Computer Science & Engineering, Global Institute of Public Health, New York University
Title: Unstructured Data and Population-level Public Health
Bio. Rumi Chunara is an Assistant Professor at NYU, in Computer Science & Engineering and the College of Global Public Health. Her research focuses on how we can use unstructured data to illuminate population-level epidemiology. She received her B.S. in Electrical Engineering at Caltech, S.M. in Electrical Engineering and Computer Science at MIT and Ph.D. in Electrical and Medical Engineering at the Harvard-MIT Division of Health Sciences and Technology. Rumi is a recipient of a Caltech Merit Scholarship, MIT Presidential Fellowship and is an MIT Top 35 innovator under 35 (2014).
Associate Professor of Medicine at UCSF in the Division of General Internal Medicine & primary care physician at San Francisco General Hospital’s Richard H. Fine People's Clinic
Title: Health IRL: what we can learn from social media
Bio. Dr. Sarkar’s research focuses on (1) patient safety in outpatient settings, including adverse drug events, missed and delayed diagnosis, and failures of treatment monitoring, (2) health information technology and social media to improve the safety and quality of outpatient care, and (3) implementation of evidence-based innovations in real-world, safety-net care settings. Dr. Sarkar is committed to enhancing health information technology approaches to improve primary care and ameliorate disparities in vulnerable populations, through the health-literacy-sensitive, patient-centered approaches such as co-development and usability testing, in partnership with technology development experts. Her current work applies design thinking and interdisciplinary, iterative approaches to characterize and address safety gaps in outpatient settings. She has conducted studies which explore the impact of health communication (health literacy, English proficiency) and health information technology on patient safety. Her prior studies on internet-based patient portals demonstrate digital disparities by race/ethnicity and health literacy. Her social media studies use mixed-methods approaches to understand patient perspectives about physician quality and about cancer screening behaviors. Her ongoing work employs varied health information technologies to detect and ameliorate adverse events among outpatient chronic disease populations. She is currently funded by the Agency for Healthcare Research and Quality (AHRQ) and the National Cancer Institute, with prior funding from the California Healthcare Foundation, and the Gordon and Betty Moore Foundation. In addition to her research, Dr. Sarkar is Associate Editor for Patient Safety Net www.psnet.ahrq.gov , a national web-based resource featuring the latest news and essential resources on patient safety. She serves as the co-director for the San Francisco General Hospital Primary Care Residency’s Quality Improvement, Patient Safety, and Leadership Curriculum with Dr. Claire Horton, and mentors trainees in both research and quality improvement projects. She is responsible for coordinating ambulatory morbidity and mortality conference at the General Medicine Clinic at San Francisco General Hospital, with the UCSF medicine quality and safety chief resident. Dr. Sarkar also serves as co-director for the School of Medicine’s Office of Student Research and Research Allocation Program- trainees.
Department of Information Systems, University of Haifa
Title: Engaging patients in their health care: experiences from the MobiGuide Project [SLIDES]
Abstract: MobiGuide was a large-scale European project, with over 60 researchers, clinicians and engineers, from 13 different organizations in five countries, in the area of guideline-based personalized medicine, which I have led for the past 4 years. MobiGuide is a scalable, secure, ubiquitously accessible, and user-friendly mobile solution for designing, deploying and maintaining a DSS for patients and their care providers. In this talk I will discuss how our AI-based DSS: (1) helped patients to participate in the care process, (2) helped them to be aware of what is necessary to follow up and what to communicate with physicians, (3) and assisted clinicians to utilize this participation in order to provide high quality and efficient personalized care. I will end with opportunities for future research to enhance the patient experience and involvement.
Bio. Mor Peleg is Assoc. Prof at the Dept. of Information Systems, University of Haifa, and has been Department Head in 2009-2012. She is currently on Sabbatical at Stanford Center for Biomedical Informatics Research. Her BSc and MSc in Biology and PhD in Information Systems are from the Technion, and her post-doc was at Stanford BioMedical Research. She was awarded the New Investigator Award by the American Medical Informatics Association, is International Fellow of the American College of Medical Informatics and is Associate Editor of Journal of BioMedical Informatics. Her research concerns knowledge representation, decision support systems, and process-aware information systems in healthcare. http://mis.hevra.haifa.ac.il/~morpeleg/
Professor of Medical Informatics in Epidemiology in Biostatistics and Epidemiology at the Hospital of the University of Pennsylvania
Title: AI-driven Approaches to Data Integration [SLIDES]
Abstract: In this era of "Big Data", robust and scalable approaches to integrating data from many different sources have never been so urgently needed. This is especially true in biomedical domains, where data from myriad sources such as electronic health records, personal health records, specialty information systems such as those used in clinical laboratories, radiology departments, and pharmacies, as well as environmental data and even social media are critically important for providing state-of-the art patient care and supporting research and administrative enterprises. Taken together, these data are syntactically and semantically heterogeneous on a scale that is still not fully appreciated, nor is their integration fully realized. This is because few tools currently exist to harmonize these data in a way that captures and preserves the concepts they contain and makes them usable by clinicians and researchers. For the most part, these tools focus on manually-created ontologies that require substantial skill and effort to create, and even then, they tend to be specialized to one domain or another. This presentation will present an approach to ontology creation for data harmonization and integration that is grounded in artificial intelligence methods of concept formation and discovery.Several case studies will be presented, and time will be provided for group discussion of future paths the AI community can take as we endeavor to contribute meaningfully to this critically important issue of large-scale biomedical data integration.
Bio. John H. Holmes is Professor of Medical Informatics in Epidemiology at the University of Pennsylvania Perelman School of Medicine. He is the Associate Director of the Penn Institute for Biomedical Informatics. Dr. Holmes’ research interests are focused on several areas in medical informatics, including evolutionary computation and machine learning approaches to knowledge discovery in clinical databases (data mining), interoperable information systems infrastructures for epidemiologic surveillance, regulatory science as it applies to health information and information systems, clinical decision support systems, semantic analysis, shared decision making and patient-physician communication, and information systems user behavior. Dr. Holmes is a principal or co-investigator on projects funded by the National Cancer Institute, the Patient-Centered Outcomes Research Institute, the National Library of Medicine, and the Agency for Healthcare Research and Quality, and he is the principal investigator of the NIH-funded Penn Center of Excellence in Prostate Cancer Disparities. Dr. Holmes is engaged with the Botswana-UPenn Partnership, assisting in building informatics education and clinical research capacity in Botswana. He leads the evaluation of the National Obesity Observational Studies of the Patient-Centered Clinical Research Network. Dr. Holmes is an elected Fellow of the American College of Medical Informatics and the American College of Epidemiology.