Provider and Patient-generated Remote Oro-Dental Health Electronic Data Capture for Algorithmic Longitudinal Evaluation and Risk-Assessment (PROHEALER)

项目摘要/摘要 研究。口腔和口咽癌(OC/OPC)在美国困扰着超过53,000人 每年一次。尽管在肿瘤治疗方面取得了进步，但大多数患者将经历显著的 治疗期间和治疗后的毒性负担，包括中-重度口干、吞咽困难、口腔缩小 张口(即三叉神经)、牙周病和放射性骨坏死。远程电子症状监测 通过患者报告结果的标准化评估工具(EPROS)是基于证据的最佳 实践，特别是在新冠肺炎时代，但很少有临床实践证明 落实努力。到目前为止，困扰OC/OPC幸存者的急性和慢性口腔并发症有 主要基于经验性知识进行管理，并基于提供商提供广泛的跨提供商管理变异性 经验和可用的临床信息通常是不完整、不正确或不存在的。因此， 专业人士电子数据采集的标准化和提供者评估口腔的客观措施 毒性严重性仍然是一个未得到满足的公共卫生需求。我们的中心假设是同步优化 机器可读的患者和提供者生成的数据收集可以通过以下方式实现 纵向或系统ePRO数据收集的有效执行战略(目标1)和创建 用于在电子健康和牙科记录中准确报告口腔毒性的新牙科标准(AIM 2)。作为目标2的一个子组成部分，我们还将设计和试行一种新的放射牙片，以加强治疗 提供商之间的通信。治疗后高发病率、高患病率患者的准确风险预测 使用来自AIMS 1和2的高质量电子数据的口腔后遗症将被纳入统计 基于机器学习的稳健模型(目标3)。总而言之，PROHEALER提案促进了创新和 用于数据驱动的风险评估和算法预防和管理的新信息学方法 与治疗相关的口腔健康疾病困扰着OC/OPC幸存者。 职业发展与培训。莫雷诺博士的首要目标是成为国际公认的 具有先进放射治疗技术领域专业知识的独立研究调查员，临床 信息学和严格的毒性建模方法，因为它们与提高患者的生活质量和 促进口腔并发症的精准预防和风险干预。这份提案提出了 莫雷诺博士的5年指导职业发展计划，其中包括来自知名企业的指导 致力于监督拟议项目进展的NIH调查人员和莫雷诺博士的 全面的职业发展。概述的培训活动以莫雷诺博士的临床专业知识为基础 头颈癌放射肿瘤学家和她先前在EHR效用增强方面的工作 以牙科领域知识扩展为重点的综合性教学和基于项目的课程 风险预测建模中的信息学、实施科学和高级统计方法。

PROJECT SUMMARY/ABSTRACT Research. Oral cavity and oropharyngeal (OC/OPC) cancers afflict more than 53,000 individuals in the United States annually. Despite advancements in oncologic therapies, the majority of patients will experience significant toxicity burden during and after therapy, including moderate-severe xerostomia, dysphagia, reduced mouth opening (i.e. trismus), periodontal disease, and osteoradionecrosis. Remote electronic symptom monitoring through standardized assessment tools for patient reported outcomes (ePROs) is an evidence-based best practice, particularly in the COVID-19 era, yet few clinical practices have demonstrated sustainability of implementation efforts. To date, acute and chronic orodental complications afflicting OC/OPC survivors are largely managed on empirical knowledge with wide inter-provider management variability based on provider experience and available clinical information which is often incomplete, incorrect, or nonexistent. Therefore, standardization of electronic data capture of PROs and objective measures of provider-assessed orodental toxicity severity remains an unmet public health need. Our central hypothesis is that synchronous optimization of machine-readable patient- and provider-generated data collection can be achieved through prioritization of effective implementation strategies for longitudinal oro-systemic ePRO data collection (Aim 1) and creation of novel dental standards for accurate orodental toxicity reporting in both electronic health and dental records (Aim 2). As a subcomponent to Aim 2, we will also design and pilot a novel radiation odontogram to enhance treatment communication between providers. Accurate risk predictions of high-morbidity high-prevalence post-therapy orodental sequelae using high-quality electronic data from Aims 1 and 2 will be incorporated into a statistically robust machine-learning based model (Aim 3). In summary, the PROHEALER proposal fosters innovative and novel informatics approaches for data-driven risk assessment and algorithmic prevention and management of treatment-related oral health diseases afflicting OC/OPC survivors. Career Development & Training. Dr. Moreno's overarching goal is to become an internationally recognized independent research investigator with domain expertise in advanced radiation therapy techniques, clinical informatics and rigorous toxicity modeling methodologies as they pertain to improving patient quality of life and promoting precision prevention and risk-based interventions for orodental complications. This proposal presents Dr. Moreno's 5-year mentored career development plan which includes mentorship from prominent Established NIH Investigators who have committed to overseeing the progress of the proposed projects and Dr. Moreno's overall professional development. The outlined training activities build upon Dr. Moreno's clinical expertise as a Head and Neck Cancer Radiation Oncologist and her prior work in EHR utility enhancement with the inclusion of a comprehensive didactic and project-based curriculum focused on domain knowledge expansion in dental informatics, implementation science, and advanced statistical methods in risk prediction modeling.