Implementing combined decision models in healthcare settings: the Simon and Pauker- Kassirer models

Abstract

Background: Modeling medical decision-making has attracted considerable attention over the years, and has become the topic of many investigations. Researchers have attempted to model this critical and extremely complex process from several different angles to enable hospital clinicians to engage in decision-making using empirical tools.

Purpose: This paper takes a famous managerial model of decision-making in a non-medical setting and integrates it with a well- known model of medical decision-making to generate a unified illustration of the process. Both models deal with decision-making. However, Simon’s model is less easily applied to the unique process of medical decision making. The proposed integration may help bridge the gap between the models and approaches by creating a unified framework to deal with the challenge of medical decision making in hospital environments through empirical methods.

Approach: Simon’s model of automation provides the general structure of the decision-making process by dividing it into three stages: Intelligence, Design and Choice. The Pauker & Kassirer model deals with probabilistic and statistical applications of clinical processes, and introduces a threshold approach and decision trees as the main decision tools. The discussion explores the advantages and disadvantages of each model and what can be gained by combining them.

Research limitations: Although these models were used to form an integrated framework, they were developed almost three decades apart. Therefore, caution is of the essence when applying them to real-life circumstances, and further research is needed to validate this integration.