Improving dermatology access by direct-to-patient teledermatology and computer-assisted diagnosis

通过直接面向患者的远程皮肤病学和计算机辅助诊断改善皮肤病学的可及性

• 批准号: 10317682
• 负责人: DENNIS H OH
• 金额: --
• 依托单位: VETERANS AFFAIRS MED CTR SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10317682
• 关键词: Address; Appointment; Area; Artificial Intelligence; Benchmarking; Caring; Categories; Client satisfaction; Clinic; Collaborations; Communities; Computer Assisted; Computer Vision Systems; Computer-Assisted Diagnosis; Computers; Consult; Consultations; Data; Dermatologic; Dermatologist; Dermatology; Diagnosis; Diagnostic; Evaluation; Foundations; Future; Geography; Goals; Health Personnel; Health system; Home; Hybrids; Image; Improve Access; Intervention; Interview; Leadership; Link; Measures; Mediating; Medical; Methodology; Methods; Modeling; Nevi and Melanomas; Outcome; Pathway interactions; Patient Care; Patients; Performance; Persons; Positioning Attribute; Primary Health Care; Process; Quality of Care; Readiness; Recommendation; Recording of previous events; Research Design; Role; Secure; Self-Direction; Site; Skin; Skin Care; Surveys; System; Technology; Testing; Time; Training; Travel; Triage; United States Department of Veterans Affairs; Veterans; Vision; Wait Time; comparison intervention; connected care; data warehouse; digital imaging; experience; follow-up; health care service organization; improved; innovation; innovative technologies; mHealth; medical specialties; military veteran; mobile application; novel coronavirus; organizational readiness; pandemic disease; programs; prospective; rapid diagnosis; remote health care; satisfaction; skin disorder; teledermatology; telehealth; tool; treatment as usual; willingness

Background: Access to dermatology remains a significant problem in the Department of Veterans Affairs (VA), particularly during the COVD-19 pandemic. To address this need, VA will deploy an asynchronous teledermatology mobile app-My VA Images-which allows new dermatology patients to securely submit history and photos of their skin for evaluation. The app may also eventually provide a conduit for patients to submit skin images at will for analysis and triage by artificial intelligence (AI)-powered computer vision to a dermatologist. Significance: This project addresses the following gaps: 1) The impact of direct-to-patient teledermatology on access to dermatology and on the satisfaction with such care by both patients and health care providers has not been systematically studied; 2) Currently no AI-powered computer vision tool has been developed and validated for patient-generated images; 3) The readiness of large healthcare organizations, such as VA, and their stakeholders to engage in direct-to-patient teledermatology and AI is unknown. Innovation and Impact: Two related innovations will be tested: 1) Direct-to-patient teledermatology for new patients and 2) Evaluation of patient-submitted skin images by AI-powered computer vision. These separately have the potential to transform remote access to expert skin care in VA and together are potentially synergistic. At the conclusion of the project, we anticipate having a systematic understanding of how direct-to-patient technologies perform and of the operational gaps that will need to be addressed by VA before these technologies can be implemented enterprise-wide. The goal is to establish a critical scholarly and operational foundation to safely move toward a transformative vision where Veterans will no longer be tied to a fixed time and place for care, but instead will have the choice of self-directed, convenient and rapid access to expert-level dermatology care wherever and whenever they need it. Specific Aims: 1. Assess the impact of direct-to-patient teledermatology on access and health system utilization. 2. Assess, refine and augment computer-assisted evaluation of patient-submitted images. 3. Assess readiness of VA and Veterans' acceptance to implement direct-to-patient care. Methodology: Aim 1 will use a Type I hybrid pragmatic study design to compare the impact of the direct-to- patient teledermatology intervention relative to usual in-person and usual consultative teledermatology referrals, measuring access chiefly by data from VA's Central Data Warehouse. Aims 1 and 3 will measure patient satisfaction and readiness for change using survey instruments and interviews. Aim 2 will include both testing, training and refinement of the AI-powered computer vision and measure concordance with dermatologists. Population: Veterans referred to Dermatology at three VA medical facilities. Intervention: Eligible and medically appropriate patients will be offered the option to submit history and images to Dermatology using the My VA Images app. Comparison: The intervention will be compared to usual care (in- person and consultative teledermatology) groups. We will also compare two AI-powered computer vision models with dermatologist diagnoses. Outcomes over a 5-year period: 1) Multiple measures of temporal and geographic access to dermatologic care; 2) Patient satisfaction; 3) Concordance of AI with dermatologist diagnoses; 4) Organizational and patient-readiness for remote and computer-assisted dermatologic care; and 5) Implementation and sustainability of the direct-to-new patient teledermatology process. Next Steps/Implementation: Successful completion of the project will provide VA’s Office of Connected Care and other offices tasked with enhancing access to specialty care with critical data that will justify further expansion of the direct-to-patient asynchronous teledermatology program. The project will also provide VA with critical data to evaluate the role of AI-powered computer vision in future remote care strategies.

