Clinical Decision Support System for Point of Care Use

Ontology-driven Design and Software Implementation

Farion, K.
Michalowski, W.
Wilk, S.
O’Sullivan, D.
Rubin, S.
Weiss, D.

Departments of Pediatrics and Emergency Medicine, University of Ottawa, Children’s Hospital of Eastern Ontario, Ottawa, Canada
MET Research Group, Telfer School of Management, University of Ottawa, Ottawa, Canada
Department of Surgery, University of Ottawa, Children’s Hospital of Eastern Ontario, Ottawa, Canada
Institute of Computing Science, Poznan University of Technology, Poznan, Poland

Correspondence to:

Szymon Wilk Telfer School of Management University of Ottawa 55 Laurier Ave East Ottawa, ON K1N 6N5 Canada [email protected]

Methods of Information in Medicine 48(04):p 381-390, 2009. | DOI: 10.3414/ME0574

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.