educación en Salud/organización & administración , Equidad en Salud/organización & administración , Bibliotecas/organización & administración , Universidades/organización & administración , Promoción de la Salud/organización & administración , Humanos , Características de la Residencia , Factores Socioeconómicos , Estados UnidosRESUMEN
Group authorship (also known as corporate authorship, team authorship, consortium authorship) refers to attribution practices that use the name of a collective (be it team, group, project, corporation, or consortium) in the authorship byline. Data shows that group authorships are on the rise but thus far, in scholarly discussions about authorship, they have not gained much specific attention. Group authorship can minimize tensions within the group about authorship order and the criteria used for inclusion/exclusion of individual authors. However, current use of group authorships has drawbacks, such as ethical challenges associated with the attribution of credit and responsibilities, legal challenges regarding how copyrights are handled, and technical challenges related to the lack of persistent identifiers (PIDs), such as ORCID, for groups. We offer two recommendations: 1) Journals should develop and share context-specific and unambiguous guidelines for group authorship, for which they can use the four baseline requirements offered in this paper; 2) Using persistent identifiers for groups and consistent reporting of members' contributions should be facilitated through devising PIDs for groups and linking these to the ORCIDs of their individual contributors and the Digital Object Identifier (DOI) of the published item.
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Introduction: The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare. Methods: We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare. We built bulk-natural language processing pipelines to extract structured information from clinical notes and stored them in common data models. We developed multimodal AI/machine learning (ML) tools and tutorials to enrich the toolbox of the multidisciplinary workforce to analyze multimodal healthcare data. We have created a fertile ground to cross-pollinate clinicians and AI scientists and train the next generation of AI health workforce to collaborate effectively. Results: Our work has democratized access to unstructured health information, AI/ML tools and resources for healthcare, and collaborative education resources. From 2017 to 2022, this has enabled studies in multiple clinical specialties resulting in 68 peer-reviewed publications. In 2022, our cross-discipline efforts converged and institutionalized into the Center for Collaborative AI in Healthcare. Conclusions: Our Collaborative AI in Healthcare initiatives has created valuable educational and practical resources. They have enabled more clinicians, scientists, and hospital administrators to successfully apply AI methods in their daily research and practice, develop closer collaborations, and advanced the institution-level learning health system.
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Contributor Role Ontologies and Taxonomies (CROTs) provide a standard list of roles to specify individual contributions to research. CROTs most common application has been their inclusion alongside author bylines in scholarly publications. With the recent uptake of CROTs among publishers -particularly the Contributor Role Taxonomy (CRediT)- some have anticipated a positive impact on ethical issues regarding the attribution of credit and responsibilities, but others have voiced concerns about CROTs shortcomings and ways they could be misunderstood or have unintended consequences. Since these discussions have never been consolidated, this review collated and explored published viewpoints about the ethics of CROTs. After searching Ovid Medline, Scopus, Web of Science, and Google Scholar, 30 papers met the inclusion criteria and were analyzed. We identified eight themes and 20 specific issues related to the ethics of CROTs and provided four recommendations for CROT developers, custodians, or others seeking to use CROTs in their workflows, policy and practice: 1) Compile comprehensive instructions that explain how CROTs should be used; 2) Improve the coherence of used terms, 3) Translate roles in languages other than English, 4) Communicate a clear vision about future development plans and be transparent about CROTs' strengths and weaknesses. We conclude that CROTs are not the panacea for unethical attributions and should be complemented with initiatives that support social and infrastructural transformation of scholarly publications.
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Introduction: Enterprise data warehouses (EDWs) serve as foundational infrastructure in a modern learning health system, housing clinical and other system-wide data and making it available for research, strategic, and quality improvement purposes. Building on a longstanding partnership between Northwestern University's Galter Health Sciences Library and the Northwestern Medicine Enterprise Data Warehouse (NMEDW), an end-to-end clinical research data management (cRDM) program was created to enhance clinical data workforce capacity and further expand related library-based services for the campus. Methods: The training program covers topics such as clinical database architecture, clinical coding standards, and translation of research questions into queries for proper data extraction. Here we describe this program, including partners and motivations, technical and social components, integration of FAIR principles into clinical data research workflows, and the long-term implications for this work to serve as a blueprint of best practice workflows for clinical research to support library and EDW partnerships at other institutions. Results: This training program has enhanced the partnership between our institution's health sciences library and clinical data warehouse to provide support services for researchers, resulting in more efficient training workflows. Through instruction on best practices for preserving and sharing outputs, researchers are given the tools to improve the reproducibility and reusability of their work, which has positive effects for the researchers as well as for the university. All training resources have been made publicly available so that those who support this critical need at other institutions can build on our efforts. Conclusions: Library-based partnerships to support training and consultation offer an important vehicle for clinical data science capacity building in learning health systems. The cRDM program launched by Galter Library and the NMEDW is an example of this type of partnership and builds on a strong foundation of past collaboration, expanding the scope of clinical data support services and training on campus.