背景：获得皮肤科治疗仍然是退伍军人事务部的一个重大问题 (VA)，特别是在 COVD-19 大流行期间，为了满足这一需求，VA 将部署异步系统。 远程皮肤科移动应用程序 - My VA Images - 允许新皮肤科患者安全地提交病史 该应用程序还可能最终为患者提供提交的渠道。 通过人工智能 (AI) 驱动的计算机视觉随意分析和分类皮肤图像 皮肤科医生。 意义：该项目解决了以下空白：1) 直接面向患者的远程皮肤病学对 获得皮肤科治疗的机会以及患者和医疗保健提供者对此类护理的满意度 2）目前还没有开发出人工智能驱动的计算机视觉工具 验证患者生成的图像；3) 大型医疗机构（例如 VA）的准备情况； 他们的利益相关者是否参与直接面向患者的远程皮肤病学和人工智能尚不清楚。 创新和影响：将测试两项相关创新：1）直接面向患者的远程皮肤病学 患者；2) 通过人工智能计算机视觉评估患者提交的皮肤图像。 有潜力改变弗吉尼亚州对专家皮肤护理的远程访问，并且在一起具有潜在的协同作用。 在项目结束时，我们期望能够系统地了解如何直接面向患者 技术性能以及 VA 在此之前需要解决的运营差距 技术可以在整个企业范围内实施，目标是建立一个关键的学术和可操作的体系。 安全地迈向变革性愿景的基础，让退伍军人不再受固定时间的束缚 和地点的护理，而是可以选择自主、方便、快速地获得专家级的帮助 随时随地为他们提供皮肤科护理。 具体目标： 1. 评估直接面向患者的远程皮肤科对获取和卫生系统的影响 2. 评估、完善和增强对患者提交的图像的计算机辅助评估。 3. 评估 VA 的准备情况和退伍军人对实施直接面向患者护理的接受程度。 方法论：目标 1 将使用 I 类混合实用研究设计来比较直接对 相对于通常的面对面和通常的咨询式远程皮肤病学的患者远程皮肤病学干预 推荐，主要通过 VA 中央数据仓库的数据来衡量访问情况，目标 1 和 3 将进行衡量。 目标 2 将包括使用调查工具和访谈来提高患者满意度和变革准备度。 测试、训练和完善人工智能驱动的计算机视觉并测量与 人群：退伍军人在三个 VA 医疗机构进行皮肤科治疗。 符合条件且医学上适当的患者将可以选择将病史和图像提交给 使用“我的 VA 图像”应用​​程序的皮肤科比较：干预措施将与常规护理进行比较（在- 我们还将比较两个人工智能驱动的计算机视觉。 5 年期间皮肤科医生诊断结果的模型：1) 时间和时间的多重测量。 获得皮肤科护理的地理范围；2) 患者满意度；3) 人工智能与皮肤科医生的一致性； 诊断；4) 组织和患者为远程和计算机辅助皮肤病护理做好准备； 5) 直接面向新患者的远程皮肤病学流程的实施和可持续性。 后续步骤/实施：该项目的成功完成将为 VA 的互联护理办公室提供服务 和其他负责通过关键数据加强获得专业护理的办公室，这些数据将进一步证明合理性 该项目还将扩大直接面向患者的异步远程皮肤科项目。 使用关键数据来评估人工智能驱动的计算机视觉在未来远程护理策略中的作用。