The Use of Clinical Decision Support Systems Based on Artificial Intelligence for Improving Treatment Outcomes and Reducing Medical Errors

Abstract

Artificial Intelligence (AI)-based Clinical Decision Support Systems (CDSS) are increasingly being integrated into healthcare systems to enhance treatment outcomes and reduce medical errors. This study evaluates the effectiveness of AI-driven CDSS in clinical environments by examining their impact on decision-making accuracy, treatment efficiency, and patient safety. A convergent mixed-methods approach was employed, combining quantitative data from 178 healthcare professionals with qualitative insights from case studies and expert interviews. The findings demonstrate that AI-based CDSS significantly improve treatment accuracy, reduce diagnostic and therapeutic errors, and enhance clinical workflow efficiency. However, challenges such as system integration, user trust, and algorithm transparency remain significant barriers. The study provides recommendations for optimizing the implementation of AI-based CDSS in healthcare systems.