Assessing the effectiveness of a digital platform to support the mental health of healthcare workers in the response and recovery phases of COVID-19

新型冠状病毒(新冠肺炎)从根本上改变了医疗保健的提供，并显著影响了 个人和社区的心理健康。医疗保健对心理健康的影响 在大流行的各个阶段，工作人员都特别紧张。这种影响是 预计对所有人都是慢性的和普遍的，特别是对受影响不成比例的代表不足的人 少数民族和女性人口。迫切需要开发和测试可扩展的数字方法，该方法 可以识别、解决和支持医护人员(HCW)的福利 大流行。卫生工作者很忙，与获得心理健康支持有关的耻辱。我们寻求 利用数字平台简化对关注福祉的资源的访问，并直接连接到 心理健康提供者通过使用阶梯式护理模式的实时支持。在…的急性期 在大流行期间，我们的团队开发并在整个宾夕法尼亚医疗卫生系统中实施了宾夕法尼亚钴。 Cobalt是一个基于Web和文本消息的平台，允许卫生工作者完成上下文调查和 在他们自己的时间远程进行基于证据的评估。然后，个人被引导到量身定做的幸福中 资源和适当的个人或团体精神保健。在整个宾夕法尼亚医学院，在短短7个月内， Cobalt拥有18,300名独立用户，并已确定111名保健工作者报告有自我伤害和 立即将这些人与精神健康提供者联系起来，以获得支持和评估。而钴 保持了高度的参与度，并提高了卫生系统识别高危个人的能力，它 需要有积极性的用户。个人必须将关怀“拉”向他们，并克服多种障碍 从确定精神健康支持的需求，到预约和参加预约。 我们 寻求评估一种主动吸引个人参与的“推式”护理模式(Cobalt)是否可以 改善个人心理健康、对准入的满意度，并减少影响劳动力的因素 生产力(例如缺勤)。具体目标将通过随机对照试验评估 钴对HCW抑郁/焦虑的疗效(主要结果)与钴(常规护理)的比较。 次要结果将包括幸福感、对获得护理的满意度和工作衡量标准。 生产力。将探索不同种族和性别的治疗效果。此外，我们将寻求 更好地了解人们对获得精神卫生保健的看法以及与 通过半结构化定性访谈对医务人员中的钴进行调查。总体而言，这个项目寻求解决一个 显著差距，并加强妇幼保健人员获得和接受侧重于精神健康和福祉的资源 关心。我们的目的是建立一种积极主动的文化，为老年人提供福祉和心理健康支持 在大流行的多个阶段期间的医疗工作人员。我们的方法评估现有的数字 这些模型可以及时执行，并可快速扩展以供其他卫生系统使用。

The novel coronavirus (COVID-19) has radically changed the delivery of healthcare and significantly impacted the mental health of individuals and communities. The effect upon the mental health of the healthcare workforce has been particularly strained throughout the various phases of the pandemic. This impact is predicted to be chronic and pervasive for all and particularly for disproportionately affected underrepresented minority and female populations. There is a critical need to develop and test scalable digital approaches which can identify, address and support the well-being of healthcare workers (HCW) over time and beyond the pandemic. HCWs are busy and there is stigma associated with accessing mental health support. We seek to leverage digital platforms to facilitate ease of access to well-being focused resources and direct connection to mental health providers through real time support using a stepped model of care. During the acute phase of the pandemic, our team developed and implemented Penn Cobalt across the Penn Medicine health system. Cobalt is a web and text-message based platform which allows HCWs to complete contextual surveys and evidence-based assessments remotely on their own time. Individuals are then directed to tailored well-being resources and appropriate individual or group mental healthcare. Across Penn Medicine, and in just 7 months, Cobalt has had 18,300 unique users and has identified 111 HCWs reporting thoughts of self-harm and immediately connected those individuals with a mental health provider for support and evaluation. While Cobalt has had sustained high engagement and increased the health system's ability to identify high-risk individuals, it requires a motivated user. Individuals must “pull” care toward them and overcome multiple barriers ranging from identifying the need for mental health support, to making an appointment, and attending the appointment. We seek to evaluate whether a “pushed” model of care (Cobalt+), which proactively engages individuals, can improve individual mental health, satisfaction with access, and decrease factors which affect workforce productivity (e.g. absenteeism). The specific aims will evaluate, through a randomized controlled trial, the effectiveness of Cobalt+ on HCW depression/anxiety (primary outcome) compared with Cobalt (usual care). Secondary outcomes will include well-being, satisfaction with access to care, and measures of work productivity. Heterogeneous treatment effects will be explored for race and gender. Additionally, we will seek to better understand perceptions of access to mental health care and the effectiveness of Cobalt compared with Cobalt among HCWs through semi-structured qualitative interviews. Overall, this project seeks to address a significant gap and enhance HCW access and receipt of mental health and well-being focused resources and care. Our intent is that this will enable a proactive culture of well-being and mental health support for the healthcare workforce during the multiple phases of the pandemic. Our approach evaluates existing digital models which can be executed in a timely fashion and rapidly scaled for use across other health systems.