Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science

Radiotherapy biobanking : current landscape, opportunities, challenges, and future aspirations

This work was supported by the National Cancer Research Institute (NCRI) Clinical and Translational Radiotherapy Research Working Group (CTRad), which was established in 2009 by six of the NCRI's funding partners. We gratefully acknowledge Carolyn Chan and Julie Stock (NCRI) for their assistance in collecting the responses to the questionnaire sent to CTRad membership. Open Access via the Wiley OA AgreementPeer reviewedPublisher PD

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

Improving Oncology Worldwide

This open access book describes strategies and experiences of highly skilled professionals in improving oncology care worldwide. The book is structured into three main sections with several chapters each, reflecting the authors' individual, real-life experiences. It explores ways to improve oncology education and scientific training, how to set up and run a clinical research facility ethically and efficiently in low- and middle-income settings, addressing the challenges that the workforce encounters in the real world. The main challenges of today’s oncologists seem to be the ever-growing patient care and administrative workload and the risk of burn-out. What are the best strategies to maintain a healthy work-life for the benefit of the patients, the physicians and society, taking into account the different needs, depending on factors like peace, social and gender equality? This book addresses oncologists all over the world and their allies throughout the associated industries to highlight the importance of shared and sustainable education, clinical research and global cancer care

Implementation interventions to promote the uptake of evidence-based practices in stroke rehabilitation (Review)

Background Rehabilitation based upon research evidence gives stroke survivors the best chance of recovery. There is substantial research to guide practice in stroke rehabilitation, yet uptake of evidence by healthcare professionals is typically slow and patients often do not receive evidence‐based care. Implementation interventions are an important means to translate knowledge from research to practice and thus optimise the care and outcomes for stroke survivors. A synthesis of research evidence is required to guide the selection and use of implementation interventions in stroke rehabilitation. Objectives To assess the effects of implementation interventions to promote the uptake of evidence‐based practices (including clinical assessments and treatments recommended in evidence‐based guidelines) in stroke rehabilitation and to assess the effects of implementation interventions tailored to address identified barriers to change compared to non‐tailored interventions in stroke rehabilitation. Search methods We searched CENTRAL, MEDLINE, Embase, and eight other databases to 17 October 2019. We searched OpenGrey, performed citation tracking and reference checking for included studies and contacted authors of included studies to obtain further information and identify potentially relevant studies. Selection criteria We included individual and cluster randomised trials, non‐randomised trials, interrupted time series studies and controlled before‐after studies comparing an implementation intervention to no intervention or to another implementation approach in stroke rehabilitation. Participants were qualified healthcare professionals working in stroke rehabilitation and the patients they cared for. Studies were considered for inclusion regardless of date, language or publication status. Main outcomes were healthcare professional adherence to recommended treatment, patient adherence to recommended treatment, patient health status and well‐being, healthcare professional intention and satisfaction, resource use outcomes and adverse effects. Data collection and analysis Two review authors independently selected studies for inclusion, extracted data, and assessed risk of bias and certainty of evidence using GRADE. The primary comparison was any implementation intervention compared to no intervention. Main results Nine cluster randomised trials (12,428 patient participants) and three ongoing trials met our selection criteria. Five trials (8865 participants) compared an implementation intervention to no intervention, three trials (3150 participants) compared one implementation intervention to another implementation intervention, and one three‐arm trial (413 participants) compared two different implementation interventions to no intervention. Eight trials investigated multifaceted interventions; educational meetings and educational materials were the most common components. Six trials described tailoring the intervention content to identified barriers to change. Two trials focused on evidence‐based stroke rehabilitation in the acute setting, four focused on the subacute inpatient setting and three trials focused on stroke rehabilitation in the community setting. We are uncertain if implementation interventions improve healthcare professional adherence to evidence‐based practice in stroke rehabilitation compared with no intervention as the certainty of the evidence was very low (risk ratio (RR) 1.19, 95% confidence interval (CI) 0.53 to 2.64; 2 trials, 39 clusters, 1455 patient participants; I2 = 0%). Low‐certainty evidence indicates implementation interventions in stroke rehabilitation may lead to little or no difference in patient adherence to recommended treatment (number of recommended performed outdoor journeys adjusted mean difference (MD) 0.5, 95% CI –1.8 to 2.8; 1 trial, 21 clusters, 100 participants) and patient psychological well‐being (standardised mean difference (SMD) –0.02, 95% CI –0.54 to 0.50; 2 trials, 65 clusters, 1273 participants; I2 = 0%) compared with no intervention. Moderate‐certainty evidence indicates implementation interventions in stroke rehabilitation probably lead to little or no difference in patient health‐related quality of life (MD 0.01, 95% CI –0.02 to 0.05; 2 trials, 65 clusters, 1242 participants; I2 = 0%) and activities of daily living (MD 0.29, 95% CI –0.16 to 0.73; 2 trials, 65 clusters, 1272 participants; I2 = 0%) compared with no intervention. No studies reported the effects of implementation interventions in stroke rehabilitation on healthcare professional intention to change behaviour or satisfaction. Five studies reported economic outcomes, with one study reporting cost‐effectiveness of the implementation intervention. However, this was assessed at high risk of bias. The other four studies did not demonstrate the cost‐effectiveness of interventions. Tailoring interventions to identified barriers did not alter results. We are uncertain of the effect of one implementation intervention versus another given the limited very low‐certainty evidence. Authors' conclusions We are uncertain if implementation interventions improve healthcare professional adherence to evidence‐based practice in stroke rehabilitation compared with no intervention as the certainty of the evidence is very low

2007-2008 annual report to the S.C. General Assembly and the S.C. Budget & Control Board

The South Carolina Centers of Economic Excellence publishes an annual report to the South Carolina Budget & Control Board with executive summary, economic impact summary, program history, description for each Centers of Economic Excellence with biography of endowed chair, program achievements, review board members, by-laws of the review board, and program account report