Kocielnik Rafal, Agapie Elena, Argyle Alexander, Hsieh Dennis T, Yadav Kabir, Taira Breena, Hsieh Gary
University of Washington, WA.
UCLA Medical Center, CA.
AMIA Annu Symp Proc. 2020 Mar 4;2019:552-561. eCollection 2019.
Accessing patients' social needs is a critical challenge at emergency departments (EDs). However, most EDs do not have extra staff to administer screeners, and without personnel administration, response rates are low especially for low health literacy patients. To facilitate engagement with such low health literacy patients, we designed a chatbot - HarborBot for social needs screening. Through a study with 30 participants, where participants took a social needs screener both via a traditional survey platform and HarborBot, we found that the two platforms resulted in comparable data (equivalent in 87% of the responses). We also found that while the high health literate participants preferred the traditional survey platform because of efficiency (allowing participants to proceed at their own pace), the low health literate participants preferred HarborBot as it was more engaging, personal, and more understandable. We conclude with a discussion on the design implications for chatbots for social needs screening.
了解患者的社会需求是急诊科面临的一项重大挑战。然而，大多数急诊科没有额外的工作人员来管理筛查工作，而且如果没有专人负责，回复率会很低，尤其是对于健康素养较低的患者。为了便于与这类健康素养较低的患者互动，我们设计了一个聊天机器人——HarborBot，用于社会需求筛查。通过一项有30名参与者的研究，参与者分别通过传统调查平台和HarborBot进行社会需求筛查，我们发现这两个平台得出的数据相当（87%的回复结果相同）。我们还发现，健康素养较高的参与者由于效率原因（允许参与者按自己的节奏进行）更喜欢传统调查平台，而健康素养较低的参与者更喜欢HarborBot，因为它更具吸引力、更个性化且更易于理解。最后，我们讨论了聊天机器人在社会需求筛查方面的设计意义。
