Jonathan H. Chen, MD, PhD, Physician Data Scientist
 Personal Information
Email     jonc101 (at) stanford.edu
Phone     (626) 840-4491 (cell / voicemail)
  (650) 725-3655 (office)
Office     1265 Welch Rd
  MSOB X213
  Stanford, CA 94305
Calendar     [Request Meeting]
Skype     jonc101x
Twitter     @jonc101x
CV     [CV] [Biosketch]
Stanford Affiliations
  • Department of Medicine
  • Biomedical Informatics Research
  • Hospital Medicine
  • Primary Care and Population Health

  •  Peer-Reviewed Publications
    Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations
    Chen, J.H., Asch, S.M. New England Journal of Medicine (2017)
    Related Press: [Nature Medicine] [PBS Nova] [Eric Topol] [Cross Invalidation] [Healthcare Analytics] [FierceHealthcare 1] [FierceHealthcare 2] [FierceHealthcare 3] [ClinicalOMICS] [Medscape]
    Decaying Relevance of Clinical Data Towards Future Decisions in Data-Driven Inpatient Clinical Order Sets
    Chen, J.H., Alagappan, M., Goldstein, M.K., Asch, S.M., Altman, R.B. International Journal of Medical Informatics (2017)
    The New HIT: Human Health Information Technology
    Leung, T.I., Goldstein, M.K., Musen, M.A., Cronkite, R., Chen, J.H., Gottlieb, A., Leitersdorf, E. MEDINFO (2017)
    Effect of Opioid Prescribing Guidelines in Primary Care
    Chen, J.H., Hom, J., Richman, I., Asch, S.M., Podchiyska, T., Atwan Johansen, N. Medicine (2016)
    Predicting Inpatient Clinical Order Patterns with Probabilistic Topic Models vs. Conventional Order Sets
    Chen, J.H., Goldstein, M.K., Asch, S.M., Mackey, L., Altman, R.B. Journal of the American Medical Informatics Association (2016)
    Use of Opioid Agonist Therapy for Medicare Patients in 2013
    Lembke, A., Chen, J.H. JAMA Psychiatry (2016)
    Related Press: [Medscape] [Pacific Standard] [Kaiser Health] [US News] [Healio] [Med Page Today] [Clincial Advisor] [Pew Trusts] [Modern Healthcare]
    Fulfilling Outpatient Medicine Responsibilities During Internal Medicine Residency: A Quantitative Study of Housestaff Participation with Between Visit Tasks
    Hom, J., Richman, I., Chen, J.H., Singh, B., Crump, C., Chi, J. BMC Med. Educ. 2016;16(1):139. doi:10.1186/s12909-016-0665-6.
    Patient Outcomes When Housestaff Exceed Eighty Hours per Week
    Ouyang, D., Chen, J.H., Krishnan, G., Hom, J., Witteles, R., Chi, J. American Journal of Medicine (2016)
    The Patient You Least Want To See [A Piece of My Mind]
    Chen, J.H. JAMA (2016)
    Related Press: [Health Affairs] [Scope]
    Dynamically Evolving Clinical Practices and Implications For Predicting Medical Decisions
    Chen, J.H., Goldstein, M.K., Asch, S.M., Altman, R.B. Pacific Symposium of Biocomputing (2016)
    Distribution of Opioids by Different Types of Medicare Providers
    Chen, J.H., Humphreys K., Shah, N.H., Lembke, A. JAMA Internal Medicine (2016)
    Related Press: [CNN] [NY Times 1] [NY Times 2] [Washington Post] [USA Today] [NBC] [HuffPost Live] [Medscape] [Kaiser Health 1] [Kaiser Health 2] [Kaiser Health 3] [Kaiser Health 4] [STAT 1] [STAT 2] [Pacific Standard Magazine] [Christian Science Monitor] [UPI] [Philly] [Medical Daily] [Pain Medicine] [Science News] [Stanford Medicine] [Cleveland.com] [Sacramento Bee]
    Internal Medicine Resident Computer Usage: An Electronic Audit of an Inpatient Service
    Ouyang D, Chen JH, Hom J, Chi J. JAMA Internal Medicine (2016)
    Related Press: [MedPage Today] [MedicalResearch.com]
    OrderRex: Clinical Order Decision Support and Outcome Predictions by Data-Mining Electronic Medical Records
    Chen, J. H., Podchiyska, T. & Altman, R. B. Journal of the American Medical Informatics Association ocv091 (2016). doi:10.1093/jamia/ocv091
    [IMIA 2016 Best Papers in Secondary Use of Patient Data]
    Improving and Sustaining a Reduction in Iatrogenic Pneumothorax through a Multifaceted Quality Improvement Approach
    Shieh, L., Go, M., Gessner, D., Chen, J.H., Hopkins, J., Maggio, P. Journal of Hospital Medicine 2015;10(9):599-607. doi:10.1002/jhm.2388
    Data-Mining Electronic Medical Records for Clinical Order Recommendations: Wisdom of the Crowd or Tyranny of the Mob?
    Jonathan H. Chen, Russ B. Altman. AMIA Joint Summits on Translational Science Proceedings (2015)
    (Best Student Paper Award, Finalist)
