Value Creation for Healthcare Ecosystems through Artificial Intelligence Applied to Physician-to-Physician Communication: A Systematic Review

Artificial intelligence, natural language processing, and large language models in healthcare.

This systematic review investigates the application of AI to physician-to-physician communication within the existing paradigm of AI in healthcare. It explores the potential of AI to augment physicians' capabilities, particularly in decision-making and knowledge sharing, without aiming to replace human expertise. The review operates within the established frameworks of AI research, focusing on specific applications within a defined domain. It identifies current challenges and limitations, such as data quality and ethical considerations, and proposes future research directions within the existing paradigm. While acknowledging the transformative potential of AI, the study doesn't propose a radical shift in understanding or practice but rather focuses on incremental improvements and optimizations within the current paradigm. This work could also be considered to be at a Model Drift stage, as the authors suggest exploring physician-generated real-world data from professional communication as an alternative to traditional data sources like EHRs. This represents a potential refinement of existing data acquisition models but doesn't constitute a complete paradigm shift. The focus remains on improving current AI models rather than proposing a fundamentally different approach.