Abstract: Medical science enables healthcare potential previously impossible, but the escalating complexity drives care fragmentation and inadequate access to clinical expertise, even when it is often limited to the undesirable variability of anecdotal experience. Without new approaches in clinical knowledge synthesis, distribution, and consistent execution, the status quo will remain both over- and under-utilization of resources with pervasive diagnostic errors and unsustainable growth in healthcare waste. “Grand challenges” in clinical decision support thus include mining clinical data sources to automatically generate information. I will review our efforts developing a collaborative filtering machine learning approach for medical decision making, analogous to Netflix or Amazon.com’s “Customer’s like you also liked” algorithms. This can exceed manual constructs like clinical order set checklists while aligning with practice guidelines and predicting clinical outcomes. This is even more important for prevalent cases where well-defined guidelines do not exist. While the above can enable broader access to consistent healthcare recommendations, the complementary opportunity is to identify low value processes to avoid. I will review our work developing algorithms to estimate diagnostic test probabilities to identify low yield tests to avoid. Tapping into real-world clinical data streams like electronic medical records will reveal the community's latent knowledge in a reproducible form. Delivering this back as clinical decision support will uniquely close the loop for a learning health system. Our group seeks to empower individuals with the collective experience of the many, combining human and artificial intelligence approaches that will deliver better care than either alone.
Bio: Jonathan H. Chen MD, PhD practices medicine for the concrete rewards of caring for real people and to inspire research focused on discovering and distributing the latent knowledge embedded in clinical data.
Chen co-founded a company to translate his Computer Science graduate work into an expert system for organic chemistry, with applications from drug discovery to an education tool for students around the world. To gain perspective tackling societal problems in health care, he completed training in Internal Medicine and a Research Fellowship in Medical Informatics. He has published influential work in the New England Journal of Medicine, JAMA, JAMA Internal Medicine, Bioinformatics, Journal of Chemical Information and Modeling, and the Journal of the American Medical Informatics Associations, with awards and recognition from the NIH Big Data 2 Knowledge initiative, National Library of Medicine, American Medical Informatics Association, Yearbook of Medical Informatics, and American College of Physicians, among others.
In the face of ever escalating complexity in medicine, informatics solutions are the only credible approach to systematically address challenges in healthcare. Tapping into real-world clinical data like electronic medical records with machine learning and data analytics will reveal the community's latent knowledge in a reproducible form. Delivering this back to clinicians, patients, and healthcare systems as clinical decision support will uniquely close the loop on a continuously learning health system. Dr. Chen's group seeks to empower individuals with the collective experience of the many, combining human and artificial intelligence approaches that will deliver better care than either can do alone.
Computational Biology in Takeda Pharmaceuticals
Abstract: In this talk Dr. Szalma will give an overview of the role of computational biology in Takeda drug discovery and development ecosystem. He will show several examples how human data is acquired, processed and analyzed for insights to support reverse and forward translation using statistical and machine learning methods.
Bio: Sándor Szalma is Global Head, Computational Biology in Takeda Pharmaceuticals. He is responsible for computational biology, computational and statistical genetics, machine learning and informatics approaches supporting target discovery/reverse translation and forward translation/biomarker and patient stratification in oncology, neuroscience and gastroenterology. He serves as a member of the governance board of Open Targets and leads the Takeda engagement in the Regeneron Whole Exome Sequencing of UK Biobank Consortium. Before joining Takeda, he was head of Translational Informatics and External Innovation, R&D IT in Janssen Research & Development, LLC. Previously, he was member of the industry advisory committee of ELIXIR, member of the board of the Pistoia Alliance, member of the Translational Medicine Advisory Committee of the PhRMA Foundation and led the Data & Knowledge Management Strategic Governance Group of Innovative Medicine Initiative. His past positions included president of MeTa Informatics, general manager of QuantumBio and senior director of Computational Biology and Bioinformatics at Accelrys, Inc. He was co-founder of Acheuron Pharmaceuticals, Inc. He lectured at UCSD Extension and was adjunct professor at Rutgers University in the Computational Biology and Molecular Biophysics program. He is the author of 45 scientific publications and book chapters and two patents. He received his doctoral degree in physical organic chemistry from A. Szent-Györgyi Medical University in Szeged, Hungary.
