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  • Title: Modelling novice clinical reasoning for a computerized decision support system.
    Author: ONeill ES, Dluhy NM, Chin E.
    Journal: J Adv Nurs; 2005 Jan; 49(1):68-77. PubMed ID: 15610383.
    Abstract:
    AIM: The aim of this paper is to introduce the theoretical framework that directs the project. BACKGROUND: The Novice Computer Decision Support (N-CODES) Project is developing a point-of-care system to assist novice acute care nurses while making clinical judgements. Unlike prior approaches, N-CODES is guided by a theoretical understanding of nurses' decision-making processes, including the manner by which novices develop this skill. FRAMEWORK: Assumptions within information processing theory guided the clinical decision-making framework. The framework is composed of a clinical decision-making model and a second embedded model depicting the clinical reasoning development of novice nurses. MODELS: The model is developed within a pluralistic perspective synthesizing theoretical and empirical knowledge on clinical decision-making and the development of novice reasoning skills. A visual representation of experienced nurse decision-making is presented. A central element is the nurse's use of pre-encounter data and working knowledge. A second model integrates empirical data on the developing clinical reasoning of the novice. This knowledge is loosely scattered through 25 years of literature. The intersection of these models provides a novel perspective on the way novices begin to identify working knowledge patterns and develop a sense of saliency. CONCLUSIONS: Previous attempts to build comprehensive clinical decision support systems have disregarded important theoretical considerations hindering the success of these projects. Grounding a Decision Support System in a theoretical model of novice nurse decision-making will strengthen the utility and acceptance of the Decision Support System. Additionally, a conceptualization of novice nurse development is an asset to nurse educators, managers and scientists interested in improving clinical decision-making.
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