John F. Hurdle, MD, PhD
- Nutritional Data Mining
- Clinical Natural Language Processing
- Ethics Committees, Research
- Health Services
- Departments: Biomedical Informatics - Professor
Academic Office Information
421 Wakara Way, Room: Suite 140, Room 2028
Salt Lake City, UT 84108
I started my informatics career with a keen desire to improve patient safety, especially in the realm of medication errors (which, at the time, were estimated to be causing over 100,000 needless fatalities a year in the US). Over the past 15 years, I developed a very strong interest in applying natural language processing (NLP) tools to clinical narratives. My work on adverse drug events convinced me that there were important signals in clinical notes (aka "unstructured data") that can be used to improve patient care. After completing an NLP Senior Fellowship sponsored by the National Library of Medicine, I was awarded two research grants from the NIH to explore the utility of preprocessing clinical text to make clinical NLP more useful and efficient. My POET natural language processing lab works to develop practical and efficient tools that can extract information locked in clinical narrative text. Increasingly we need the information that can only be found in text to augment traditional structured information like laboratory test results, or medication lists. In combination, these two types of data are essential for modern data analytics and data science apps.
More recently I developed an interest in the nascent field of Nutrition Informatics. So my other lab focuses on nutrition data mining (NDM). Nutrition informatics holds great promise, especially as the United States faces an epidemic of diet-related diseases such as obesity, type II diabetes, and malnutrition. Nutrition informatics is very much in its infancy, and our Department is the first major informatics program to engage nutrition in a serious and principled way. Our primary goal for this work centers on building scalable tools that can measure the food quality of what households buy (in grocery stores or online) coupled to targeted, personalized recommendations designed to nudge households towards a healthier household food environment.
Main Research Interests: practical Natural Language Processing for clinical and biomedical text applications; finding smart and inexpensive ways to assess the grocery quality of the foods households buy at grocery stores and online.
Education: Dr. John F. Hurdle earned his MD from the University of Colorado (1981) and his MS in Computer Science from Columbia University the same year, followed by a PhD in Computer Science from the University of Utah (1994). He took his informatics postdoctoral training here at Utah (1996-97). Following his postdoctoral training, Dr. Hurdle worked as a research clinical informaticist at the Salt Lake Veterans Medical Center’s (VAMC) Geriatric Research, Education, and Clinical Center (1998-2004). While there, he was the Principal Investigator on two VA Health Services Research and Development (HSRD) Grants, the first such grants funded at that VAMC in over two decades. His small center grant from HSRD has grown into a multi-million dollar HSRD enterprise at the VAMC and includes the VA’s primary informatics research infrastructure, VINCI.
At the University of Utah: He joined the Department of Biomedical Informatics (BMI) as a regular faculty member in 2005. In 2007 he served as a Senior Fellow at the National Library of Medicine. Dr. Hurdle holds the rank of Professor. His work in the BMI spans clinical informatics, clinical research informatics, and public health/consumer health informatics. In addition to a long-standing commitment to improving patient safety, he currently directs a lab that focuses on clinical natural language processing (NLP) and another lab that focuses on nutrition data mining (NDM) . The POET NLP lab builds tools to unlock the content of clinical narratives using NLP, so that this content can be used to assist the healthcare enterprise. The QualMART NDM lab is comprised of University of Utah researchers, graduate students, and post-docs who have expertise in computer science, biomedical informatics, nutrition, and consumer behavior. Our long-term goal focuses on improving the quality of what people eat in order to improve their overall quality of life. Our approach uses weaves of together consumer behavior theory, high-performance computing and simulation, cutting-edge nutrition modeling, and large-scale database management.
Etc.: In addition to research, he is active in both service and education,. He served as the Department’s Director of Graduate Studies from 2008 to 2016 and was the principal investigator of the BMI T15 NLM Training Grant for nearly a decade. Dr. Hurdle has served as a grant reviewer for the National Library of Medicine’s Standing Study Section (2008-2012) and continues to participate in special emphasis panel grant reviews for NLM and other NIH institutes. He served as Chair of the American Medical Informatics Association’s Ethics Committee when it created AMIA’s first code of professional conduct. He also served as member, Vice Chair, and Chair of the University’s Institutional Review Board (1999 – 2016) as well as Chair of the Resource for Genetic and Epidemiologic Research (2011-present), the data governance body overseeing the use of the Utah Population Database.