Natural Language Processing at the VA: From Research to Operations
Abstract: The Veterans Health Administration is the largest integrated health care system in the United States, and data files created from veterans’ healthcare records are among the richest and largest sources of longitudinal clinical information available to researchers. The VA Informatics and Computing Infrastructure (VINCI) is VA Health Services Research and Development Resource Center that provides researchers access to nationwide VA patient data along with tools and computing for analysis. VINCI also provides a variety of services to the VA-affiliated researchers. One of VINCI teams focuses on natural language processing (NLP). This seminar will describe VINCI and the NLP-related work performed at VINCI.
Bio: Dr. Olga Patterson is a Research Assistant Professor at the Division of Epidemiology at the University of Utah. Her research is focused on computational analysis of clinical narrative documents using natural language processing and machine learning for the purposes of information extraction, information retrieval, and classification. She also leads an annotation team performing medical chart abstraction for retrospective clinical studies and care quality assessments. As Applied NLP Team lead at the VA Informatics and Computing Infrastructure (VINCI), she provides education and consulting to VA-affiliated researchers on the use of unstructured data in retrospective studies. As a co-investigator on multiple clinical outcomes studies, she develops and deploys systems that extract clinically relevant variables from unstructured text in various clinical subdomains including cardiology, oncology, pathology, and mental health.
Abstract: Pediatric clinical decision support poses many challenges. We will explore two clinical decision support projects utilizing the electronic health record and discuss the ramifications of each. The first is focused on a pediatric head injury algorithm developed to assess the risk of clinically important traumatic head injury to aid the clinician in the decision making process of whether or not to order head imaging while in the emergency department. The second concentrates on patients presenting to the emergency department with signs and symptoms that could be related to a brain tumor.
Bio: Dr. Gutglass is a clinical professor of pediatrics at UCSD and has practiced pediatric emergency medicine at Rady Childrens Hospital for the past twenty years. He received his masters in Biomedical Informatics at Oregon Health Sciences University. He has also worked as a consultant for Cerner corporation where he helped utilize analytics to optimize physician workflow. Currently he does clinical research focusing on brain tumor presentations and the effects on children of legalizing marijuana.
Near-Real Time Personalized Medicine and Cystic Fibrosis
Abstract: Near real-time microbiology approaches will enable doctors to make better decisions about patient treatments. The San Diego research community has established a collaborative effort to generate and interpret metagenomics, metatranscriptomic and metabolomics (i.e., -omics) data from cystic fibrosis (CF) sputum samples in approximately 1-2 days. This work is part of a greater background of a long-term sampling effort, where each patient serves as their own benchmarks for different disease states. This approach allows us to more rapidly determine what has changed at any particular time in the patient’s history. Using these "-omics" data we are identifying the underlying viral and microbial mechanisms that drive the cyclical nature, stable, exacerbation and recovery, of CF. This background data is extremely useful for diagnosing what is unique about fatal exacerbations and points to possible treatment options. A case study in which we applied this approach to a patient experiencing a fatal exacerbation event will be presented. The “-omics” techniques complimented each other and allowed us to determine the most likely cause of the event. I will also discuss what we learned that worked versus what did not work.
Bio: Forest Rohwer is a Fellow of the American Academy for Advancement of Science (AAAS), American Academy of Microbiology (AAM) and Canadian Institute for Advanced Research (CIFAR). He led the development of viromics, which involves isolating and sequencing the RNA/DNA from all of the viruses in a sample. From this data, it is possible determine what types of viruses are present and what functions they are encoding. Dr. Rohwer uses viromics to study ecosystems ranging from the human body to coral reefs and has shown that most genomic diversity on the planet is viral. Dr. Rohwer has published >200 peer-reviewed articles, was awarded the International Society of Microbial Ecology Young Investigators Award and was listed as one of the World's Most Influential Scientific Minds. He has also published two books: Coral Reefs in the Microbial Seas and Life in Our Phage World.
