Western Norway Familial Cancer Center, Haukeland University Hospital, Bergen, Norway.
Western Norway Familial Cancer Center, Haukeland University Hospital, Bergen, Norway; Faculty of Health Studies, VID Specialized University, Bergen, Norway.
Patient Educ Couns. 2022 Jun;105(6):1488-1494. doi: 10.1016/j.pec.2021.09.027. Epub 2021 Oct 6.
We aimed at developing a pilot version of an app (Rosa) that can perform digital conversations with breast or ovarian cancer patients about genetic BRCA testing, using chatbot technology, to identify best practices for future patient-focused chatbots.
We chose a commercial chatbot platform and participatory methodology with a team of patient representatives, IT engineers, genetic counselors and clinical geneticists, within a nationwide collaboration. An iterative approach ensured extensive user and formal usability testing during the development process.
The development phase lasted for two years until the pilot version was completed in December 2019. The iteration steps disclosed major challenges in the artificial intelligence (AI)-based matching of user provided questions with predefined information in the database, leading initially to high level of fallback answers. We therefore developed strategies to reduce potential language ambiguities (e.g. BRCA1 vs BRCA2) and overcome dialogue confusion. The first prototype contained a database with 500 predefined questions and 67 corresponding predefined answers, while the final version included 2257 predefined questions and 144 predefined answers. Despite the limited AI functionality of the chatbot, the testing revealed that the users liked the layout and found the chatbot trustworthy and reader friendly.
Building a health chatbot is challenging, expensive and time consuming with today's technology. The users had a positive attitude to the chatbot, and would use it in a real life setting, if given to them by health care personnel.
We here present a framework for future health chatbot initiatives. The participatory methodology in combination with an iterative approach ensured that the patient perspective was incorporated at every level of the development process. We strongly recommend this approach in patient-centered health innovations.
我们旨在开发一个应用程序（Rosa）的试点版本，该应用程序可以使用聊天机器人技术与乳腺癌或卵巢癌患者进行关于遗传 BRCA 测试的数字对话，以确定未来以患者为中心的聊天机器人的最佳实践。
我们选择了一个商业聊天机器人平台和参与性方法，该方法由一组患者代表、IT 工程师、遗传咨询师和临床遗传学家组成，这是一个全国性的合作。迭代方法确保在开发过程中进行广泛的用户和正式可用性测试。
开发阶段持续了两年，直到 2019 年 12 月完成了试点版本。迭代步骤揭示了人工智能（AI）在基于用户提供的问题与数据库中预定义信息的匹配方面的主要挑战，最初导致了高比例的后备回答。因此，我们制定了策略来减少潜在的语言歧义（例如 BRCA1 与 BRCA2）并克服对话混淆。第一个原型包含一个包含 500 个预定义问题和 67 个相应预定义答案的数据库，而最终版本包含 2257 个预定义问题和 144 个预定义答案。尽管聊天机器人的 AI 功能有限，但测试表明，用户喜欢布局，并认为聊天机器人值得信赖且易于阅读。
使用当今的技术构建健康聊天机器人具有挑战性、昂贵且耗时。如果由医疗保健人员提供，用户对聊天机器人持积极态度，并愿意在现实生活中使用它。
我们在此提出了未来健康聊天机器人计划的框架。参与性方法与迭代方法相结合，确保在开发过程的每个层面都纳入了患者的观点。我们强烈建议在以患者为中心的健康创新中采用这种方法。
