Self-Monitoring Support Application for Adults with Diabetes and Hypertension

项目总结/摘要 该项目的目的是开发一个理论驱动的，语音激活的，可扩展的，移动健康干预， 促进并存糖尿病（DM）患者的自我管理和医患沟通， 高血压（HTN）。在3000万患有DM的美国人中，超过2000万人也患有HTN。自我- 慢性疾病的管理是一个有前途的战略，防止发展额外的共同， 减少疾病的发生，降低发病率和死亡率。自我监测健康指标（例如，血液 血压[BP]，葡萄糖）是成功自我管理的关键组成部分。通过自我监测，患者 可以识别健康指标的模式，获得更多的健康信息，并改变健康行为。 为了满足患有DM和HTN的个体的自我管理需求，我们建议开发 智能扬声器平台上的语音激活自我监控（VoiS）支持应用程序，包括三种类型 1）自我监控特征，包括语音激活数据输入（即，血糖和血压），智能笔记， 记录可能导致生物标志物异常值的生活方式相关事件，以及智能语音提醒; 2)临床决策支持功能，包括基于证据的知识库，带有用于DM和 HTN，以及3）共享决策功能，包括在多个平台上可视化患者数据，以及 在智能扬声器上对患者数据进行音频简报。 我们假设，DM和HTN并存的患者将使用方便的VoiS应用程序进行常规检查， 自我监测生物标志物和记录生活方式相关的事件。其他假设有：（1） VoiS应用程序生成的综合患者数据将帮助患者更好地了解其 条件;以及（2）通过VoiS应用程序共享患者生成的数据将有效地帮助患者和提供者 相互沟通，设定共同的目标，并选择个性化的护理计划，以促进遵守 治疗 在我们验证这种基于理论的mHealth自我管理干预的临床疗效之前，我们 首先，我们需要开发VoiS。因此，本研究的目的是1）开发VoiS应用程序，包括三个 功能;和2）测试VoiS应用程序在实验室和现场的可接受性和可用性， DM和HTN共存。这个项目的发现将加强我们对用户感知接受度的理解， 此外，调查结果将用于生成另一个R21 申请通过试点测试推进这项研究，以确定初步的临床疗效， 随机设计我们预计，该项目将有助于减少种族和社会经济差距 在自我监测和结果的糖尿病和HTN患者，表明延迟获得护理;和 为其他共存的代谢性慢性疾病的复制工作提供信息。

PROJECT SUMMARY/ABSTRACT The purpose of this project is to develop a theory-drien, voice-activated, scalable, mHealth intervention to promote self-management and patient-provider communication in patients with coexisting diabetes (DM) and hypertension (HTN). Among the 30 million Americans who have DM, more than 20 million also have HTN. Self- management of chronic conditions is a promising strategy for preventing the development of additional co- occurring diseases and resulting in reduced morbidity and mortality. Self-monitoring health indicators (e.g., blood pressure [BP], glucose) is a key component of successful self-management. Through self-monitoring, patients can recognize patterns in their health indicators, obtain more health information, and change health behaviors. To meet the self-management needs of individuals with comorbid DM and HTN, we propose to develop a voice-activated self-monitoring (VoiS) support application on a smart speaker platform that includes three types of fearues 1) self-monitoring features, including voice-activated data entry (i.e., glucose and BP), smart notes to record lifestyle-related episodes that could result in unusual values of biomarkers, and smart speech reminders; 2) clinical decision support features, including an evidence-based knowledge base with AI engine for DM and for HTN, and 3) shared decision-making features, including visualization of patient data on multiple platforms and an audio briefing of patient data on a smart speaker. We hypothesize that patients with coexisting DM and HTN will use the convenient VoiS app for routine self-monitoring of biomarkers and for recording lifestyle-related episodes. Other hypotheses are: (1) the synthesized patient data produced by the VoiS app will help patients better understand the status of their conditions; and (2) patient-generated data-sharing via the VoiS app will help patients and providers effectively communicate with each other, set shared goals, and choose personalized care plans to promote adherence to treatment. Before we can verify the clinical efficacy of this theory-based mHealth self-management intervention, we first need to develop the VoiS. Therefore, aims of this study are to 1) develop the VoiS app including the three features; and 2) test acceptability and usability of the VoiS app in the lab and in the field by patients with coexisting DM and HTN. Findings from this project will enhance our understanding of user-perceived acceptance, usability, and satisfaction with the VoiS app. Additionally, findings will be used to generate another R21 application to move this research forward through pilot testing to determine preliminary clinical efficacy using a randomized design. We anticipate that this project will contribute to reduce racial and socioeconomic disparities in self-monitoring and outcomes for patients with DM and HTN that are indicated by delayed access to care; and inform the replication of this work for other coexisting metabolilc chronic conditions.