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：在退伍军人事务部中，使用皮肤病仍然是一个重大问题 （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 TelederMatology移动应用程序MY VA Images-允许新的皮肤病患者安全提交历史记录 和他们的皮肤照片以进行评估。该应用程序有时也可能为患者提交的管道 随意通过人工智能（AI）能力的计算机视觉分析和分类的皮肤图像 皮肤科医生。 意义：该项目解决以下差距：1）直接到患者的远程表现对 患者和医疗保健提供者都可以使用皮肤病学并满足于这种护理 没有系统地研究； 2）目前尚未开发AI驱动的计算机视觉工具，并且 已验证用于患者生成的图像； 3）大型医疗机构（例如VA）的准备就绪 他们的利益相关者参与直接远程远程表现和人工智能，这是未知的。 创新和影响：将测试两项相关的创新：1）直接到患者的新型创新 患者和2）通过AI驱动的计算机视觉评估患者提取的皮肤图像。这些分别 有可能转变在VA中远程获得专家皮肤护理的访问，并共同具有协同作用。 在项目结束时，我们预计对直接对象有系统的了解 技术执行以及在这些方面需要解决的操作差距 技术可以在企业范围内实施。目标是建立批判性科学和运营 基础安全地朝着变革性的愿景迈进，退伍军人将不再与固定时间联系在一起 和护理的地方，但可以选择自我指导，方便和快速进入专家级别 无论何时何地，皮肤病学关怀。 具体目的：1。评估直接到患者的远程表现对访问和卫生系统的影响 利用率。 2。评估，完善和增强计算机辅助评估的患者图像。 3.评估VA和退伍军人接受直接护理的准备就绪。 方法论：AIM 1将使用I型混合务实研究设计来比较直接的影响 患者相对于通常的面对面和通常的咨询远程表相的静态性干预 转介，主要通过VA中央数据仓库的数据来衡量访问。目标1和3将测量 使用调查工具和访谈的患者满意度和准备就绪。 AIM 2将包括 AI驱动的计算机视觉和测量协调的测试，培训和完善 皮肤科医生。人口：退伍军人提到三个VA医疗设施的皮肤病学。干涉： 符合条件和医学上适当的患者将被选出将历史和图像提交给 使用我的VA图像应用的皮肤病学。比较：将干预措施与通常的护理（IN- 人和咨询远程手学）小组。我们还将比较两个AI驱动的计算机视觉 具有皮肤科医生诊断的模型。在5年内的成果：1）临时和 地理访问皮肤科护理； 2）患者满意度； 3）AI与皮肤科医生的一致性 诊断; 4）远程和计算机辅助皮肤病学护理的组织和患者准备；和 5）直接向新患者远程表现过程的实施和可持续性。 下一步/实施：成功完成该项目将为VA的Connected Care办公室提供 和其他任务是通过关键数据增强专业护理访问权限的办公室，这将证明进一步合理 直接到患者异步远程表静态学计划的扩展。该项目还将提供VA 使用关键数据来评估AI驱动的计算机视觉在未来的远程护理策略中的作用。