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Andrew Gonzalez, MD, JD, MPH, RPVI

Andrew Gonzalez, MD, JD, MPH

  • Associate Director for Data Science and Research Scientist, Center for Health Services Research, Regenstrief Institute, Inc.
  • Assistant Professor, Department of Surgery, Indiana University School of Medicine
  • 2019-21 National Academy of Medicine Omenn Fellow
  • Adjunct Faculty, Network Science Institute, Indiana University 
  • Adjunct Faculty, Center for Research on Race & Ethnicity in Society, Indiana University 
  • Adjunct Faculty, Department of Health Policy & Management, Indiana University  Fairbanks School of Public Health
  • Faculty Affiliate, Regenstrief Center for Healthcare Engineering, Purdue University

Dr. Gonzalez believes in the Learning Health System as paradigm for advancing foundational research across a number of disciplines as well as “closing the loop” by facilitating real world implementations of research findings. His early career agenda explores specific use cases centering around two recurring research themes: Application of design-thinking to both health policy and to translational medical devices to improve patient care and use of real world data and artificial intelligence (AI) to improve clinical decision-making and outcomes in vascular surgery.

Dr. Gonzalez’s goal is to have multilevel impact that advances foundational research in computational vascular imaging, develops usable regulatory and bioethical frameworks for “doctor in the middle” paradigms of AI implementation in healthcare, and enhances “trustworthy/explainable AI” that protects healthcare equity rather than exacerbate disparities for historically marginalized groups. To this end, he is leveraging formal education in medicine, law, public health, and health services research to generate impactful discoveries across the following fields to pioneer a new career pathway as a “full-stack” clinician-scientist.

“We strive to create the backend solutions for seamlessly recording, curating, and analyzing real world healthcare data to generate insight at the point-of-care. Providers should spend their time attending to patients, not documenting.”

Current Research Projects

Applications of Artificial Intelligence to Catheter Based Angiography in Peripheral Arterial Disease
(AHRQ K12 Leaning Health Systems Grant, PI: Gonzalez)
We aim to implement an active learning algorithm with the goal of creating a cloud based system that can perform feature extraction using real world angiograms. We also aim to identify knowledge gaps in care to guide use of this platform in delivering better care for patient’s with peripheral vascular disease.

Fragmentation of Care in Peripheral Arterial Disease: A Network Theory Approach
(Funding pending)
Peripheral arterial disease is the leading cause of amputation in the US. We will consider the pathway of care in PAD as a complex adaptive system and apply network theory to characterize fragmentation of care. We hope this analytic framework will identify hospital and system specific leverage points that can reduce amputations rates for patients with PAD.