PICOAS: a clinical knowledge linking model for delivering up-to-date, interrelated, and personalized decision support

Clinical decision support is aimed at delivering the best evidence available encapsulated in practice guidelines. The current challenges in reaching this goal include keeping guidelines up-to-date, linking them to address multi-morbidity, and flexible customization to fit patient preferences. Although a variety of solutions have been proposed to address these challenges, a comprehensive approach for their systematic integration remains absent. We propose PICOAS, a knowledge linking model composed of three modes, to establish the relationship between knowledge sources of guidelines, medical literature, and patient reviews. An LLM-Agent architecture is developed, which is capable of understanding and providing decision support informed by the knowledge link model. We demonstrate the feasibility and effectiveness of our approach using a study of breast cancer. An experiment was conducted for evaluating its capabilities in addressing the three challenges.