Evaluating the Impact of Electronic Health Record Implementation and Use on Clinical Workflows in Ophthalmology
Bio: Sally Baxter is currently a National Library of Medicine postdoctoral fellow in biomedical informatics at UCSD. Her research interests include (1) investigating how data from the EHR and other sources (e.g. sensors, wearables) can be leveraged to better understand the connections between systemic diseases and medications with vision and other eye-related outcomes, and (2) understanding how ophthalmologists learn and interact with the EHR, and how these interactions might be improved in order to support high-quality care, enhanced patient experience, and ease of use for clinicians. She practices comprehensive ophthalmology with a specialization in complex cataract surgery at the San Diego VA. She was an Angier B. Duke Scholar at Duke University, received her Masters of Public Health from the London School of Hygiene & Tropical Medicine as a United States Marshall Scholar, and was a 21st Century Scholar at the Perelman School of Medicine at the University of Pennsylvania prior to coming to UCSD for her internal medicine and ophthalmology training.
Bio: Dr. Steven Lane is a practicing primary care physician and clinical informaticist who is passionate about health information technology and its potential to improve the care we provide in our communities, and around the world. At Sutter Health, in Northern California, he serves as Clinical Informatics Director for Privacy, Information Security & Interoperability. Dr. Lane has been a leader in advocating for interoperability in California and around the country through lowering barriers to information sharing and optimizing the utility of the data exchanged.
Dr. Lane began his informatics career in 1990, supporting the hospital information system at the University of California San Francisco (UCSF). He served as an EHR Ambulatory Physician Lead during Sutter Health’s Ambulatory EMR implementation in 1999, their first-in-the-country implementation of an EMR-integrated patient portal in 2001, and 29 hospital acute care implementation completed in 2015.
Dr. Lane has served as a co-chair of the Certification Commission for Healthcare Information Technology (CCHIT) Ambulatory, and Long Term & Post-Acute Care Workgroups, and as a member of the E-Prescribing Workgroup, the California Office of Health Information Integrity (CalOHII) Privacy Committee and Patient Consent & Informing Task Group, the Office of the ONC HIT Standards Committee’s Transport and Security Standards Workgroup, and the California Association of Health Information Exchanges (CA-HIE) Directory Services and Sensitive Information Workgroups. He currently serves on the boards of The Sequoia Project and the Santa Cruz Health Information Exchange, as Vice Chair of the Carequality Steering Committee, as a member of the international Epic Care Everywhere Governing Council, co-chair of the DirectTrust Clinicians Steering Workgroup, and Clinical Professor of Family & Community Medicine at UCSF.
Pharmacogenomics of Drug Induced Kidney Injury
Abstract: Acute kidney injury is a common complication in the critically ill population, is multifactorial and associated with increased mortality. Drug induced kidney injury is a significant contributor to the development of AKI. Pharmacogenomics may play a role in identifying at risk patients and mitigating risk. Phenotype standardization and clinical adjudication is essential to determining to determining the contribution of genetics to drug induced kidney injury given its multifactorial nature. Genome wide association studies allow for the detection of rare variants associated with serious adverse events. In this presentation, the audience will learn about approaches to studying pharmacogenomics of kidney injury including phenotype standardization, cohort creation, clinical adjudication, genotyping and replication of results.
Bio: Dr. Awdishu is a Professor of Pharmacy and Medicine and Chair of the Division of Clinical Pharmacy at UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences. She practices in the UCSD Chronic Kidney Disease Program and chairs the Therapeutics course series, simulation and interprofessional education program. Her research program involves pharmacokinetics and pharmacogenomics of drugs in kidney disease. She co-directed The International Drug Induced Renal Injury Consortium (DIRECT) in collaboration with The International Serious Adverse Event Consortium. The DIRECT study is investigating the genetic basis of serious drug induced renal injury, through a collaborative network comprised of leading clinical research centers from around the world. She is a co-investigator in the UAB-UCSD O’Brien Center for Acute Kidney Injury Research studying new novel biomarkers of acute kidney injury.
