Enhancing the Effectiveness of Community Health Workers to Reduce Cervical Cancer Disparities in African American Women

项目摘要/摘要 非裔美国女性被诊断为宫颈癌(CC)的可能性几乎是白人的两倍 女人。他们最初的临床表现也更负面，特征是更严重的发育不良变化和 晚期疾病。有鉴于此，黑人女性死亡的可能性也是女性的两倍多也就不足为奇了 从CC到白人女性的对比。更糟糕的是，无论肿瘤分期如何，这些存活率差异仍然存在。 在初步诊断时。事情不必是这样的。CC是完全可以预防的。 广泛接受HPV疫苗接种和遵守宫颈筛查指南(并进行适当的跟踪) 将几乎消除所有新的CC病例。不幸的是，只有42%的年轻成年黑人女性 接受了至少一剂HPV疫苗的白人女性的这一比例为52%。已更正自我报告数据 调查显示，只有58%的黑人女性遵守筛查指南，而白人女性的这一比例为73%。 在之前的试点工作中，我们为非裔美国人开发并测试了移动CC导航干预 女人。集成的基于Web的风险评估使我们的短信软件应用程序能够从 为每个用户的特定宫颈健康预防量身定做的视频和基于文本的消息 挑战。该原型包括3种类型的视频(有脚本的插曲、无脚本的同行叙事和 教育指导)和3种类型的短信(提醒、教育和支持)。可用性测试 强烈支持这种面向患者的干预措施的可行性和潜在有效性。 我们建议在这一试点工作的基础上，开发一个数字仪表盘，将我们的 移动导航干预和电子健康记录(EHR)。此集成套餐将用于 提供导航服务的社区卫生工作者(CHW)。这一新的分析工具将提供CHWS 在患者级别、病例级别和遭遇中实时显示其导航数据的统一图形化视图- 水平。所有导航数据都将依靠各种图形元素以可视方式呈现。 我们将招募16名目标终端用户，他们在一系列领域提供癌症预防导航服务 参加焦点小组的工作场所设置。参与者将被要求判断布局的充分性， 计划中的仪表板的结构和功能。此外，我们还将招聘高管、董事、 实施/项目经理，以及拥有上游或下游接触点的最终用户 个人面谈的电子健康记录工作流程(总计N=12)。这些讨论将集中在挑战和 将拟议的移动健康工具整合到电子病历工作流程中的机会。根据我们所学到的 这些小组和我们的专家顾问团队，然后我们将开发一个原型仪表板。什么时候 完成后，16个目标终端用户将返回进行可用性测试。可用性测试将包括完成一个 旨在模拟典型最终用户将如何体验的功能的一系列任务 开发仪表板。将评估三个可用性指标：效率、准确性和主观满意度。

PROJECT SUMMARY/ABSTRACT African American women are almost twice as likely to be diagnosed with cervical cancer (CC) as white women. Their initial clinical picture is also more negative, characterized by more severe dysplastic changes and later-stage disease. Given this, it is not surprising that Black women are also more than twice as likely to die from CC as compared to white women. Even worse, these survival disparities persist irrespective of tumor stage at initial diagnosis. It does not have to be this way. CC is completely preventable. Broad uptake of HPV vaccination and adherence to cervical screening guidelines (with proper follow-up) would virtually eliminate all new cases of CC. Unfortunately, only 42% of young adult Black women have received at least one dose of the HPV vaccine compared to 52% of white women. Corrected self-report data show that only 58% of Black women are adherent to screening guidelines compared to 73% of white women. In previous pilot work, we developed and tested a mobile CC navigation intervention for African American women. An integrated web-based risk assessment allowed our SMS software app to select from a library of videos and text-based messages specifically tailored for each user’s particular cervical health prevention challenges. This prototype included 3 types of videos (scripted vignettes, unscripted peer narratives, and educational instruction) and 3 types of text messages (reminder, educational, and supportive). Usability testing strongly supported the feasibility and potential effectiveness of this patient-facing intervention. We are proposing to build on this pilot work by developing a digital dashboard that integrates with our mobile navigation intervention and with electronic health records (EHR). This integrated package will be for community health workers (CHWs) who provide navigation services. This new analytic tool will provide CHWs a unified, graphical view of their navigation data in real-time at the patient-level, case-level, and encounter- level. All navigation data will be presented visually, relying on a diverse array of graphical elements. We will recruit 16 target end-users who provide cancer prevention navigation services in a range of workplace settings to participate in focus groups. Participants will be asked to judge the adequacy of the layout, structure, and functionality of the planned dashboard. In addition, we will recruit executive leaders, directors, implementation/project managers, and end users who have either upstream or downstream touch points with EHR workflows for individual interviews (total N=12). These discussions will focus on the challenges and opportunities of integrating the proposed mHealth tools into EHR workflows. Based on what we learn from these groups and our expert team of consultants, we will then develop a prototype dashboard. When completed, the 16 target end-users will return for usability testing. The usability test will involve completing a series of tasks intended to simulate how a typical end-user would experience the functionality of the fully developed dashboard. Three usability metrics will be assessed: efficiency, accuracy, and subjective satisfaction.