The TouCAN Codebook: Detecting textual misunderstanding in doctor-patient communication with the philosophy of language tools

Abstract

Effective communication is widely recognized as a cornerstone of successful medical treatment, as extensively documented in prior research. The doctor-patient relationship relies on clear, accurate information exchange to ensure precise diagnoses, treatment adherence, and patient satisfaction. Yet misunderstandings can seriously undermine this process, creating barriers to optimal care and weakening the therapeutic alliance—a critical element of effective healthcare. Consequently, identifying, understanding, and addressing these misunderstandings is essential. This paper introduces a novel approach to detecting and analyzing such misunderstandings in clinical interactions by drawing on concepts from the philosophy of language. Specifically, we present the ToUCAN Codebook, a structured framework designed to systematically classify and examine instances of textual miscommunication in doctor-patient dialogues. By offering a clear methodology for identifying and preventing potential communication breakdowns, the ToUCAN Codebook contributes to improved healthcare outcomes and a deeper understanding of the dynamics that shape medical discourse.