Conceptual Framework to Support Clinical Trial Optimization and End-to-End Enrollment Workflow.
Ontology highlight
ABSTRACT:
SUBMITTER: Jain NM
PROVIDER: S-EPMC6873934 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature
Publications
Conceptual Framework to Support Clinical Trial Optimization and End-to-End Enrollment Workflow.
Jain Neha M NM Culley Alison A Knoop Teresa T Micheel Christine C Osterman Travis T Levy Mia M
JCO clinical cancer informatics 20190601
In this work, we present a conceptual framework to support clinical trial optimization and enrollment workflows and review the current state, limitations, and future trends in this space. This framework includes knowledge representation of clinical trials, clinical trial optimization, clinical trial design, enrollment workflows for prospective clinical trial matching, waitlist management, and, finally, evaluation strategies for assessing improvement. ...[more]
Similar Datasets
Project description:The objective of this review was to describe methods used to study and model workflow. The authors included studies set in a variety of industries using qualitative, quantitative and mixed methods. Of the 6221 matching abstracts, 127 articles were included in the final corpus. The authors collected data from each article on researcher perspective, study type, methods type, specific methods, approaches to evaluating quality of results, definition of workflow and dependent variables. Ethnographic observation and interviews were the most frequently used methods. Long study durations revealed the large time commitment required for descriptive workflow research. The most frequently discussed technique for evaluating quality of study results was triangulation. The definition of the term "workflow" and choice of methods for studying workflow varied widely across research areas and researcher perspectives. The authors developed a conceptual framework of workflow-related terminology for use in future research and present this model for use by other researchers.
| S-EPMC2995718 | biostudies-literature
Project description:The unprecedented demand for severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) testing led to challenges in prioritizing and processing specimens efficiently. We describe and evaluate a novel workflow using provider- and patient-facing ask at order entry (AOE) questions to generate distinctive icons on specimen labels for within-laboratory clinical decision support (CDS) for specimen triaging. A multidisciplinary committee established target turnaround times (TATs) for SARS-CoV-2 nucleic acid amplification test (NAAT) based on common clinical scenarios. A set of AOE questions was used to collect relevant clinical information that prompted icon generation for triaging SARS-CoV-2 NAAT specimens. We assessed the collect-to-verify TATs among relevant clinical scenarios. Our study included a total of 1,385,813 SARS-CoV-2 NAAT conducted from March 2020 to June 2022. Most testing met the TAT targets established by institutional committees, but deviations from target TATs occurred during periods of high demand and supply shortages. Median TATs for emergency department (ED) and inpatient specimens and ambulatory pre-procedure populations were stable over the pandemic. However, healthcare worker and other ambulatory test TATs varied substantially, depending on testing volume and community transmission rates. Median TAT significantly differed throughout the pandemic for ED and inpatient clinical scenarios, and there were significant differences in TAT among label icon-signified ambulatory clinical scenarios. We describe a novel approach to CDS for triaging specimens within the laboratory. The use of CDS tools could help clinical laboratories prioritize and process specimens efficiently, especially during times of high demand. Further studies are needed to evaluate the impact of our CDS tool on overall laboratory efficiency and patient outcomes. IMPORTANCE We describe a novel approach to clinical decision support (CDS) for triaging specimens within the clinical laboratory for severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) nucleic acid amplification tests (NAAT). The use of our CDS tool could help clinical laboratories prioritize and process specimens efficiently, especially during times of high demand. There were significant differences in the turnaround time for specimens differentiated by icons on specimen labels. Further studies are needed to evaluate the impact of our CDS tool on overall laboratory efficiency and patient outcomes.
| S-EPMC10865785 | biostudies-literature
Project description:BACKGROUND:The implementation of clinical decision support systems (CDSSs) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and those associated with technology acceptance. However, the literature regarding these subjects is fragmented and originates from two traditionally separate disciplines: implementation science and technology acceptance. OBJECTIVE:Our objective is to propose an integrated framework that bridges the gap between the behavioral change and technology acceptance aspects of the implementation of CDSSs. METHODS:We employed an iterative process to map constructs from four contributing frameworks-the Theoretical Domains Framework (TDF); the Consolidated Framework for Implementation Research (CFIR); the Human, Organization, and Technology-fit framework (HOT-fit); and the Unified Theory of Acceptance and Use of Technology (UTAUT)-and the findings of 10 literature reviews, identified through a systematic review of reviews approach. RESULTS:The resulting framework comprises 22 domains: agreement with the decision algorithm; attitudes; behavioral regulation; beliefs about capabilities; beliefs about consequences; contingencies; demographic characteristics; effort expectancy; emotions; environmental context and resources; goals; intentions; intervention characteristics; knowledge; memory, attention, and decision processes; patient-health professional relationship; patient's preferences; performance expectancy; role and identity; skills, ability, and competence; social influences; and system quality. We demonstrate the use of the framework providing examples from two research projects. CONCLUSIONS:We proposed BEAR (BEhavior and Acceptance fRamework), an integrated framework that bridges the gap between behavioral change and technology acceptance, thereby widening the view established by current models.
| S-EPMC7441385 | biostudies-literature
Project description:Epigenetics helps define current cell states, yet also shapes how cells respond to external cues such as differentiation or stress. The epigenetic plasticity of a cell describes how flexible this regulation is. Bivalent chromatin is an exemplar of epigenetic plasticity. This co-occurrence of the active-associated H3K4me3 and inactive-associated H3K27me3 histone modifications on opposite tails of the same nucleosome was first described in mouse embryonic stem cells where it is found at promoters of key developmental genes. It has been postulated that bivalent chromatin poises these promoters, keeping them free from repressive DNAmethylation, enabling them to be transcriptionally upregulated upon differentiation. Bivalent chromatin has also been reported in other cell types including somatic cells and cancer cells, however we know little of the dynamics, resolution and regulation of this chromatin state. This is partly due to the technical challenges distinguishing bone-fide bivalent chromatin, where both marks are on the same nucleosome, from sample heterogeneity where some alleles have H3K4me3 and others H3K27me3. We developed a robust and sensitive reChIP method to accurately profile bivalent chromatin in as little as 2 million mouse embryonic stem cells. We validated the sensitivity of our method to detect changes in bivalent chromatin by profiling mouse ESCs lacking the epigenetic priming factors Dppa2 and Dppa4.
