Within the medical field, there has been significant progress in the development of ontologies and their subsequent use to represent and utilize knowledge more effectively. These have culminated in the creation of large, curated medical ontologies for use in a wide array of applications, as well as higher level frameworks to organize and mitigate conflicts between disparate ontologies. While the engineering field has not been a similar progress in developing and adopting curated ontologies, there has been extensive research into how to effectively use semantic frameworks in engineering knowledge management and design in general, and specifically for the effective creation and documentation of functional basis models. Functional models are a useful tool in the early phases of product design, as they can help more effectively define goals and represent how a product must behave to accomplish these goals. In the specific realm of medical device design however, this process is complicated by a number of factors, including the complexity of the healthcare system and clinical knowledge, as well as a lack of domain specific expertise in the engineering field. Because of these challenges, effective transfer of information from medical domain experts to an engineering context and subsequent utilization of this information are essential to the success of a medical device innovation project. Despite the magnitude and importance of this challenge, few tools exist to help designers record, contextualize, and utilize medical knowledge for the specific purpose of engineering design. In this paper, we present a framework for directly integrating clinical knowledge relating to medical science and practice into the early phases of the engineering process to assist in medical device innovation and design. To accomplish this, existing medical and engineering ontologies were researched, obtained, and interlinked so as to explicitly tie functional models of medical device designs to the underlying medical clinical knowledge and procedures that define a product’s operational environment. The result is a framework that unifies the knowledge embodied in large medical ontologies with the functional basis ontology. This integration facilitates the effective preservation and use of medical knowledge in functional model creation and in the engineering design innovation process in general. To demonstrate the potential usefulness of this framework, we present a simple example of how our framework can be used to associate a functional model with a deconstructed medical procedure, thus enabling the seamless integration of a medical perspective directly into an engineering model.
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ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 17–20, 2014
Buffalo, New York, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-4629-2
PROCEEDINGS PAPER
A Semantic Framework to Integrate Healthcare and Clinical Knowledge in Medical Device Innovation and Design
Thomas J. Hagedorn,
Thomas J. Hagedorn
University of Massachusetts Amherst, Amherst, MA
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Ian R. Grosse,
Ian R. Grosse
University of Massachusetts Amherst, Amherst, MA
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Sundar Krishnamurty,
Sundar Krishnamurty
University of Massachusetts Amherst, Amherst, MA
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Jack C. Wileden
Jack C. Wileden
University of Massachusetts Amherst, Amherst, MA
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Thomas J. Hagedorn
University of Massachusetts Amherst, Amherst, MA
Ian R. Grosse
University of Massachusetts Amherst, Amherst, MA
Sundar Krishnamurty
University of Massachusetts Amherst, Amherst, MA
Jack C. Wileden
University of Massachusetts Amherst, Amherst, MA
Paper No:
DETC2014-35087, V01BT02A014; 11 pages
Published Online:
January 13, 2015
Citation
Hagedorn, TJ, Grosse, IR, Krishnamurty, S, & Wileden, JC. "A Semantic Framework to Integrate Healthcare and Clinical Knowledge in Medical Device Innovation and Design." Proceedings of the ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1B: 34th Computers and Information in Engineering Conference. Buffalo, New York, USA. August 17–20, 2014. V01BT02A014. ASME. https://doi.org/10.1115/DETC2014-35087
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