Modeling participant-related clinical research events using conceptual knowledge acquisition techniques

• Published in: AMIA ... Annual Symposium proceedings Vol. 2007; pp. 593 - 597
• Main Authors: Payne, Philip R O, Mendonca, Eneida A, Starren, Justin B
• Format: Journal Article
• Language: English
• Published: United States American Medical Informatics Association 11.10.2007
• Subjects: Abstracting and Indexing as Topic - methods; Algorithms; Artificial Intelligence; Clinical Protocols; Clinical Trials as Topic; Humans; Subject Headings; Unified Medical Language System
• ISSN: 1942-597X; 1559-4076

The active phase of a clinical trial is defined by a protocol schema consisting of participant-related events organized into multiple visits. Current efforts to model protocol schemas in a computable format have focused on high-level abstractions, such as the temporal relationships between visits. However, such approaches do not address the need for a more granular computational model of the individual events that comprise each visit. To address the preceding gap in knowledge, this paper will describe a study in which conceptual knowledge acquisition (CKA) techniques were applied to a corpus of 32 clinical trials protocol documents in order to develop a knowledge collection of common participant-related clinical research events. These techniques identified 7 high-level concepts that could be used as organizing principles in the resulting knowledge collection. Such results confirm the utility of CKA methods in the clinical research domain.