Methods Inf Med 2009; 48(04): 381-390
DOI: 10.3414/ME0574
Original Articles
Schattauer GmbH

Clinical Decision Support System for Point of Care Use

Ontology-driven Design and Software Implementation
K. Farion
1   Departments of Pediatrics and Emergency Medicine, University of Ottawa, Children’s Hospital of Eastern Ontario, Ottawa, Canada
,
W. Michalowski
2   MET Research Group, Telfer School of Management, University of Ottawa, Ottawa, Canada
,
S. Wilk
2   MET Research Group, Telfer School of Management, University of Ottawa, Ottawa, Canada
,
D. O’Sullivan
2   MET Research Group, Telfer School of Management, University of Ottawa, Ottawa, Canada
,
S. Rubin
3   Department of Surgery, University of Ottawa, Children’s Hospital of Eastern Ontario, Ottawa, Canada
,
D. Weiss
4   Institute of Computing Science, Poznan University of Technology, Poznan, Poland
› Author Affiliations
Further Information

Publication History

Received: 20 May 2008

accepted: 12 January 2009

Publication Date:
17 January 2018 (online)

Preview

Summary

Objectives: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation.

Methods: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications’ functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions.

Results: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical pros-tatectomy on the hospital ward) and implemented on two computing platforms – desktop and handheld computers.

Conclusions: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.