Patient–physician communication is an often overlooked yet a very important aspect of providing medical care. Positive patient–physician quality of communication within discourse has an influence on various aspects of a consultation such as a patient’s treatment adherence to prescribed medical regimen and their medical care outcome. As few reference standards exist for exploring semantics within the patient–physician setting and its effects on personalized healthcare, this paper presents a study exploring three methods to capture, model and evaluate patient–physician communication among three distinct data-sources. We introduce, compare and contrast these methods for capturing and modeling patient–physician communication quality using relatedness between discourse content within a given consultation. Results are shown for all three data-sources and communication quality scores among physicians recorded. We found our models demonstrate the ability to capture positive communication quality between both participants within a consultation. We also evaluate these findings against self-reported questionnaires highlighting various aspects of the consultation and rank communication quality among seventeen physicians who consulted amid one-hundred and thirty-two patients.

医患沟通经常被忽视，但却是提供医疗服务的一个非常重要的方面。话语中积极的医患沟通质量对咨询的各个方面都有影响，例如患者对规定医疗方案的治疗依从性及其医疗结果。由于很少有参考标准可用于探索患者-医生设置中的语义及其对个性化医疗保健的影响，本文提出了一项研究，探索了三种方法来捕获、建模和评估三个不同数据源之间的患者-医生交流。我们介绍、比较和对比这些使用给定咨询中话语内容之间的相关性来捕获和建模患者-医生沟通质量的方法。结果显示了所有三个数据源和记录的医生之间的通信质量分数。我们发现我们的模型展示了在咨询中捕捉两个参与者之间积极沟通质量的能力。我们还根据自我报告的问卷评估了这些发现，这些问卷突出了咨询的各个方面，并对在一百三十二名患者中咨询的十七名医生之间的沟通质量进行了排名。