Risk communication is one of the most delicate dialogues within the healthcare domain. Such delicacy is given by the nature of the topics treated within these dialogues and the easiness with which misunderstandings between doctors and patients may occur. Hence, one of the main challenges is to enhance doctors’ awareness of implicit understandings between doctors and patients in the context of pre-operative communication of risks. In this paper, we intend to shed light on this topic, poorly investigated in the literature, by starting from the perspective of the philosophy of language, in particular pragmatic analysis tools that make the implicit understandings of the interaction explicit. We analyze actual cases involving evaluation before cardiac surgery from a philosophy of language perspective. Then, we demonstrate on the dataset we collected, how available state-of-the-art models are far from reaching acceptable performance in detecting misunderstandings within healthcare-wise dialogues. Finally, we conclude the paper by tracing a possible research direction on this topic.

Misunderstanding and Risk Communication in Healthcare

Monica Consolandi
;
Simone Magnolini;Mauro Dragoni
2023-01-01

Abstract

Risk communication is one of the most delicate dialogues within the healthcare domain. Such delicacy is given by the nature of the topics treated within these dialogues and the easiness with which misunderstandings between doctors and patients may occur. Hence, one of the main challenges is to enhance doctors’ awareness of implicit understandings between doctors and patients in the context of pre-operative communication of risks. In this paper, we intend to shed light on this topic, poorly investigated in the literature, by starting from the perspective of the philosophy of language, in particular pragmatic analysis tools that make the implicit understandings of the interaction explicit. We analyze actual cases involving evaluation before cardiac surgery from a philosophy of language perspective. Then, we demonstrate on the dataset we collected, how available state-of-the-art models are far from reaching acceptable performance in detecting misunderstandings within healthcare-wise dialogues. Finally, we conclude the paper by tracing a possible research direction on this topic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/346167
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