A Review of Decision Support Mechanisms in Clinical Practice: Techniques, Limitations and Future Opportunities in Healthcare

Abstract

Digital advancements in healthcare have driven many medical institutions to use Clinical Decision Support Systems (CDSS), which improve how medical decisions are made, lower the risk of mistakes and personalize patient care. The paper describes the core concepts, types and main technologies of CDSS, making it clear that knowledge-based systems are controlled by clinical rules, while systems that do not depend on knowledge use AI and ML. It analyzes important roles of CDSS, for example, security for patients, precision in diagnoses, administrative assistance and limiting expenses. It also points out the challenges getting in the way of using CDSS, such as too many alerts, unreliable data and problems coordinating different systems. Moreover, it explains that enhanced AI, federated learning, applying blockchain technology, and personalized medicine can lead to new chances for CDSS improvement. Additionally, future opportunities are discussed, suggesting that such systems need to be clear, work well together and guard people’s privacy to be used in various healthcare settings.