The Intersection of Intellectual Property and Data
Abstract: Big data is providing a new source of value for many innovative entities. For example, inventions ranging from genetic testing to fitness monitors produce large amounts of data beyond the invention itself (such as data about users). Much of this data can be kept secret by the entity that creates it, potentially indefinitely, inhibiting data sharing and reproducibility. Professor Simon will discuss how intellectual property intersects with big data and describe some of the challenges it may raise for data aggregation.
Bio: Professor Simon is a Visiting Associate Professor at the University of California, San Diego, Rady School of Management. In the upcoming academic year, she will be a Visiting Professor at California Western School of Law. Professor Simon is also a Professor and Director of the Center for Law and Intellectual Property at TJSL, and a Non-Resident Fellow at Stanford Law School. Professor Simon was recently awarded an Edison Innovation Fellowship. Before moving to San Diego, Professor Simon was the teaching fellow for the Law, Science and Technology LL.M. Program at Stanford Law School, and a fellow in the Center for Law and the Biosciences. Prior to that, Professor Simon was an associate at Fenwick & West, where she represented technology clients in intellectual property litigation, counseling and patent prosecution. Her pro bono representation of clients included successful appeals before the Ninth and Federal Circuits.
Professor Simon's research focuses on intellectual property, big data, and bioethics. Professor Simon’s articles have been published in Science, Nature Biotechnology, and numerous law reviews, such as the Northwestern University Law Review and Houston Law Review. Her article, Rules, Standards, and the Reality of Obviousness, was selected as one of the year’s best law review articles related to intellectual property and republished in Intellectual Property Law Review. Her most recent work examines the role of patents in facilitating innovation, drawing on a series of interviews she conducted with professionals from the medical device industry.
How Working in Government Health IT Changed My Views About the Healthcare System...and My Mailman
Bio: Jason McNamara wants to live in a world where communities are healthy and trust one another; wine and scotch doesn’t add extra inches to our inseams; and everyone has more time to spend with those they love, doing the activities they cherish the most. As a Health IT professional with over 15 years of experience, he’s worked with the Centers for Medicare and Medicaid Services (CMS), the Military Health System, clinical software vendors, and solution providers on the implementation of EHRs, Health IT tools, Health Information Exchange Infrastructure, and national HIT policy programs. His graduate studies at The Johns Hopkins School of Medicine were focused in Applied Health Science Informatics. When not working to make healthcare smarter at Amazon Web Services (AWS), you can find him investing in Real Estate; enjoying all of Southern California’s outdoor adventure sports and camping; teaching executive professionals at the George Washington University in public health informatics; and learning how to build new memories with his life partner and their son.
Real Time Research: Getting the Public Back in Public Health
Abstract: Priorities in public health have historically been set using a top-down framework where the health needs of the public are proclaimed by a few experts and can remain rigid for decades. This is because traditionally health research is data starved and relies on labor intensive strategies for data collection (e.g., telephone surveys). In the new big data era it is now possible to mine public data (including internet searches, social media posts, news articles, etc.) to discover the health needs of the public in near real time. To
demonstrate the value of ta bottom-up research agenda John will show how he uses big media data to discover and respond to emerging health needs, often when no other scientific data are available. In addition
he will describe several case studies where a bottom up research has directly impacted the health of thousands or millions.
