Can a novel telemedicine tool reduce disparities related to the identification of preschool children with autism?

新型远程医疗工具能否减少学龄前自闭症儿童识别方面的差异？

• 批准号: 10354317
• 负责人: Zachary E Warren
• 金额: $ 21.63万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-17 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10354317
• 关键词: Address; African American; Age; Age-Months; Agreement; Assessment tool; Attention; Behavior; Behavior Disorders; Behavioral; Blinded; COVID-19; COVID-19 pandemic; Caring; Child; Classification; Clinical; Computer Analysis; Data; Data Set; Decision Making; Development; Diagnosis; Diagnostic; Early Diagnosis; Early Intervention; Engineering; Evaluation; Evidence based intervention; Face; Family; Geography; Gold; Health Services Accessibility; Hispanic; Home; Improve Access; Investigation; Linguistics; Machine Learning; Measures; Methodology; Methods; Mining; Modeling; Nursery Schools; Parents; Performance; Persons; Phenotype; Play; Population; Preschool Child; Procedures; Process; Production; Property; Provider; Psychometrics; Registries; Reporting; Risk; Risk Assessment; Sampling; Scientist; Services; Socioeconomic Status; Specialist; Structural Racism; Structure; Symptoms; System; Target Populations; Techniques; Telemedicine; Testing; Time; Toddler; Translating; Underserved Population; Wait Time; Waiting Lists; Work; aged; aging population; autism spectrum disorder; autistic children; barrier to care; base; community clinic; design; diagnostic tool; disorder risk; disparity reduction; formative assessment; geographic barrier; health disparity; improved; innovation; novel; satisfaction; sound; telehealth; tertiary care; tool; tool development; underserved community; usability

PROJECT SUMMARY Families seeking evaluation for autism spectrum disorder (ASD) often face barriers such as low availability of specialists, lengthy waitlists, and long distances to tertiary care diagnostic centers. This is especially true for children from traditionally underserved groups and communities. Without innovative approaches for enhanced identification of ASD, families and clinicians will continue to struggle with accessing and providing care. Telemedicine offers tremendous potential for addressing this need, but there are few psychometrically sound, validated tools that can be administered remotely, via telehealth platforms, in order to guide service and action. Our team developed and conducted a preliminary evaluation of a novel parent-administered, clinician-guided tele-diagnostic tool, the TAP (TELE-ASD-PEDS), designed specifically for direct-to-home and community clinic use with toddlers. Remote administration of the TAP yielded a very high level of agreement with blinded comprehensive evaluation regarding ASD risk classification. Subsequently, the unanticipated broad dissemination of the TAP during COVID-19 demonstrated its value for traditionally underserved groups, spanning broad geographies. Although promising, this work was limited by its specific focus on toddlers with ASD concerns. A telemedicine tool designed for the unique context and population of preschool-aged children referred for diagnostic assessment could have tremendous value in terms of both accurate identification as well as family engagement with service. In the current work, we propose a computationally informed co-production in which we involve our targeted population as active partners in designing a new telemedicine tool, the TAP– Preschool, for ASD risk assessment in preschoolers. This approach will follow our innovative methodology for fusing advanced computational analyses with stakeholder expertise (1) by mining our large clinical registry to identify key ASD behavior targets and (2) rigorously translating these key behaviors to generate telehealth assessment techniques. With input from our computational experts, clinical scientists, and end-users, we will then evaluate the performance, usability, and utility of the TAP–Preschool. We will gather critical data not only regarding its structure and accuracy, but also its potential deployment across systems responsible for engaging children and families from underserved groups in meaningful service. This work has potential to transform the ASD evaluation process and dramatically improve care access for traditionally underserved groups.

项目摘要 寻求自闭症谱系障碍（ASD）评估的家庭通常面临障碍，例如 专家，漫长的等待名单，以及到三级医疗诊断中心的距离。更是如此 来自传统上得不到充分服务的群体和社区的儿童。如果没有创新的办法来加强 ASD的识别，家庭和临床医生将继续努力获得和提供护理。 远程医疗为满足这一需求提供了巨大的潜力，但几乎没有心理测量学上的声音， 经验证的工具，可通过远程保健平台远程管理，以指导服务和行动。 我们的团队开发并进行了一个新的家长管理，临床医生指导的初步评估， 远程诊断工具，TAP（TELE-ASD-PEDS），专为直接到家庭和社区诊所设计 使用toddlers。TAP的远程管理产生了非常高的一致性， 关于ASD风险分类的综合评估。随后，意想不到的广泛 在COVID-19期间传播TAP证明了其对传统上服务不足的群体的价值， 广泛的地理。虽然这项工作很有前途，但由于其具体关注的是患有ASD的幼儿， 性问题为学龄前儿童的独特环境和人群设计的远程医疗工具 转诊进行诊断评估在准确识别以及 家庭参与服务。在目前的工作中，我们提出了一个计算知情的共同生产 我们让目标人群作为积极的合作伙伴参与设计一种新的远程医疗工具，TAP， 学龄前，用于学龄前儿童ASD风险评估。这种方法将遵循我们的创新方法， 将先进的计算分析与利益相关者的专业知识融合在一起（1），通过挖掘我们的大型临床注册表， 确定关键ASD行为目标，以及（2）严格翻译这些关键行为以产生远程医疗 评估技术。通过我们的计算专家、临床科学家和最终用户的输入，我们将 然后评估TAP学前班的性能、可用性和实用性。我们不仅要收集关键数据， 关于它的结构和准确性，以及它在负责参与的系统之间的潜在部署， 来自得不到充分服务群体的儿童和家庭提供有意义的服务。这项工作有可能改变 ASD评估过程，并大大改善传统上服务不足的群体的护理机会。