The Aghaeepour lab uses machine learning to study the immune system in clinical settings. This includes integrative “multiomics” analysis across genomics, proteomics, and single-cell technologies, as well as quantitative clinical phenotyping, to produce a holistic understanding of immunity.
Dr. Mudumbai is an Associate Professor with an outcomes and health services research focus that integrates his clinical, administrative, and research roles. Dr. Mudumbai's main research interests are translational: 1) optimizing therapeutic strategies and reducing adverse outcomes related to medication management, particularly opioids; and 2) measuring and improving the quality of perioperative and pain management using telehealth. His research team of data analysts, research associates, and trainees are based out of the VA Palo Alto’s Menlo Park campus. Dr. Mudumbai currently is leading investigations on a) the relationship between opioids and incident cancer in VA populations with collaborators from the National Cancer Institute (NCI) to help guide policy recommendations; and b) the adoption and outcomes of telehealth for preoperative evaluation and optimization within VA populations. His team is funded by the FDA, VA, and NIH
My research examines questions of health economics and health policy, with a focus on economics and policy in the perioperative setting. One area of interest is the economics of chronic pain, where I am examining several topics. The first is the epidemiology and economics of opioid use in the perioperative setting, where my research examines risk factors for chronic opioid use following surgery as well as the effectiveness of interventions aimed at reducing this risk. In addition, my work is also focusing on the economics and cost-effectiveness of treatments for chronic back pain.
A second area of interest examines the economics of the structure of physician practice organizations. In the past, most physicians tended to practice in the context of solo/small group practices. However, this practice model has grown less common over time and today, physicians are more likely to practice in the setting of large group practices. Whether this new model is of benefit—or harm—to patients remains unknown. Currently, I am examining the extent to which this new model has affected outcomes and prices for perioperative care.
My areas of clinical focus are hemodynamic monitoring and heart failure. My methodologic areas of focus are the conduct of population-based cohort studies using large healthcare databases; predictive analytics; sex and gender epidemiology; patient engagement; innovative methods for data processing and warehousing; and software and applications development. My research leverages big data and digital technology to bridge key gaps in the delivery of care and outcomes for patients with heart failure and/or undergoing cardiovascular interventions, zooming in on sex/gender and personalized care.
The aim of my patient-centered research program is to improve access to care and quality of life outcomes of women and men with cardiovascular disease. Our work focuses on personalized risk stratification and long-term outcomes. Among our recent key accomplishments are original research papers describing patient-defined outcomes (PACE and disability-free survival), defining optimal blood pressure targets during cardiac and noncardiac surgery, comparative effectiveness of CABG vs. PCI, and sex differences in heart failure outcomes.