Bio: Dr. Ayers is committed to getting the public back in public health. He passively assesses and responds to the public’s health needs by harnessing internet search queries, intelligent virtual assistants, news media, social media, and online networks. Beginning in 2011 he showed electronic cigarettes were the most popular smoking alternative on the market, being the first to predict their rise. This study has been followed by several examples of unique discoveries making public health science more responsive to the public and more effective in the process. For instance, his recent JAMA Internal Medicine report describing how Charlie Sheen’s HIV-positive disclosure prompted record-levels of public engagement with condoms, HIV symptoms, and HIV testing was covered in more than 6,000 news outlets and trended on both Facebook and Twitter. The publication of this report was later linked to a significant increase in HIV testing and made more impactful by partnering with several medical device makers to implement follow-up campaigns encouraging at-home HIV testing and condom use. His work has also been trans-disciplinary (e.g., he has published with more than 75 different collaborators from applied mathematics, climatology, communications, computer science, economics, engineering, political science, sociology, and more). Dr. Ayers has published more than 60 peer-reviewed articles and several commentaries/op-eds, that consistently rank in the top 1% of Altmetric’s research rankings (including several that are among the most circulated articles in science among a reference group of 7 million plus articles). He has an h-index of 30. Dr. Ayers is frequently featured in the media, including coverage in traditional news (e.g., ABC, CBS, NBC, etc.), tech or business focused news (e.g., Bloomberg, Popular Science, Wired, etc.), and entertainment news (e.g., Dr. Drew, Dr. Oz, Saturday Night Live, etc.). Dr. Ayers never forgot from where he came: a trailer in the Appalachian mountains of North Carolina. As a result, his focus remains on helping disadvantaged people and executing a science that impacts outcomes for millions at a time.
The Repertoire of Mutational Signatures in Human Cancer
Abstract: Somatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.
Bio: Ludmil Alexandrov is an Assistant Professor of Cellular and Molecular Medicine and Bioengineering at the University of California, San Diego. He earned his Bachelor of Science degree in Computer Science from Neumont University and received his Master’s of Philosophy in Computational Biology as well as his Ph.D. in Cancer Genetics from the University of Cambridge.
Ludmil’s research has been focused on understanding the mutational processes in cancer. In 2013, he developed the first comprehensive map of the mutational signatures in human cancer. More recently, Ludmil mapped the signatures of clock-like mutational processes operative in normal somatic cells, demonstrated that mutational signatures have the potential to be used for targeted cancer therapy, and identified the mutational signatures associated with tobacco smoking.
Ludmil has 84 publications in peer-reviewed journals from which 21 publications in Nature, Science, or Cell and another 29 publications in Nature Genetics, Nature Medicine, Cancer Cell, Science Translational Medicine, PNAS, or Nature Communications. In 2014, Ludmil Alexandrov was recognized by Forbes magazine as one of the “30 brightest stars under the age of 30”. In 2015, he was awarded the Prize for Young Scientists in Genomics and Proteomics by Science magazine and SciLifeLab, and he also received a Harold M. Weintraub Award by the Fred Hutchinson Cancer Center. In 2016, Ludmil was awarded the Carcinogenesis Young Investigator Award by Oxford University Press. In 2018, Ludmil was awarded the Balfour Prize Lecture of the Genetics Society, an Alfred P. Sloan Research Fellowship in Computational & Evolutionary Molecular Biology, and an Early Career Award by The International Academy for Medical and Biological Engineering. Ludmil is currently one of six co-investigators leading the Mutographs of Cancer project, a £20 million initiative to identify the unknown cancer-causing factors.
Epilepsy Precision Medicine: A Personal and Scientific Perspective
Abstract: Diagnostic exome sequencing can identify a disease-driving gene in 30-50% of patients with pediatric-onset, uncontrolled epilepsy. Further, more than 300 human epilepsy genes have been identified and new genes continue to be discovered. This knowledge has led to the identification of a number of precision therapies designed to target the causal genetic defect in some of these severely impacted patients. Performing research on her own child with intractable epilepsy, which led to an effective precision therapy, Dr. Dixon-Salazar will highlight how patients are innovatively supporting research in the quest for meaningful medical solutions and how harnessing knowledge that only patients have, can lead to critical medical breakthroughs.
