2024 Biomedical Informatics Seminars
May 31, 2024
Pending
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May 10, 2024
Pending
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April 19, 2024
Pending
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March 15, 2024
Mattheus Ramsis, MD, Assistant Professor of Medicine, Diretor, Cardiology Informatics, UCSD Division of Cardiovascular Medicine. "Validation of Cardiovascular Algorithms and Devices."
Bio: I am an Assistant Professor, Cardiologist, and Medical Director of Cardiology Informatics at the University of California, San Diego. I previously trained in internal medicine at Harvard Medical School-Brigham and Women's Hospital with subsequent training in cardiovascular disease, trial design, and preventative cardiology at the University of California, San Francisco where I served as a clinical instructor. Awards include the NIH T-32 award and the BMSF career development award. My previous and ongoing work consists of validating algorithms and devices for cardiovascular disease and developing digital biomarkers. I collaborate with multidisciplinary teams of clinicians, researchers, and engineers to leverage data from wearable devices, biomarkers, and electronic health records to create innovative solutions, improve patient outcomes, and enhance quality of care.
March 1, 2024 - Cancelled
February 23, 2024
Jejo Koola, MD, MS, Associate Professor of Medicine, Division of Biomedical Informatics and Hospital Medicine, Medical Director, Information Systems, University of California San Diego. "Identifying Early Hepatic Encephalopathy Through Digital Phenotyping."
Abstract: Hepatic Encephalopathy (HE) leads to frequent hospitalization, costing $2.0 billion annually. Early identification may motivate early treatment; however, diagnosing covert HE requires complex and protracted neuropsychological testing, which is often infeasible in the clinic setting. We conducted a feasibility study using passive sensing technologies as a means of “digitally phenotyping” HE. We recruited adult subjects with cirrhosis and prospectively followed them up to 6 months. We measured cognitive function monthly in a study clinic by a battery of neuropsych testing. We collected interaction data from the subjects’ smartphone utilizing the BiAffect app, which runs in the background and unobtrusively and continuously collects typing speed, typing accuracy, and accelerometer data. Additionally, we fitted subjects with a wrist-worn activity tracker (Fitbit, Inc.) for sleep, activity level, and heart rate measurement. Dr. Koola will present early pilot results on the feasibility of using digital phenotyping to identify hepatic encephalopathy.
Bio: Dr. Jejo Koola is Associate Professor in the Department of Medicine within the UC School of Medicine with a joint appointment in Hospital Medicine and Biomedical Informatics. His research interests are in using statistical and machine learning models for risk prediction using big data. He applies models to improving the care of multi-morbid patients, particularly patients with advanced liver disease, for which he has been funded by the NIH, the Department of Veterans Affairs, and AHRQ. In addition to his faculty role, he holds a medical directorship within UC San Diego Health Information Systems and is Epic certified to perform infrastructure “build” within the Electronic Health Record. He is currently involved as the data coordinating center lead for two randomized clinical trials piloting clinical decision support interventions within the EHR. Dr. Koola received his MD degree from the Medical University of South Carolina and subsequently completed his residency in Internal Medicine at the Medical College of Virginia in Richmond, Virginia in 2011. Following residency, Dr. Koola completed a post-doctoral fellowship in Biomedical Informatics through the Department of Veterans Affairs in conjunction with Vanderbilt University in 2016. Clinically, he sees a wide variety of hospitalized patients at UCSD on the hospitalist service.
February 16, 2024
Ming Tai Seale, PhD, MPH Professor, Department of Family Medicine and Public Health, Professor, Division of Biomedical Informatics, Vice Chair for Research, Department of Family Medicine and Public Health, Director, Health IS Outcomes Analysis, University of California San Diego. "AI-Generated Draft Replies Integrated into the EHR and Physicians' Electronic Communication."
Abstract: Groundbreaking quality improvement project of Electronic Health Record (EHR)-integrated generative AI-drafted replies & physician engagement with patient messages. This work is currently embargoed and details will be shared in person during the presentation.
Bio: Dr. Ming Tai-Seale is Professor and Vice Chair for Research in the Department of Family Medicine and Professor in Division of Biomedical Informatics in UC School of Medicine. Her research investigates the practice of medicine, patient-physician communications, and healthcare economics. She pioneered the use of user action log data in electronic health records to study physician practice and wellbeing. She was also the first to use video and audio recordings of clinical encounters to study time allocation in primary care practice. She is the Principal Investigator of the P30 UC San Diego Learning Health Systems Science Center funded by the Agency for Healthcare Research and Quality. In addition to her faculty appointment, she is the Director for Outcomes Analysis and Scholarship at the UC San Diego Health and Director for Research and Learning in the Population Health Services Organization at UC San Diego Health. Dr. Tai-Seale earned her Ph.D. in Health Services with a cognate in Economics from UCLA.
February 9, 2024
Amy Sitapati, MD, Clinical Professor, Division of Biomedical Informatics, Division of General Internal Medicine, Chief Medical Information Officer, Population Health, UCSDH, Interim Chief, Division of Biomedical Informatics, UCSD, Interim Chair, UC San Diego Health Department of Biomedical Informatics. "Biomedical Informatics: Systems Science and Diagnostic Safety Incidental Pulmonary Nodules Registries and Population Health to Support SureNet."
Bio: Amy M. Sitapati, MD, is Professor of Medicine, Chief of the Division of Biomedical Informatics, Chair of the UC San Diego Health Department of Biomedical Informatics, and a primary care physician at UC San Diego Health. She is Medical Director of Internal Medicine in La Jolla and leads the population health team that focuses on how clinical informatics can be used to improve the quality of care.
