Enhancing Clinical Decision-Making: An Integrated Approach Using ISPS and KMoS-SSA Framework

Abstract

Clinical psychologists navigate complex decision-making processes shaped by diverse mental health conditions, individualized patient needs, and evolving treatment options. These complexities create significant challenges, such as limited resources and the demand for personalized treatment plans. In response, this chapter introduces the Integrated System for Psychologist Support (ISPS), a comprehensive system designed to enhance informed decision-making in clinical psychology. The ISPS has been conceptualized using the Knowledge Management on a Strategy through Soft Systemic Analysis (KMoS-SSA) methodological framework, which leverages knowledge management theories and soft systems thinking to achieve desirable, effective, and feasible solutions within the evolution knowledge cycle. The ISPS incorporates a Gamified Application Module to collect patient data and a Machine Learning Module to categorize patient information into profiles that support clinical decision-making. Real-world applicability was pursued from the outset: practicing clinicians participated in co-design workshops, walkthrough evaluations, and iterative refinements that ensured the prototype fits seamlessly into routine assessment workflows while respecting stringent data-privacy regulations. In parallel, privacy-preserving synthetic data were incorporated to broaden the system’s training base without compromising confidentiality. This project is anchored in KMoS-SSA’s knowledge-evolution cycle, which captures expert insight, models domain interactions, validate proposed solutions, and continually updates them as new evidence. This iterative mechanism secures the long-term relevance and adaptability of ISPS as clinical contexts evolve.