Bio: Dr. Dixon-Salazar is a neuroscientist, geneticist, and, patient advocate. Her desire to get her Ph.D. was inspired by her daughter who developed Lennox-Gastaut Syndrome (LGS) at the age of 2. She did her Ph.D. and post-doctoral work at UC, San Diego where she studied the mechanisms of brain development and synaptic plasticity, identified genetic causes of rare disorders in children, and researched precision therapeutics in stem cell and animal models of pediatric disease. During her research tenure, and after 16 years of watching daily, unrelenting seizures in her child, she uncovered the driver of her daughter's illness and identified a novel precision therapy that improved her child's life. Dr. Dixon-Salazar is an accomplished scientist, proven thought leader, highly sought-after speaker, and staunch advocate for genomic medicine, patient-centric research, and patient engagement.
3D Visualization and Segmentation of MRI Data of Crohn's Disease Patients
Bio: Dr. Jurgen Schulze is an Associate Research Scientist at UCSD's Qualcomm Institute, and an Associate Adjunct Professor in the computer science department, where he teaches computer graphics and virtual reality. His research interests include applications for virtual and augmented reality systems, 3D human-computer interaction, and medical data visualization. He holds an M.S. degree from the University of Massachusetts and a Ph.D. from the University of Stuttgart, Germany. After his graduation he spent two years as a post-doctoral researcher in the Computer Science Department at Brown University working on real-time volume rendering in virtual reality. Dr. Schulze is the director of the Immersive Visualization Laboratory at UCSD's Qualcomm Institute.
Privacy Considerations for Future Data Stewards
Abstract: The many potential uses of individuals’ health information – some not yet imagined – present privacy-related risks to individuals, communities, and societies that may be difficult to foresee. However, when privacy is breeched, consumers, journalists, and policy makers often respond with shock and outrage. In this presentation, Dr. Schairer will review important considerations for anyone poised to collect, process, or analyze large health datasets. She will discuss both the power and the dangers of collecting highly granular health information and present insights from her current research on understanding individuals’ comfort with sharing health information.
Bio: Cindy Schairer is currently a project scientist in the Department of Family Medicine and Public Health at the UC San Diego School of Medicine. Dr. Schairer is a sociologist and qualitative researcher with a focus on ethical concerns about and stakeholder attitudes toward emerging technology. She has collaborated on numerous projects focused on technologies such as HIV molecular epidemiology, genetically engineered mosquitoes with gene drive, and digital health platforms, exploring issues of privacy, confidentiality, and individual autonomy in public health interventions.
Progress Toward Digital Transformation: APIs, Virtual Care, and Patient Engagement
Abstract: Dr. Neinstein will discuss the UCSF Center for Digital Health Innovation’s approach toward driving full-stack digital transformation through partnerships, use of APIs, operational change, modern development practices, and engagement in national policy issues.
Bio: Aaron Neinstein is Associate Professor in the UCSF Division of Endocrinology and Director of Clinical Informatics at the UCSF Center for Digital Health Innovation, with a clinical practice focused on diabetes care. Dr. Neinstein, an inaugural inductee as a Fellow of the American Medical Informatics Association, has focused his career on empowering patients and physicians to better access, share, understand, and use health information for more connected, collaborative care. He helped lead the Epic EHR implementation at UCSF and was on the founding team of Tidepool, a non-profit that creates open-source software to empower people with diabetes. At the UCSF CDHI, he leads a multi-disciplinary team focused on advancing interoperability and digital transformation of care delivery.
Applied Clinical Informatics at UCSD
Bio: Brian Clay, MD, is an academic hospitalist and Chief Medical Information Officer at UC San Diego Health. His academic interests include applied clinical informatics, especially as leveraged to improve patient safety, quality of care, and physician and patient experience. He has led multiple implementations of electronic medical record and other clinical applications at UCSD, and is currently working to enhance mobile technology throughout the organization. Dr. Clay received his M.D. from the UC San Diego School of Medicine in 2000, and completed his residency training in Internal Medicine at Vanderbilt University in Nashville, Tennessee in 2003. He has served as a faculty member at UC San Diego Health for 15 years and is currently a Clinical Professor of Medicine in the UCSD Division of Hospital Medicine.
