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