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

改善不同老年癌症患者的年龄相关风险评估和记录

基本信息

批准号：
10371440
负责人：
Melody K Schiaffino
金额：
$ 13.7万
依托单位：
SAN DIEGO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-03-15 至 2027-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10371440
关键词：
Address Adult Affect Age Aging Algorithms American Award Bioinformatics Biometry Cancer Center Cancer Survivor Caring Cities Classification Clinic Clinical Clinical Data Clinical Trials Clinical assessments Communication Comprehensive Cancer Center Data Data Science Data Set Decision Making Development Diagnosis Disease Doctor of Philosophy Documentation Elderly Electronic Health Record English Language Ensure Epidemiology Face Faculty Future Geriatric Assessment Geriatrics Gerontology Goals Health Services Research Health Status Health system Interview K-Series Research Career Programs Knowledge Language Limited English Proficiency Location Machine Learning Malignant Neoplasms Medical Records Medicine Mentors Methods Minority Natural Language Processing Oncologist Oncology Outcome Patient-Focused Outcomes Patients Pattern Persons Prevalence Process Provider Quality of Care Radiation Radiation Oncology Research Research Personnel Risk Risk Assessment Risk Estimate Risk Factors Scientist Series Survivors Symptoms System Testing Text Time Training Translational Research Treatment outcome Treatment-related toxicity Uncertainty Universities Variant age effect age related algorithm development cancer care cancer health disparity cancer risk cancer therapy cancer type care coordination care delivery career career development clinical decision-making clinical examination clinical implementation clinical practice demographics education research evidence base experience health disparity health equity human old age (65+)implementation science improved information gathering medical specialties member older patient oncology program optimal treatments patient health information patient-clinician communication predictive modeling professor routine practice screening shared decision making skills tenure track tool treatment planning

项目摘要

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).

项目摘要 MELODY K SCHIAFFINE博士，MPH是圣地亚哥州立大学（SDSU）的终身助理助理教授卫生公平，教育和放射医学研究中心的核心教师加州大学圣地亚哥分校的转化科学，以及UCSD摩尔癌中心的副成员。 Schiaffino于2014年获得卫生服务研究博士学位，并于2008年获得流行病学的MPH。健康差异系统科学家，Schiaffino博士的目标是确定组织和提供商级别的风险影响护理如何交付给各种老年人的因素最佳的护理交付和信任结果。更高的症状负担和与治疗相关的毒物癌症的风险。与年龄有关的风险评估和诊断为癌症的老年人的文件检查提供者和文档障碍，这些障碍会导致对年龄相关风险的次优评估。相关的风险评估是一系列证据低音的临床测试和筛查对于老年人的治疗计划，对于遇到语言障碍的老年人特别重要。目前，这是对有助于次级评估的机制的足够的研究辐射肿瘤中与年龄相关的风险文件。评估与年龄相关的风险时，患者的癌症结局，最近的临床试验结果表明，1 4个提供者在常规练习中实施这种标题。在具有英语障碍的老年人中常见。使用电子健康记录（EHRS），ANDD评估评估和文档实践评估的观点定性访谈和观察肿瘤学家将有助于信息未来的诊所重新设计支撑的职业发展和培训计划支持Schiaffine博士的轨迹通过以下三个目标，独立的，老化的系统科学家：1）获得先进的自然语言处理（NLP）算法开发培训以从EHR中提取非结构化文本，2）从事老年肿瘤学护理护理的观察和培训，以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）获得临床工作流程的经验实施科学提案开发。希望（加利福尼亚州杜阿尔特，加利福尼亚州）与老年医学专家/老年医学专家（主要：马里兰州艾莉森·摩尔（Alison Moore，MD））的导师；辐射肿瘤学/ HSR（共同主要：詹姆斯·墨菲（James Murphy），医学博士，MS，UCSD）；（导师：希望之城威廉·戴尔（William Dale），医学博士，博士）；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学报（LEP）差异（合作者：Alicia Fernandez，MD，UCSF）。