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COVID-19 reinforced the need for effective leadership and administration within Clinical and Translational Science Award (CTSA) program hubs in response to a public health crisis. The speed, scale, and persistent evolution of the pandemic forced CTSA hubs to act quickly and remain nimble. The switch to virtual environments paired with supporting program operations, while ensuring the safety and well-being of their team, highlight the critical support role provided by leadership and administration. The pandemic also illustrated the value of emergency planning in supporting organizations' ability to quickly pivot and adapt. Lessons learned from the pandemic and from other cases of adaptive capacity and preparedness can aid program hubs in promoting and sustaining the overall capabilities of their organizations to prepare for future events.
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Objective ChatGPT is the first large language model (LLM) to reach a large, mainstream audience. Its rapid adoption and exploration by the population at large has sparked a wide range of discussions regarding its acceptable and optimal integration in different areas. In a hybrid (virtual and in-person) panel discussion event, we examined various perspectives regarding the use of ChatGPT in education, research, and healthcare. Materials and Methods We surveyed in-person and online attendees using an audience interaction platform (Slido). We quantitatively analyzed received responses on questions about the use of ChatGPT in various contexts. We compared pairwise categorical groups with Fisher's Exact. Furthermore, we used qualitative methods to analyze and code discussions. Results We received 420 responses from an estimated 844 participants (response rate 49.7%). Only 40% of the audience had tried ChatGPT. More trainees had tried ChatGPT compared with faculty. Those who had used ChatGPT were more interested in using it in a wider range of contexts going forwards. Of the three discussed contexts, the greatest uncertainty was shown about using ChatGPT in education. Pros and cons were raised during discussion for the use of this technology in education, research, and healthcare. Discussion There was a range of perspectives around the uses of ChatGPT in education, research, and healthcare, with still much uncertainty around its acceptability and optimal uses. There were different perspectives from respondents of different roles (trainee vs faculty vs staff). More discussion is needed to explore perceptions around the use of LLMs such as ChatGPT in vital sectors such as education, healthcare and research. Given involved risks and unforeseen challenges, taking a thoughtful and measured approach in adoption would reduce the likelihood of harm.
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Twelve evidence-based profiles of roles across the Clinical and Translational Science (CTS) workforce and two patient profiles were developed by CTS Personas collaborators in 2019 as part of the CTSA Program National Center for Data to Health (CD2H). Based on feedback received from the community, CTS Personas team members collaborated to produce five additional Personas to broaden representation of the CTS workforce and enhance the existing portfolio. This paper presents the rationale and methodology used in the latest CTS Personas initiative. This work also includes an implementation scenario incorporating multiple Personas. Using the new National Institutes of Health's (NIH) Data Management and Sharing Policy as an example, we demonstrate how administrators, researchers, support staff, and all CTS collaborators can use the Personas to respond to this new policy while considering the needs of service providers and users, CTS employees with short- and long-term needs, and interdisciplinary perspectives.
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OBJECTIVE: ChatGPT is the first large language model (LLM) to reach a large, mainstream audience. Its rapid adoption and exploration by the population at large has sparked a wide range of discussions regarding its acceptable and optimal integration in different areas. In a hybrid (virtual and in-person) panel discussion event, we examined various perspectives regarding the use of ChatGPT in education, research, and healthcare. MATERIALS AND METHODS: We surveyed in-person and online attendees using an audience interaction platform (Slido). We quantitatively analyzed received responses on questions about the use of ChatGPT in various contexts. We compared pairwise categorical groups with a Fisher's Exact. Furthermore, we used qualitative methods to analyze and code discussions. RESULTS: We received 420 responses from an estimated 844 participants (response rate 49.7%). Only 40% of the audience had tried ChatGPT. More trainees had tried ChatGPT compared with faculty. Those who had used ChatGPT were more interested in using it in a wider range of contexts going forwards. Of the three discussed contexts, the greatest uncertainty was shown about using ChatGPT in education. Pros and cons were raised during discussion for the use of this technology in education, research, and healthcare. DISCUSSION: There was a range of perspectives around the uses of ChatGPT in education, research, and healthcare, with still much uncertainty around its acceptability and optimal uses. There were different perspectives from respondents of different roles (trainee vs faculty vs staff). More discussion is needed to explore perceptions around the use of LLMs such as ChatGPT in vital sectors such as education, healthcare and research. Given involved risks and unforeseen challenges, taking a thoughtful and measured approach in adoption would reduce the likelihood of harm.
