PDF(Pubmed)
Abstract：
During the COVID-19 pandemic, health care systems were faced with the urgent need to implement strategies to address the behavioral health needs of health care workers. A primary concern of any large health care system is developing an easy-to-access, streamlined system of triage and support despite limited behavioral health resources.
This study provides a detailed description of the design and implementation of a chatbot program designed to triage and facilitate access to behavioral health assessment and treatment for the workforce of a large academic medical center. The University of California, San Francisco (UCSF) Faculty, Staff, and Trainee Coping and Resiliency Program (UCSF Cope) aimed to provide timely access to a live telehealth navigator for triage and live telehealth assessment and treatment, curated web-based self-management tools, and nontreatment support groups for those experiencing stress related to their unique roles.
In a public-private partnership, the UCSF Cope team built a chatbot to triage employees based on behavioral health needs. The chatbot is an algorithm-based, automated, and interactive artificial intelligence conversational tool that uses natural language understanding to engage users by presenting a series of questions with simple multiple-choice answers. The goal of each chatbot session was to guide users to services that were appropriate for their needs. Designers developed a chatbot data dashboard to identify and follow trends directly through the chatbot. Regarding other program elements, website user data were collected monthly and participant satisfaction was gathered for each nontreatment support group.
The UCSF Cope chatbot was rapidly developed and launched on April 20, 2020. As of May 31, 2022, a total of 10.88% (3785/34,790) of employees accessed the technology. Among those reporting any form of psychological distress, 39.7% (708/1783) of employees requested in-person services, including those who had an existing provider. UCSF employees responded positively to all program elements. As of May 31, 2022, the UCSF Cope website had 615,334 unique users, with 66,585 unique views of webinars and 601,471 unique views of video shorts. All units across UCSF were reached by UCSF Cope staff for special interventions, with >40 units requesting these services. Town halls were particularly well received, with >80% of attendees reporting the experience as helpful.
UCSF Cope used chatbot technology to incorporate individualized behavioral health triage, assessment, treatment, and general emotional support for an entire employee base (N=34,790). This level of triage for a population of this size would not have been possible without the use of chatbot technology. The UCSF Cope model has the potential to be scaled, adapted, and implemented across both academically and nonacademically affiliated medical settings.
This study provides a detailed description of the design and implementation of a chatbot program designed to triage and facilitate access to behavioral health assessment and treatment for the workforce of a large academic medical center. The University of California, San Francisco (UCSF) Faculty, Staff, and Trainee Coping and Resiliency Program (UCSF Cope) aimed to provide timely access to a live telehealth navigator for triage and live telehealth assessment and treatment, curated web-based self-management tools, and nontreatment support groups for those experiencing stress related to their unique roles.
In a public-private partnership, the UCSF Cope team built a chatbot to triage employees based on behavioral health needs. The chatbot is an algorithm-based, automated, and interactive artificial intelligence conversational tool that uses natural language understanding to engage users by presenting a series of questions with simple multiple-choice answers. The goal of each chatbot session was to guide users to services that were appropriate for their needs. Designers developed a chatbot data dashboard to identify and follow trends directly through the chatbot. Regarding other program elements, website user data were collected monthly and participant satisfaction was gathered for each nontreatment support group.
The UCSF Cope chatbot was rapidly developed and launched on April 20, 2020. As of May 31, 2022, a total of 10.88% (3785/34,790) of employees accessed the technology. Among those reporting any form of psychological distress, 39.7% (708/1783) of employees requested in-person services, including those who had an existing provider. UCSF employees responded positively to all program elements. As of May 31, 2022, the UCSF Cope website had 615,334 unique users, with 66,585 unique views of webinars and 601,471 unique views of video shorts. All units across UCSF were reached by UCSF Cope staff for special interventions, with >40 units requesting these services. Town halls were particularly well received, with >80% of attendees reporting the experience as helpful.
UCSF Cope used chatbot technology to incorporate individualized behavioral health triage, assessment, treatment, and general emotional support for an entire employee base (N=34,790). This level of triage for a population of this size would not have been possible without the use of chatbot technology. The UCSF Cope model has the potential to be scaled, adapted, and implemented across both academically and nonacademically affiliated medical settings.