Dr. Sitapati is nationally recognized for her work in primary care. She has more than ten years of experience providing high-quality, patient-centered care in ambulatory settings, and strives to build multidisciplinary teams that effectively work together to improve patient care coordination. In support of patient participation in chronic disease management, Dr. Sitapati combines evidence-based medicine with patient empowerment, prevention methods, and alternative medicine (e.g., Kelee meditation) to help patients achieve their best health. She also has expertise in providing gender-affirming care to transgender and nonbinary patients.
Dr. Sitapati first joined UC San Diego Health in 2001 following completion of her residency. In 2005, she established the Center for Infectious Disease Management and Research (CIDMAR) at Howard University, a center dedicated to providing culturally competent, state-of-the-art HIV medical care to its 225 patients. In 2007, she met with First Lady, Mrs. Laura Bush, to discuss the first hospital-wide, routine HIV screening program to be implemented in the nation. In 2015, Dr. Sitapati assumed the role of medical director of internal medicine in La Jolla. She also leads a population health team that focuses on using computer systems to improve the quality of care.
In 2022 she was recognized for her humanistic approach to medicine and delivery of care for patients and their families by receiving the Leonard Tow Humanism in Medicine Award. Dr. Sitapati believes bringing humanism into the practice of medicine is the highest pinnacle in health care delivery, benefiting both patients and health care colleagues. As a professor of medicine her clinical research has been related to patient-centered care, quality improvement, and meditation. Dr. Sitapati serves as an instructor for medical students and residents.She completed her medical residency training at UC San Diego School of Medicine, and earned her medical degree from Case Western Reserve University, School of Medicine, in Cleveland, Ohio. Dr. Sitapati is board certified in internal medicine and clinical informatics.
February 2, 2024
Zhe He, PhD, FAMIA, Associate Professor, School of Information, Director, eHEALTH Lab, Director of Biostatistics, Informatics, and Research Design Program (BIRD) of UF-FSU CTSA Hub, Florida State University, Chair-Elect, AMIA Knowledge Discovery. "Harnessing Explainable, Equitable, and Actionable Data Science to Improve Health and Clinical Research."
Abstract: Data science and AI have been revolutionizing biomedical research and healthcare. The availability of large amounts of data such as electronic health records (EHRs) along with a significant increase in computational power has enabled researchers to further investigate the benefits of applying data science and AI to solving challenging problems in biomedical research and healthcare. In the healthcare, while prior research has shown superior performance of deep learning when predicting health outcomes using electronic health record (EHR) data, it has not been adequately adopted in EHR systems in the US. Evidence has shown that improved transparency and interpretability of the deep learning models will increase their trustworthiness for medical doctors, thereby increasing their adoption by healthcare systems. In clinical research, there is lack of generalizability of clinical trials due to unjustified use of overly stringent eligibility criteria. In this talk, I will discuss our recent research efforts on enhancing the interpretability of machine learning models for predicting health outcomes and using EHR data to optimize eligibility criteria design for Alzheimer’s disease clinical trials.
Bio: Dr. Zhe He is an Associate Professor at Florida State University School of Information. He is also holding courtesy appointments with Department of Behavioral Sciences and Social Medicine of College of Medicine and Department of Computer Science. He is also Team Lead of Biostatistics, Informatics, and Research Design (BIRD) Program of UF-FSU Clinical and Translational Science Award. His research lies at the intersection of Biomedical & Health Informatics, Computers Science, and Information Science. He currently serves as Chair-Elect of AMIA Knowledge Discovery and Data Mining Working Group. As an informatician, his research expertise includes machine learning, natural language processing, knowledge representation, and big data analytics. At FSU, he is leading the eHealth Lab. The overarching goal of his research is to improve population health and advance biomedical research through the collection, analysis, and application of electronic health data from heterogeneous sources. As Principal Investigator, Dr. He has been funded by National Institutes of Health, Eli Lilly and Company, Amazon, NVIDIA, and Institute for Successful Longevity. His papers received prestigious recognitions including two Distinguished Paper Awards of AMIA 2015 and 2017 Annual Symposium. In 2022, he was inducted as a Fellow of the American Medical Informatics Association.
January 19, 2024
Eugenia McPeek Hinz, MD, MS, Associate Chief Medical Information Officer, Associate Program Director, Clinical Informatics Fellowship, Duke University Health System. "Screening and Connecting Patients to Resources for Health Related Social Needs."
Abstract: Health-Related Social Needs (HRSN) are the non-medical factors that adversely impact as much as 70% of a patient's health outcomes. Challenges in identifying and linking patients to relevant resources result in a typical success rates of only 15-30%. The successful connection rate reflects the sequential and interdependent steps with multiple potential points for failure, for the patient to receive a resource from a community based organization (CBO). The Duke Health journey began in 2018 with ad hoc discrete data capture of HRSN. In 2021, we began systematic screening for Social Determinant of Health (SDOH) with the integration of NCCARE360 on the Unite Us platform in our Electronic Health Record (EHR). In this presentation, I will share Duke Health’s experiences with SDOH screening, challenges encountered, lessons learned, and future steps to automate connections to resources.
Bio: Eugenia McPeek Hinz MD MS is an Associate Chief Medical Information Officer for Duke University Health System and Physician Informatician with extensive experience in the build and configuration of Duke Health's Electronic Health Record (EHR). She completed a Master of Science in Biomedical Informatics at Vanderbilt University in 2012 as a National Library of Medicine Fellow. In August 2012, she joined Duke University Health System to lead more than 30 physician champions in support of the implementation of our EHR across Inpatient, Surgical and Ambulatory environments. In her work she supports EHR usability, provider well-being, regulatory, compliance, research and SDOH integration.
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