Algorithms, Artificial Intelligence, Decision Support Systems, Clinical, Decision Support Techniques, Diagnosis, Computer-Assisted
A lack of acceptance has hindered the widespread adoption and implementation of clinical prediction rules (CPRs). The use of clinical decision support systems (CDSSs) has been advocated as one way of facilitating a broader dissemination and validation of CPRs. This requires computable models of clinical evidence based on open standards rather than closed proprietary content. The on-going TRANSFoRm project has developed ontological models of CPRs suitable for providing CPR based decision support. This paper presents a description of the design and implementation of the ontology model for CPRs that has been proposed. The conceptual validity of the ontology is discussed using the example of a specific CPR in the form of the Alvarado Score for acute appendicitis. We demonstrate how the model is used to query the structure of this particular rule, providing a computable representation suitable for CPRs in general.
Medicine and Health Sciences
Corrigan D, Taweel A, Fahey T, Arvanitis T, Delaney B. An ontological treatment of clinical prediction rules implementing the Alvarado score. Studies in Health Technology and Informatics. 2013;186:103-7.