A Novel Collaborative Decision Description Language (CoDeL): for Modelling Personalized Doctor-Patient Shared Decision Making (Preprint)

Abstract

BACKGROUND Effective shared decision making between patients and physicians is crucial for enhancing healthcare quality and reducing medical errors. But the shared decision making process itself is difficult to understand, and it is not clear where to begin to solve the problems that arise during this interaction. OBJECTIVE Therefore, we propose a Collaborative Decision Description Language (CoDel) to help better understand and characterize the interactive process by modeling the common decision scenario, so that each decision process has a reliable theoretical basis and traceability. METHODS The CoDel we define consists of four factors: A decision-maker interaction process protocol based on Lightweight Social Calculs (LSC); Using Speech Acts to define the semantic relations in the interaction process; Arguments in semantics guided by clinical guidelines; Incorporate constraints for personality modeling. RESULTS Finally, we validate and demonstrate the applicability of our approach in conjunction with the interaction between patients and physicians with atrial fibrillation. In addition, we combine our method with GPT to solve the unexplainability of GPT, and at the same time validate our method and enrich our argument. CONCLUSIONS Through the defined decision language, the communication between doctors and patients can be improved.