Design-a-Trial: A Rule-Based Decision Support System for Clinical Trial Design

Nammuni, Kushan; Pickering, Claire; Modgil, Sanjay; Montgomery, Alan; Hammond, Peter; Wyatt, Jeremy C.; Altman, Douglas G.; Dunlop, Robert; Potts, Hww

doi:10.1007/978-1-4471-0643-2_1

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…There is a compelling need to query and re-use eligibility criteria in order to accelerate the development of new clinical research protocols and related clinical research documents (e.g., case report forms, data collection forms, training materials, etc). Related effort include EligWriter [19] and Design-a-Trial [42] that supported the reuse of eligibility criteria during clinical trial protocol authoring, as well as ERGO [6] and ASPIRE [8] that supports eligibility criteria annotation.…”

Section: Resultsmentioning

confidence: 99%

Formal representation of eligibility criteria: A literature review

Weng

Sim

et al. 2010

Journal of Biomedical Informatics

146

116

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Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria.

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Section: Resultsmentioning

confidence: 99%

Formal representation of eligibility criteria: A literature review

Weng

Sim

et al. 2010

Journal of Biomedical Informatics

146

116

View full text Add to dashboard Cite

show abstract

“…There is a need to manage eligibility criteria in order to accelerate the development of new clinical research protocols and related clinical research documents (eg, case report forms, data collection forms, and training materials). Related efforts include EligWriter and Designa‐Trial that supported the re‐use of eligibility criteria during clinical trial protocol authoring, as well as ERGO and ASPIRE that supported the annotation of eligibility criteria. The definition of computable phenotype algorithms requires interoperability with patient data.…”

Section: Methodsmentioning

confidence: 99%

Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services

Daniel

Ouagne

Sadou

et al. 2016

Learning Health Systems

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With the development of platforms enabling the integration and use of phenome, genome, and exposome data in the context of international research, data management challenges are increasing, and scalable solutions for cross border and cross domain semantic interoperability need to be developed. Reusing routinely collected clinical data, especially, requires computable portable phenotype algorithms running across different electronic health record (EHR) products and healthcare systems. We propose a framework for describing and comparing mediation platforms enabling cross border phenotype identification within federated EHRs. This framework was used to describe the experience gained during the EHR4CR project and the evaluation of the platform developed for accessing semantically equivalent data elements across 11 European participating EHR systems from 5 countries. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data.

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“…Broad tools like Design-a-Trial [40] start to get at these issues but have made little impact in part because they require ongoing maintenance of methodological and clinical knowledge bases, and do not incorporate knowledge from prior studies or outcomes data. By modeling the notion of bias and confounding into OCRe, we have begun to provide an informatics foundation for study design decision support, as discussed in Section 4.3 below.…”

Section: Motivating Use Cases and Backgroundmentioning

confidence: 99%

The Ontology of Clinical Research (OCRe): An informatics foundation for the science of clinical research

Sim

Carini

et al. 2014

Journal of Biomedical Informatics

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To date, the scientific process for generating, interpreting, and applying knowledge has received less informatics attention than operational processes for conducting clinical studies. The activities of these scientific processes — the science of clinical research — are centered on the study protocol, which is the abstract representation of the scientific design of a clinical study. The Ontology of Clinical Research (OCRe) is an OWL 2 model of the entities and relationships of study design protocols for the purpose of computationally supporting the design and analysis of human studies. OCRe’s modeling is independent of any specific study design or clinical domain. It includes a study design typology and a specialized module called ERGO Annotation for capturing the meaning of eligibility criteria. In this paper, we describe the key informatics use cases of each phase of a study’s scientific lifecycle, present OCRe and the principles behind its modeling, and describe applications of OCRe and associated technologies to a range of clinical research use cases. OCRe captures the central semantics that underlies the scientific processes of clinical research and can serve as an informatics foundation for supporting the entire range of knowledge activities that constitute the science of clinical research.

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Design-a-Trial: A Rule-Based Decision Support System for Clinical Trial Design

Cited by 5 publications

References 6 publications

Formal representation of eligibility criteria: A literature review

Formal representation of eligibility criteria: A literature review

Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services

The Ontology of Clinical Research (OCRe): An informatics foundation for the science of clinical research

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