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Docentes , Integración Escolar , Humanos , Escolaridad , Instituciones de Salud , ProbabilidadRESUMEN
As the USA and the rest of the world raced to fight the COVID-19 pandemic, years of investments from the National Center for Advancing Translational Sciences allowed for informatics services and resources at CTSA hubs to play a significant role in addressing the crisis. CTSA hubs partnered with local and regional partners to collect data on the pandemic, provide access to relevant patient data, and produce data dashboards to support decision-making. Coordinated efforts, like the National COVID Cohort Collaborative (N3C), helped to aggregate and harmonize clinical data nationwide. Even with significant informatics investments, some CTSA hubs felt unprepared in their ability to respond to the fast-moving public health crisis. Many hubs were forced to quickly evolve to meet local needs. Informatics teams expanded critical support at their institutions which included an engagement platform for clinical research, COVID-19 awareness and education activities in the community, and COVID-19 data dashboards. Continued investments in informatics resources will aid in ensuring that tools, resources, practices, and policies are aligned to meet local and national public health needs.
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OBJECTIVE: Inadequate diversity in clinical trials is widely recognized as a significant contributing factor to health disparities experienced by racial/ethnic minorities and other diverse populations in the US. To address this in a scalable way, we sought to develop a web tool that could help enhance underserved minority participation in clinical research. METHODS: We used our research literacy support flashcard tool as the initial prototype for human-centered design and usability testing of the web tool Health for All in public library settings. After forming partnerships with leadership from Chicago Public Libraries (CPL), local medical libraries, and the Chicago Department of Public Health, we conducted seven iterative design sessions with focus groups of library patrons and library staff from six CPL branches serving underserved communities followed by two rounds of usability testing and website modification. RESULTS: Based on the qualitative research findings from Design Sessions 1-7, we enacted the design decision of a website that was a hybrid of fact-filled and vignette (personal stories) paper prototypes divided into 4 modules (trust, diversity, healthy volunteers, pros/cons), each with their own outcome metrics. The website was thus constructed, and navigation issues identified in two rounds of usability testing by library patrons were addressed through further website modification, followed by the launch of a beta version of a hybridized single-scrolling and guided module prototype to allow further development with website analytics. CONCLUSIONS: We report the development of Health for All, a website designed to enhance racial/ethnic minority participation in clinical trials by imparting research literacy, mitigating distrust engendered by longstanding racism and discrimination, and providing connections to clinical trials recruiting participants.
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Alfabetización en Salud/métodos , Poblaciones Vulnerables , Chicago , Ensayos Clínicos como Asunto , Grupos Focales , Disparidades en Atención de Salud , Humanos , Bibliotecas Médicas , Participación del Paciente , Salud Pública , Investigación Cualitativa , Navegador WebRESUMEN
Assigning authorship and recognizing contributions to scholarly works is challenging on many levels. Here we discuss ethical, social, and technical challenges to the concept of authorship that may impede the recognition of contributions to a scholarly work. Recent work in the field of authorship shows that shifting to a more inclusive contributorship approach may address these challenges. Recent efforts to enable better recognition of contributions to scholarship include the development of the Contributor Role Ontology (CRO), which extends the CRediT taxonomy and can be used in information systems for structuring contributions. We also introduce the Contributor Attribution Model (CAM), which provides a simple data model that relates the contributor to research objects via the role that they played, as well as the provenance of the information. Finally, requirements for the adoption of a contributorship-based approach are discussed.
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Autoria , HumanosRESUMEN
QUESTION: Is there a means of assessing research impact beyond citation analysis? SETTING: The case study took place at the Washington University School of Medicine Becker Medical Library. METHOD: This case study analyzed the research study process to identify indicators beyond citation count that demonstrate research impact. MAIN RESULTS: The authors discovered a number of indicators that can be documented for assessment of research impact, as well as resources to locate evidence of impact. As a result of the project, the authors developed a model for assessment of research impact, the Becker Medical Library Model for Assessment of Research. CONCLUSION: Assessment of research impact using traditional citation analysis alone is not a sufficient tool for assessing the impact of research findings, and it is not predictive of subsequent clinical applications resulting in meaningful health outcomes. The Becker Model can be used by both researchers and librarians to document research impact to supplement citation analysis.