“I was once asked by a recruiter how I could rationalize staying in academic biomedical informatics rather than work in industry for a lot more money. ‘Oh that’s easy’, I told her, ‘In industry I would be working on what they want – in academics, I work on what I want.’”
|Research Fellow||National Institutes of Health/NLM
|Senior Research Fellow|
|Postdoctoral Fellowship||University of Utah, Department of Medical Informatics and The Veterans Administration
|Doctoral Training||University of Utah
|Graduate Training||Columbia University
|Professional Medical||University of Colorado, Denver
|University of Maryland (European Division), Computer Studies||Adjunct||Germany|
|University of Maryland, European Division||Director (CIO), Info Systems, Admin Computing, Institutional Research||Germany|
- Brewster P, Guenther PM, Jordan KC, Hurdle JF (2015). Development and Validation of a Novel Household Grocery Food Purchase Quality Score. FASEB J, 29(1), 131-3.
- He S, Botkin JR, Hurdle JF (2015). An Analysis of Information Technology Adoption by IRBs of Large Academic Medical Centers in the United States. J Empir Res Hum Res Ethics, 10(1), 31-6.
- Tran LT, Brewster PJ, Chidambarab V, Hurdle JF (06/20/2015). Towards Measuring the Food Quality of Grocery Purchases: an Estimation Model of the Healthy Eating Index-2010 Using only Food Item Counts. doi:10.1016/j.profoo.2015.06.020. Procedia Food Sci, 4, 148-159.
- Hurdle JF, Haroldsen SC, Hammer A, Spigle C, Fraser AM, Mineau GP, Courdy SJ (09/15/2014). Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database.IMIA Yearbook of Medical Informatics 2014. Yearbook of Medical Informatics.
- He S, Narus SP, Facelli JC, Lau LM, Botkin JR, Hurdle JF (2014). A domain analysis model for eIRB systems: addressing the weak link in clinical research informatics. J Biomed Inform, 52, 121-9.
- Bradford W, Hurdle JF, LaSalle B, Facelli JC (2014). Development of a HIPAA-compliant environment for translational research data and analytics. J Am Med Inform Assoc, 21(1), 185-9.
- Chidambaram V, Brewster PJ, Jordan KC, Hurdle JF (2013). qDIET: toward an automated, self-sustaining knowledge base to facilitate linking point-of-sale grocery items to nutritional content. AMIA Annu Symp Proc, 2013, 224-33.
- He S, Ganzinger M, Hurdle JF, Knaup P (2013). Proposal for a data publication and citation framework when sharing biomedical research resources. Stud Health Technol Inform, 192, 1201.
- Hurdle JF, Smith KR, Mineau GP (2013). Mining electronic health records: an additional perspective. Nat Rev Genet, 14(1), 75.
- Hurdle JF, Haroldsen SC, Hammer A, Spigle C, Fraser AM, Mineau GP, Courdy SJ (2013). Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database. J Am Med Inform Assoc, 20(1), 164-71.
- Brinkerhoff KM, Brewster PJ, Clark EB, Jordan KC, Cummins MR, Hurdle JF (2011). Linking supermarket sales data to nutritional information: an informatics feasibility study. AMIA Annu Symp Proc, 2011, 598-606.
- He S, Hurdle JF, Botkin JR, Narus SP (2010). Integrating a Federated Healthcare Data Query Platform With Electronic IRB Information Systems. AMIA Annu Symp Proc, 2010, 291-5.
- Facelli LC, Hurdle JF, Mitchell JA (February 2012). Medical and Bioinformatics. In Ziad O., Abu-Faraj (Eds.), Biomedical Engineering Education & Advanced Bioengineering Learning: Interdisciplinary Concepts. Hershey, PA: IGI GLOBAL.
- Chidambaram VC, Brewster PJ, Tran T, Jordan KC, Hurdle JF (2014). qDIET: Toward Calculating HEI Scores From Grocery Store Sales Data. Proc NJNDC 2014, Portland, OR: NNDC.
- Tran LT, Brewster PJ, Chidambaram V, Hurdle JF (2014). An Estimation Model of the Healthy Eating Index 2010 to Measure the Dietary Quality of Grocery Purchases. (poster) [Abstract].
- Brewster PJ, Hurdle JF (June, 2011). Dietary Pattern Analysis Using Electronic Grocery Transaction Data. Poster session presented at National Library of Medicine Annual Training Conference 2011, Bethesda, MD.