Improving age-related risk assessment and documentation for diverse older adults with cancer

项目总结 Melody K Schiaffino，博士，公共卫生硕士，圣地亚哥州立大学终身教职助理教授， 放射医学和健康公平、教育和研究中心的核心教员 加州大学圣地亚哥分校转化科学教授，加州大学圣迭戈分校摩尔斯癌症中心准会员。Dr。 Schiaffino于2014年获得卫生服务研究博士学位，并于2008年获得流行病学公共卫生硕士学位。作为一名 健康差异系统科学家Schiaffino博士的目标是识别组织和提供者级别的风险 影响如何向接受癌症治疗的不同老年人提供护理的因素 最佳护理提供和治疗结果。老年人，特别是少数族裔，由于 癌症治疗的症状负担和治疗相关毒性风险较高。题为《改善环境》的提案 在被诊断为癌症的不同老年人中进行与年龄相关的风险评估和记录，寻求 检查导致对年龄相关风险的次优评估的提供者和文档障碍。年龄- 相关风险评估是一系列以证据为基础的临床测试和筛查，可以改善癌症 对于老年人的治疗计划，它对于经历语言障碍的老年人尤为突出。 目前对造成次优评估的机制研究不足， 放射肿瘤学中年龄相关风险的记录。虽然有证据支持改善沟通和 患者的癌症结局当评估与年龄相关的风险时，最近的临床试验结果显示，只有 4个供应商正在常规做法中实施这项评估。有效的评估就更少了 在有英语障碍的老年人中很常见。了解组织和提供商级别 对使用电子健康记录(EHR)的评估和记录做法的看法，以及 定性地采访和观察肿瘤学家，将有助于为未来的临床工作流程重新设计提供信息。这个 拟议的职业发展和培训计划支持Schiaffino博士成为 独立的、老化的系统科学家通过以下三个目标：1)获得先进的自然 从电子病历提取非结构化文本的语言处理(NLP)算法开发培训，2) 参与老年肿瘤护理服务的观察和培训，了解临床工作流程 以及围绕年龄相关风险评估的临床实践，以及3)获得临床工作流程方面的经验 实施科学建议的制定。该项目将在南加州大学、加州大学圣迭戈分校和加州大学伯克利分校 霍普(加利福尼亚州杜阿尔特)与老年医学/老年学专家导师(主要：艾莉森·摩尔，医学博士，硕士)； 放射肿瘤学/高铁(共同主修：James Murphy，MD，MS，UCSD)；老年肿瘤学/决策 (导师：William Dale，医学博士，希望之城)；NLP/生物信息学(导师：Mike Hogarth，医学博士，加州大学洛杉矶分校)； 预测模型/生物统计学(合作者：Barbara Bailey，PhD，SDSU)和临床实施科学 和有限的英语水平(LEP)差距(合作者：Alicia Fernandez，医学博士，加州大学旧金山分校)

PROJECT SUMMARY Melody K Schiaffino, PhD, MPH is a tenure-track Assistant Professor at San Diego State University (SDSU), a core faculty member in the Center for Health Equity, Education, and Research in Radiation Medicine and Translational Science at UC San Diego, and Associate Member of the UCSD Moores Cancer Center. Dr. Schiaffino received her PhD in Health Services Research in 2014 and MPH in Epidemiology in 2008. As a health disparities systems scientist, Dr. Schiaffino’s goals are to identify organizational and provider-level risk factors that affect how care is delivered to diverse older adults undergoing treatment for cancer to improve sub- optimal care delivery and treatment outcomes. Older, specifically minority, adults are at greater risk due to the higher symptom burden and treatment-related toxicity risk of cancer therapy. The proposal entitled, Improving age-related risk assessment and documentation in diverse older adults diagnosed with cancer, seeks to examine provider and documentation barriers that result in sub-optimal assessment of age-related risk. Age- related risk assessments are a series of evidence based clinical tests and screening that can improve cancer treatment planning for older adults, it is especially salient for older adults experiencing language barriers. There is currently insufficient research on the mechanisms contributing to sub-optimal assessment and documentation of age-related risk in radiation oncology. While evidence supports improved communication and cancer outcomes for patients when age-related risk is assessed, recent clinical trial findings show that only 1 in 4 providers are implementing this assessment in routine practice. Effective assessments are even less common in older adults with English language barriers. Understanding organizational and provider-level perspectives on assessment and documentation practices using electronic health records (EHRs), and qualitatively interviewing and observing oncologists, will help inform future clinic workflow redesign. The proposed career development and training plan supports Dr. Schiaffino’s trajectory toward becoming an independent, aging-systems scientist through the following three goals: 1) Obtain advanced natural language processing (NLP) algorithm development training to extract unstructured text from EHRs, 2) Engage in observation and training in geriatric oncology care delivery, to understand clinical workflow and clinical practices around assessment of age-related risk, and 3) Gain experience in clinical workflow implementation science proposal development. This project will take place at SDSU, UCSD, and City of Hope (Duarte, CA) with mentors who are experts in Geriatrics/Gerontology (Primary: Alison Moore, MD, MS); Radiation Oncology/HSR (Co- Primary: James Murphy, MD, MS, UCSD); Geriatric Oncology/ Decision-Making (Mentor: William Dale, MD, PhD, City of Hope); NLP/Bioinformatics (Mentor: Mike Hogarth, MD, UCSD); Predictive Models/Biostatistics (Collaborator: Barbara Bailey, PhD, SDSU) and clinical implementation science and Limited English Proficiency (LEP) disparities (Collaborator: Alicia Fernandez, MD, UCSF).