Improving Access Through Targeted Delivery of Telemedicine

背景：改善获得护理的机会是退伍军人事务部的高度优先事项。虽然对Access的改进有 尽管近年来取得了一些进展，但仍然存在差距和效率低下的问题，特别是在错过就诊时间方面。 显示‘。退伍军人管理局报告说，大约15%-18%的预定门诊初级保健预约没有 已完成，2017财年因缺席而损失了920万个预约。在前期工作中， 我们论证了社会风险因素对退伍军人事务部缺勤率的重要性。这些发现表明，不- 结合患者水平因素的Show预测模型可以预测漏诊率并提供 退伍军人的临床表型(即退伍军人社会脆弱性的综合描述)最多 不露面的风险。VA Video Connect(VVC)是一种新开发的远程医疗应用程序，可提供视频 会议服务作为连接退伍军人及其退伍军人医疗提供者的一种手段。VVC，退伍军人 可以从任何移动或基于网络的设备(例如智能手机、平板电脑或计算机)访问其退伍军人管理局提供商 不需要位于卫星诊所。以前的工作支持VVC可以作为目标的想法 那些没有预约就诊的风险较高的人。此CDA建议基于风险、有针对性地使用 VVC在社会脆弱患者中作为减少临床缺勤的一种手段。 意义：这项提案旨在通过识别、描述和吸引退伍军人来改善获得护理的机会 谁将从其他初级保健方法中受益最大，特别是VA Video Connect。 创新：本研究有几个方面的创新。首先，我们将利用机器学习预测 根据退伍军人的社会风险识别和描述退伍军人缺席风险最高的技术。 这种方法从来没有被用来解决缺席问题。二是积极做好退役军人工作 在关于如何优化使用VVC作为获得初级教育的替代方法的形成性评估中 关心。让退伍军人在整个提案中参与进来将确保退伍军人的声音适当地融入 最终的产品。最后，该建议利用新的远程医疗技术(即VVC)作为一种手段 改善错过诊所的高风险退伍军人的就诊机会。 具体目标和方法：(1)根据退伍军人的表型特征，采用回归树分析方法 未出席诊所预约的估计风险。假设：社会风险因素与NO- 与非卧床VA人群和某些表型相比，未出现率更高 其他。(2)采用序贯探索性混合方法设计高招入伍表型退伍军人 评估退伍军人使用VVC的适宜性和能力。假设：确定 退伍军人的表型将得到VVC的最佳服务，而其他表型将需要更高的强度 初级保健计划或持续的面对面护理。(3)在50名退伍军人中试点定向使用VVC 在使用I型混合动力车的SFVA，没有出现初级保健诊所预约的风险 有效性--实施设计。我们将收集有关当地适应性的形成性实施数据， 可接受性和忠诚度。假设：VVC将是一种可接受的替代初级保健方式 退伍军人和供养者。 下一步：在有效实施这一CDA之后，我们将与业务合作伙伴(办公室)合作 互联医疗和远程医疗)，并对VVC的重点使用情况进行多站点评估 退伍军人错过诊所预约的风险很高。

Background: Improving access to care is a high priority within the VA. While improvements to access have been made in recent years, gaps and inefficiencies still exist, particularly around missed clinic visits, or `no- shows'. The VA reports that approximately 15-18% of scheduled outpatient primary care appointments are not completed and that 9.2 million appointments were lost because of no-shows in FY2017. In preliminary work, we demonstrated the importance of social risk factors on VA no-show rates. These findings suggest that a no- show prediction model that incorporates patient-level factors could predict missed clinic rates and provide clinical phenotypes (i.e. an aggregate description of a Veterns' social vulnerabilities) of Veterans at greatest risk of no-showing. VA Video Connect (VVC) is a newly developed telemedicine application that provides video conferencing services as a means to connect Veterans with their VA medical providers. With VVC, Veterans can access their VA provider from any mobile or web-based device (e.g. smartphone, tablet, or computer) and do not need to be located at a satelite clinic. Previous work supports the idea that VVC could be targeted to those at elevated risk of no-showing clinic appointments. This CDA proposes a risk-based, targeted use of VVC in patients with social vulnerabilities as a means of decreasing clinic no-shows. Significance: This proposal aims to improve access to care by identifying, describing and engaging Veterans who would most benefit from alternative methods of primary care, specifically VA Video Connect. Innovation: This research has several innovative aspects to it. First, we will utilize machine-learning predictive techniques to identify and describe Veterans who are at highest risk of no-showing based on their social risk. This methodology has never been utilized in addressing no-shows. Second, we will actively engage Veterans in a formative assessment of how to optimize the use of VVC as an alternative method to obtaining primary care. Engaging Veterans throughout this proposal will ensure that Veterans' voices are properly integrated into the final product. Finally, this proposal utilizes novel telemedicine technologies (i.e. VVC) as a means of improving access for Veterans who are at high risk of missing clinic visits. Specific Aims & Methodology: (1) Use regression tree analysis to phenotype Veterans based on their estimated risk of no-showing clinic appointments. Hypothesis: Social risk factors are associated with no- shows in the ambulatory VA population and certain phenotypes will have higher no-show rates compared to others. (2) Use a sequential exploratory mixed methods design to engage phenotyped Veterans at high risk for no-showing and assess Veteran suitability and capability of using VVC. Hypothesis: Certain phenotypes of Veterans will be optimally served by VVC, while other phenotypes will require higher intensity primary care programs or continued in-person care. (3) Pilot the targeted use of VVC among 50 Veterans at-risk of no-showing primary care clinic appointments at the SFVA using a Type I hybrid effectiveness-implementation design. We will collect formative implementation data about local adaptability, acceptability, and fidelity. Hypothesis: VVC will be an acceptable alternative modality of primary care for both Veterans and providers. Next Steps: Following the effective implementation of this CDA, we will work with operational partners (Office of Connected Care and Telehealth) and perform a multisite assessment of the focused use of VVC on Veterans at high risk of missing clinic appointment.