Improving age-related risk assessment and documentation for diverse older adults with cancer - Melody K Schiaffino, PhD, MPH is an associate professor in the Department of Radiation Medicine and Applies Sciences in the UC San Diego School of Medicine. Dr. Schiaffino received her PhD in Health Services Research in 2014 and MPH in Epidemiology in 2008. As a health systems scientist, Dr. Schiaffino’s goals are to identify organizational and provider-level risk factors that affect how care is delivered to older adults undergoing treatment for cancer to improve sub-optimal care delivery and treatment outcomes. Older 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 older adults diagnosed with cancer, seeks to examine provider and documentation factors 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. 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 needing an interpreter. 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 Geriatric Oncology/ Decision-Making (Mentor: William Dale, MD, PhD, City of Hope); NLP/Bioinformatics (Mentor: Mike Hogarth, MD, UCSD); Radiation Oncology/HSR (Co- Primary: James Murphy, MD, MS, UCSD); Predictive Models/Biostatistics (Collaborator: Barbara Bailey, PhD, SDSU) and clinical implementation science (Co-Mentor: Alicia Fernandez, MD, UCSF).