2024-02-26 | GSE242686 | GEO
Project description:Design of Phase III trials for diabetic nephropathy currently requires patients at a high risk of progression defined as within three years of a hard end point (end-stage renal disease, 40% loss of estimated glomerular filtration rate, or death). To improve the design of these trials, we used natural history data from the Joslin Kidney Studies of chronic kidney disease in patients with diabetes to develop an improved criterion to identify such patients. This included a training cohort of 279 patients with type 1 diabetes and 134 end points within three years, and a validation cohort of 221 patients with type 2 diabetes and 88 end points. Previous trials selected patients using clinical criteria for baseline urinary albumin-to-creatinine ratio and estimated glomerular filtration rate. Application of these criteria to our cohort data yielded sensitivities (detection of patients at risk) of 70-80% and prognostic values of only 52-63%. We applied classification and regression trees analysis to select from among all clinical characteristics and markers the optimal prognostic criterion that divided patients with type 1 diabetes according to risk. The optimal criterion was a serum tumor necrosis factor receptor 1 level over 4.3 ng/ml alone or 2.9-4.3 ng/ml with an albumin-to-creatinine ratio over 1900 mg/g. Remarkably, this criterion produced similar results in both type 1 and type 2 diabetic patients. Overall, sensitivity and prognostic value were high (72% and 81%, respectively). Thus, application of this criterion to enrollment in future clinical trials could reduce the sample size required to achieve adequate statistical power for detection of treatment benefits.
| S-EPMC5796779 | biostudies-literature
Project description:SummaryDeepKG is an end-to-end deep learning-based workflow that helps researchers automatically mine valuable knowledge in biomedical literature. Users can utilize it to establish customized knowledge graphs in specified domains, thus facilitating in-depth understanding on disease mechanisms and applications on drug repurposing and clinical research, etc. To improve the performance of DeepKG, a cascaded hybrid information extraction framework (CHIEF) is developed for training model of 3-tuple extraction, and a novel AutoML-based knowledge representation algorithm (AutoTransX) is proposed for knowledge representation and inference. The system has been deployed in dozens of hospitals and extensive experiments strongly evidence the effectiveness. In the context of 144,900 COVID-19 scholarly full-text literature, DeepKG generates a high-quality knowledge graph with 7,980 entities and 43,760 3-tuples, a candidate drug list, and relevant animal experimental studies are being carried out. To accelerate more studies, we make DeepKG publicly available and provide an online tool including the data of 3-tuples, potential drug list, question answering system, visualization platform.AvailabilityFree to all users: http://covidkg.ai/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC8689937 | biostudies-literature
Project description:Background: Proteomic mass spectrometry is widely used to quantify proteins in biological specimens for biomarker discovery. Clinical studies requiring proteomic analysis of plasma are more complicated due to the high dynamic range and abundance of major plasma proteins. There is an unmet need to develop robust, rapid and cost-effective workflows able to support large-scale clinical studies of thousands of plasma specimens. We set about developing a suitable system to be used for the analysis of plasma collected from FIELD trial participants which investigated five years oral fenofibrate on coronary heart disease and microvascular complications.
2023-09-29 | PXD029732 | Pride
Project description:BackgroundClinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks.Methods/designThe objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks.DiscussionThis is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.
| S-EPMC3328243 | biostudies-literature
Project description:As defaunation spreads through the world, there is an urgent need for restoring ecological interactions, thus assuring ecosystem processes. Here, we define the new concept of credit of ecological interactions, as the number of interactions that can be restored in a focal area by species colonization or reintroduction. We also define rewiring time, as the time span until all the links that build the credit of ecological interactions of a focal area have become functional again. We expect that the credit will be gradually cashed following refaunation in rates that are proportional to (1) the abundance of the reintroduced species (that is expected to increase in time since release), (2) the abundance of the local species that interact with them, and (3) the traits of reintroduced species. We illustrated this approach using a theoretical model and an empirical case study where the credit of ecological interactions was estimated. This new conceptual framework is useful for setting reintroduction priorities and for evaluating the success of conservation initiatives that aim to restore ecosystem services.
| S-EPMC5355187 | biostudies-literature
Project description:The Vision and Change in Undergraduate Biology Education: Call to Action report has inspired and supported a nationwide movement to restructure undergraduate biology curricula to address overarching disciplinary concepts and competencies. The report outlines the concepts and competencies generally but does not provide a detailed framework to guide the development of the learning outcomes, instructional materials, and assessment instruments needed to create a reformed biology curriculum. In this essay, we present a detailed Vision and Change core concept framework that articulates key components that transcend subdisciplines and scales for each overarching biological concept, the Conceptual Elements (CE) Framework. The CE Framework was developed using a grassroots approach of iterative revision and incorporates feedback from more than 60 biologists and undergraduate biology educators from across the United States. The final validation step resulted in strong national consensus, with greater than 92% of responders agreeing that each core concept list was ready for use by the biological sciences community, as determined by scientific accuracy and completeness. In addition, we describe in detail how educators and departments can use the CE Framework to guide and document reformation of individual courses as well as entire curricula.
| S-EPMC5459242 | biostudies-literature