AI-Supported Decision-Making in Clinical Settings:
Transforming Healthcare Delivery

The healthcare industry is undergoing a significant paradigm shift, with artificial intelligence (AI) rapidly transitioning from a supplemental support tool to a strategic component deeply embedded in clinical IT infrastructure.

The American Medical Association (AMA) reports a significant increase in AI adoption, with nearly two-thirds of physicians using health AI in 2024, up 78% from the previous year.

Modern AI systems excel at learning from historical medical data, recognizing intricate patterns, prognosticating disease progression, recommending evidence-based treatment options, and assisting with comprehensive care planning.

Their increasing popularity points to a future where AI literacy and effective collaboration with intelligent systems will become indispensable competencies for healthcare professionals. The "quadruple aim" of improving patient care, population health, and the work life of healthcare professionals, as well as lowering healthcare costs, appears increasingly attainable through the thoughtful integration of AI.

The concept of AI being "embedded" into clinical infrastructure, rather than simply serving as a "supportive" component, implies a deep integration into clinical workflows, necessitating changes in data collection, processing, presentation, and governance. Furthermore, healthcare organizations must train employees on new systems and address potential security and privacy risks, as well as AI-specific issues such as bias and lack of explainability.

In this article, ITRex, a software engineering company that specializes in healthcare AI solutions, examines the current state of medical AI and its growing use in clinical decision making.