摘要：
背景：在COVID-19大流行期间，卫生保健系统面临着迫切需要实施战略，以满足卫生保健工作者的行为健康需求。任何大型医疗保健系统的主要关注点是开发易于访问的，尽管行为健康资源有限，但简化的分诊和支持系统。本文详细描述了聊天机器人程序的设计和实现，该程序旨在为大型学术医疗中心的员工分类和促进行为健康评估和治疗。
目的：描述一个程序，该程序使用聊天机器人技术来满足大型学术医疗中心员工的行为健康需求。加州大学,旧金山（UCSF）应对计划旨在提供及时访问（1）实时远程健康导航仪，用于分诊和实时远程健康评估和治疗；（2）策划在线自我管理工具；3）为那些经历与他们独特角色相关的压力的非治疗支持小组。
方法：在公私伙伴关系中，UCSFCope团队建立了一个聊天机器人，根据行为健康需求对员工进行分类。聊天机器人是基于算法的，自动化,交互式人工智能对话工具，使用自然语言理解通过提供一系列带有简单多项选择答案的问题来吸引用户。每个聊天机器人会话的目标是引导用户使用适合其需求的服务。设计人员开发了Chatbot数据仪表板，以直接通过聊天机器人识别和跟踪趋势。关于其他程序元素，网站用户数据每月收集一次，每个非治疗支持组收集参与者满意度.
结果：UCSFCopeChatbot迅速开发并于2020年4月20日推出。截至2022年5月31日，10.9%(3,785/34,790)的员工使用了这项技术；在报告任何形式的心理困扰的人中，39.7%(708/1783)的员工要求亲自服务，包括那些有现有提供者的人。UCSF员工对所有计划要素都做出了积极的回应。截至2022年5月31日，UCSFCope网站拥有615,334个独立用户，拥有66,585个独特的网络研讨会视图，和601,471视频短裤的独特观点。UCSFCopystaffforspecialinterventions,有40多个单位要求这些服务。市政厅特别受欢迎，超过80％的与会者报告的经验是有益的。
结论：UCSFCope计划使用聊天机器人技术纳入个性化行为健康分类，评估，治疗,以及对整个员工基础的一般情感支持(N=34,790)。如果不使用聊天机器人技术，这种规模的人群的分类水平是不可能的。UCSFCope模型具有缩放的潜力，适应,并在学术和非学术附属医疗机构中实施。
目的：描述一个程序，该程序使用聊天机器人技术来满足大型学术医疗中心员工的行为健康需求。加州大学,旧金山（UCSF）应对计划旨在提供及时访问（1）实时远程健康导航仪，用于分诊和实时远程健康评估和治疗；（2）策划在线自我管理工具；3）为那些经历与他们独特角色相关的压力的非治疗支持小组。
方法：在公私伙伴关系中，UCSFCope团队建立了一个聊天机器人，根据行为健康需求对员工进行分类。聊天机器人是基于算法的，自动化,交互式人工智能对话工具，使用自然语言理解通过提供一系列带有简单多项选择答案的问题来吸引用户。每个聊天机器人会话的目标是引导用户使用适合其需求的服务。设计人员开发了Chatbot数据仪表板，以直接通过聊天机器人识别和跟踪趋势。关于其他程序元素，网站用户数据每月收集一次，每个非治疗支持组收集参与者满意度.
结果：UCSFCopeChatbot迅速开发并于2020年4月20日推出。截至2022年5月31日，10.9%(3,785/34,790)的员工使用了这项技术；在报告任何形式的心理困扰的人中，39.7%(708/1783)的员工要求亲自服务，包括那些有现有提供者的人。UCSF员工对所有计划要素都做出了积极的回应。截至2022年5月31日，UCSFCope网站拥有615,334个独立用户，拥有66,585个独特的网络研讨会视图，和601,471视频短裤的独特观点。UCSFCopystaffforspecialinterventions,有40多个单位要求这些服务。市政厅特别受欢迎，超过80％的与会者报告的经验是有益的。
结论：UCSFCope计划使用聊天机器人技术纳入个性化行为健康分类，评估，治疗,以及对整个员工基础的一般情感支持(N=34,790)。如果不使用聊天机器人技术，这种规模的人群的分类水平是不可能的。UCSFCope模型具有缩放的潜力，适应,并在学术和非学术附属医疗机构中实施。
