Saurabh Arun Rahurkar, PhD
Assistant Professor
Biomedical Informatics
Academic information
- Department: Biomedical Informatics
Research interests
- Electronic Health Records (EMR)
- Statistics
- Predictive Modeling
- Data Science
About
Biography
I am an assistant professor in the Department of Biomedical Informatics and a core faculty at the Center for Advancement of Team Science, Analytics and Systems Thinking in Health Services and Implementation Science (CATALYST). Due to the translational nature of my work, I am also a member of the Translational Data Analytics Institute (TDAI), where I am active in the Computational Health and Life Sciences; Foundations of Data Science and AI; and Responsible Data Science groups.
With over a decade of experience in biomedical informatics, I excel in bridging the clinical domain with data-driven approaches. My passion lies in utilizing my skills to develop tools that provide data-driven actionable insights, improving care by targeting all actors in the care process, including care providers, pharmacies, and patients. I possess expertise in a wide array of analytic methodologies including statistical and predictive modeling, econometrics, and AI/ML, enabling me to undertake diverse initiatives such as building predictive models and implementing them in Electronic Health Records (EHRs) to conducting statewide health technology assessments. My proficiency in health information technologies has been instrumental in leveraging early-stage Fast Healthcare Interoperability Resources (FHIR) to improve health outcomes in emergency departments.
Another significant aspect of my work involves employing data science expertise for the secondary use of EHRs in driving research and insights into care processes by generating Real-World Data. I effectively utilizes large-scale distributed infrastructure to facilitate these analyses. I also focus on the use of EHR log data, including clickstream data from EHRs, to understand physician behavior and study clinical and pharmacological health outcomes in the context of physician actions.
I am also an expert in systematic review and meta-analysis methodologies, having conducted several high-impact systematic reviews cited in state and federal reports as well as legislation. I am an effective communicator, adept at conveying findings to diverse audiences. My work has been utilized in congressional hearings to influence legislation and health policy, highlighting my impact on the broader healthcare landscape.
I also teach the BMI 5760: Public Health Informatics course.
Credentials
Education
- Postdoctoral Fellowship - Public Health Informatics
- Regenstrief Institute, Center for Biomedical Informatics, Indianapolis, IN, United States
- PhD
- University of Alabama at Birmingham, Birmingham, AL, United States
- MPH
- University of Alabama at Birmingham, Birmingham, AL, United States
Research
Research interests
- Electronic Health Records (EMR)
- Statistics
- Predictive Modeling
- Data Science
I am a clinician by training, holding a DDS degree. I further expanded my expertise with a Master's in Public Health, focusing on health services research from the University of Alabama at Birmingham (UAB). My doctoral work, also completed at UAB, concentrated on the impact of Health Information Exchange, and resulted in high-impact publication that received attention from media such as Politico as well as inclusion in Federal policy reports.
Following my formal education, I received a postdoctoral fellowship in public health informatics at the Regenstrief Institute in the Center for Biomedical Informatics. During this period, I developed a deep understanding of EHR data and large-scale health data. I was involved in creating Real-World Data and undertook extensive work in data harmonization, including the development of common data models and crosswalks. This work provided nuanced intelligence to health data, and significantly improved the interpretability of findings based on these data.