Development of a Nursing Diagnostic Decision Support System for Inpatients with Type 2 Diabetes Mellitus Using Knowledge Engineering

Cho, In Sook; Jung, Eun Ja

Abstract

BACKGROUND: The development of decision support systems for nursing has been limited by difficulties in defining and representing the nursing knowledge base and by a lack of knowledge about how nurses make decisions. However, the current trends suggest that many of the formidable technological and conceptual challenges associated with representing nursing knowledge can be overcome, and that decision support systems developed using knowledge engineering can be used to significantly improve nursing practice. OBJECTIVE: The aim of this study was to develop a diagnostic nursing decision support system for inpatients with type 2 diabetes mellitus, and to elucidate the advantages and disadvantages of applying a knowledge engineering approach to its development.
METHODS
To acquire the relevant knowledge, a literature review was used to iteratively establish nursing diagnoses and clinical assessment criteria. Twenty-five NANDA diagnoses and 145 clinical assessment variables were structured into a criteria table used as the knowledge base for a prototype system. To investigate the responses of nurses to knowledge presentation, 27 nurses from inpatient and ambulatory settings and the graduate course of nursing informatics were recruited and a scenario-based preliminary evaluation was performed.
RESULTS
A prototype for inpatients with type 2 diabetes mellitus was developed as a Web-based stand-alone system. It automatically generated suggested nursing problem lists based on the input data, and also provided detailed explanatory information for each item on the list. We describe the advantages and disadvantages of the development approach used and discuss the users' impressions of the system.