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Dr. Claudia Der-Martirosian is a research investigator at OCHIN. A quantitative sociologist and a health services researcher by training, she has expertise in mixed methods, incorporating both quantitative and qualitative approaches. With over 25 years of experience in population health and health-related research, she has more than 20 years of experience managing large, complex data sets from multiple sources, conducting data analysis, using electronic health records, and performing data visualization. She is skilled at transforming complex qualitative and quantitative data into meaningful insights.
Claudia was a core investigator (2011-24) at two research centers within the U.S. Department of Veterans Affairs (VA): the Center for the Study of Healthcare Innovation, Implementation & Policy (CSHIIP) and the Veterans Emergency Management Evaluation Center (VEMEC) at the VA Greater Los Angeles. For six years (2014-20), she served as the associate director of VEMEC, where she developed the research program and a dissemination plan for best practices in emergency management and disaster preparedness at the VA. In her role as associate director, she managed a team of 20 doctoral- and master’s-level VA researchers from multidisciplinary backgrounds, overseeing IRB submissions, the development of scholarly publications, toolkits, and online trainings, while working closely with investigators, data analysts, and project managers.
Claudia has delivered over 70 presentations at national conferences and has first- and co-authored more than 115 publications in peer-reviewed scientific journals in health-related fields, with a strong focus on access to care for underserved populations. As principal investigator (PI), co-PI, and co-investigator, she has received several federal government operations and research grants.
Claudia’s research portfolio on use of telehealth in primary care began with her work on the utilization of telehealth services in primary care during the COVID-19 pandemic. She received VA operations and research funding to examine patient, provider, and site characteristics associated with telehealth use in primary care settings.
Claudia's research portfolio on the utilization of telehealth services during major disasters began with her mixed methods study on examining the use of telehealth services at the VA during Hurricane Sandy in 2012. She was one of the first researchers to illustrate how VA telehealth services provided virtual access to sustain continuity of care during major hurricanes, when physical access to VA health care systems was limited due to road closures and flooding.
Claudia led the analysis of all-hazards assessment data for 140 VA Medical Centers (VAMCs) (collected in two phases: 2008-10 and 2011-13) and identified the most critical missions for an emergency management program and the capabilities associated with those missions. This approach helped adapt the group-design assessment tool to a less resource intensive self-assessment instrument that can be used by VAMC directors and senior leaders to self-evaluate and improve the readiness of all VAMCs.
Continuity of care during disasters is critical, especially for patients facing greater medical complexity. At VEMEC, Claudia conducted a series of studies on access to VA care during natural disasters (such as the 2012 Hurricane Sandy, 2017 Atlantic hurricanes, 2018 Midwest flooding, 2017-18 California fires), as well as major environmental incidents (such as the 2015-16 Porter Ranch natural gas leak).
Claudia and the VEMEC study team conducted the VA Preparedness Survey using a stratified, simple random web-based survey (October-December 2018) of all employees at VA medical facilities nationwide. A total of 4,026 VA employees, both clinical and non-clinical, responded. Claudia led the development of the conceptual framework, helped design the sampling strategy for the survey, and created the survey instrument. In addition, she oversaw the management of the fielding of the survey, data collection/cleaning, post-stratification of survey weights, and data analysis.
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