Using the Creative Process as a Computational Framework for Unfolding Complex Systems
Abstract: In my research one picture is worth approximately 60 million voxels. How can one find patterns in complex information and work with the information creatively and intuitively leading to new and unique innovation? Visualization of a complex system is not the end goal. It is the beginning of the representation of immersive, interactive, data, mathematical information that can then be transformed through experimentation and simulation on the proper computational platform. A mathematical/computational software framework that can parse a complex system, encompassing the physics, chemistry, and biology of that system, through interactive visualization tied directly to computation is needed to tackle accurate physical models of complex systems.
By applying the creative compositional process of sketching in building our multimodal (visual/sonic/gestural) rendering system, and tying this directly to interactive computation and a computational notebook infrastructure, a comprehensive multimedia computing system that seamlessly allows a researcher to move from interactive display, to computation, will enable the same type of workflow that artists experience when creating a work of art. This will facilitate the uncovering of new patterns in complex information, using our senses, with a direct connection to the computational/processing system.
Using this compositional framework within the AlloSphere, one of the largest display devices in the world for multi-modal data representation and an ideal platform for designing our n-dimensional sketching system, we have developed a series of prototypes and solutions for immersive multimodal mappings of complicated scientific data.
Bio: Dr. JoAnn Kuchera-Morin Director and Chief Scientist of the AlloSphere Research Facility (www.allosphere.ucsb.edu), Professor of Media Arts and Technology and Music. Her research focuses on creative computational systems, multi-modal media systems content and facilities design. Her years of experience in digital media research led to the creation of a multi-million dollar sponsored research program for the University of California—the Digital Media Innovation Program. She was Chief Scientist of the Program from 1998 to 2003. The culmination of Professor Kuchera-Morin’s creativity and research is the AlloSphere, a 30-foot diameter, 3-story high metal cylinder inside an echo-free cube, designed for immersive, interactive scientific and artistic investigation of multi-dimensional data sets. Scientifically, the AlloSphere is an instrument for gaining insight and developing bodily intuition about environments into which the body cannot venture—abstract higher-dimensional information spaces, the worlds of the very small or very large, and the realms of the very fast or very slow. Artistically, it is an instrument for the creation and performance of avant-garde new works and the development of new modes and genres of expression and forms of immersion-based entertainment. Professor Kuchera-Morin serves as the Director of the AlloSphere Research Facility located within the California NanoSystems Institute, Elings Hall, at the University of California, Santa Barbara. JoAnn Kuchera-Morin earned a Ph.D. in composition from the Eastman School of Music, University of Rochester.
Adult Medicaid Benefit Generosity and Receipt of Recommended Health Services among Low-income Children: The Spillover Effects of Medicaid Adult Dental Coverage
Abstract: Low-income children are less likely to receive recommended health services than their high-income counterparts. This research examines whether the design of parental Medicaid benefit packages could serve as a mechanism for reducing income-based disparities in unmet health care needs, considering dental benefits as a case study. Leveraging state-level changes to adult dental benefits over time, I find that coverage is associated with increases of 14 and 5 percentage points, respectively, in the likelihood of a recent dental visit among parents and children directly exposed to the policy. Child effects appear to be concentrated among younger children under age 12.
Bio: Brandy Lipton is an Assistant Professor in the Graduate School of Public Health at San Diego State University. She is an applied microeconomist specializing in health economics and public policy. Her core interests lie in exploring the connections between health care policies and both health and economic outcomes. The majority of her work leverages state-level variation in public health insurance policies. For example, recent research has explored the effects of optional benefits in Medicaid on adult health and labor market outcomes. Ongoing work is examining whether adult Medicaid benefits affect outcomes among children of adult enrollees. Dr. Lipton's research has been published in outlets such as Journal of Health Economics, Health Affairs, and Social Science and Medicine. Prior to joining San Diego State University, Dr. Lipton spent four years in Washington DC conducting research for the federal government. She received her PhD in economics from Northwestern University.