Designing a conversational agent for patients with hematologic malignancies: Usability and Usefulness Study

摘要

Empowering patients to record health-related information can provide further insights on treatment response, disease evolution, disease burden, Quality of Life (QoL) and enables direct measurement of the experiences of patients with chronic conditions, including hematologic malignancies. Evidence suggests that using electronic tools for the collection of patient health outcomes improves symptom control and enhances patient satisfaction. In parallel, recent advancement in machine learning and speech recognition have led to conversational agents, software systems mimicking written or spoken human speech, being increasingly adopted in the health care domain. In the present manuscript we present (i) a methodology for the implementation of a conversational agent able to collect family history and symptom-related information of patients with hematologic malignancies and (ii) its initial evaluation results from a relevant feasibility study. Our approach uses deep learning algorithms trained in conversations focused on hematologic malignancies. The evaluation of the model from the user experience perspective provides promising results regarding the acceptability and comprehensibility of the system.