    Development and Evaluation of an Electronic Medical Record–Based Best-Practice Discharge Checklist for Hospital Patients
    Garg, T., Lee, J. Y., Evans, K. H., Chen, J., & Shieh, L. (2015). The Joint Commission Journal on Quality and Patient Safety. 41, 126 (2015).
    Why providers transfuse blood products outside recommended guidelines in spite of integrated electronic best practice alerts
    Chen, J. H., Fang, D. Z., Tim Goodnough, L., Evans, K. H., Lee Porter, M., & Shieh, L. (2014). Journal of Hospital Medicine : An Official Publication of the Society of Hospital Medicine. doi:10.1002/jhm.2236
    Automated Physician Order Recommendations and Outcome Predictions by Data-Mining Electronic Medical Records
    Jonathan H. Chen, Russ B. Altman. AMIA Joint Summits on Translational Science Proceedings (2014)
    (Winner of Best Student Paper Award)
    Mining for Clinical Expertise in (Undocumented) Order Sets to Power an Order Suggestion System
    Chen, J. H., & Altman, R. B. (2013). AMIA Joint Summits on Translational Science Proceedings (2013), 34–8.
    Learning to Predict Chemical Reactions
    Matthew A. Kayala, Chloe-Agathe Azencott, Jonathan H. Chen, and Pierre Baldi. Journal of Chemical Information and Modeling 2011 51 (9), 2209-2222 (2011)
    Reaction Explorer: Towards a Knowledge Map of Organic Chemistry To Support Dynamic Assessment and Personalized Instruction
    Jonathan H. Chen, Matthew A. Kayala, Pierre Baldi. Enhancing Learning with Online Resources, Social Networking, and Digital Libraries, American Chemical Society. p. 191-209, (2010)
    No Electron Left-Behind: A Rule-based Expert System to Predict Chemical Reactions and Reaction Mechanisms
    Jonathan H. Chen, Pierre Baldi. Journal of Chemical Informatics and Modeling 49(9): 2034-2043, (2009)
    Synthesis Explorer: A Chemical Reaction Tutorial System for Organic Synthesis Design and Mechanism Prediction
    Jonathan H. Chen, Pierre Baldi. Journal of Chemical Education 2008(85):1699, (2008)
    ChemDB Update - Full-Text Search and Virtual Chemical Space
    Jonathan H. Chen, Erik Linstead, S. Joshua Swamidass, Dennis Wang, and Pierre Baldi. Bioinformatics 2007 23(17):2348-2351
    One- to Four-Dimensional Kernels for Small Molecules and Predictive Regression of Physical, Chemical, and Biological Properties
    Chloe-Agathe Azencott, Alexandre Ksikes, S. Joshua Swamidass, Jonathan Chen, Liva Ralaivola, and Pierre Baldi. Journal of Chemical Informatics and Modeling, 47(3):965-974, (2007)
    ChemDB: A Public Database of Small Molecules and Related Chemoinformatics Resources
    Jonathan Chen*, S. Joshua Swamidass*, Yimeng Dou, Jocelyne Bruand, Pierre Baldi. Bioinformatics, 21(22):4133-4139, (2005)
    Kernels for Small Molecules and the Prediction of Mutagenicity, Toxicity, and Anti-Cancer Activity
    S. Joshua Swamidass*, Jonathan Chen*, Peter Phung, Jocelyne Bruand, Liva Ralaivola, and Pierre Baldi. Proceedings of the 2005 Conference on Intelligent Systems for Molecular Biology, ISMB 05. Bioinformatics, 21, Supplement 1, i359-368, (2005).
    Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants
    S. A. Danziger, S. J. Swamidass, J. Zeng, L. R. Dearth, Q. Lu, J. H. Chen, J. Cheng, V. P. Hoang, H. Saigo, R. Luo, P. Baldi, Rainer K. Brachmann, and Richard H. Lathrop. IEEE-ACM Transactions on Computational Biology and Bioinformatics 2006, 3, (2), 114-125
    * These authors contributed equally

     Additional Publications
    Clinical Informatics: Journeys into an Emerging Subspecialty
    Leung T, Chen JH. SGIM Forum (2017)
    The Training of Next Generation Data Scientists in Biomedicine
    Garmire LX, Gliske S, Nguyen QC, Chen JH, Nemati S, Van Horn JD, Moore JH, Shreffler C, Dunn M. Pacific Symposium of Biocomputing (2017)
    The Impact of Big Data on the Physician
    Le, E., Iyer, S., Patil, T., Li, R., Chen, J. H., Wang, M., Sobel, E. (2017). In S. Srinivasan (Ed.), Guide to Big Data Applications. New York: Springer.

    Oral Presentations
    Impact of Clinician Mortality Metrics on Machine-Learned Clinical Order Patterns
    AMIA Annual Symposium, Washington DC, November 2017 (Student: Jason K. Wang)
    Data-Mining Electronic Medical Records for Decision Support Content: Better to Learn from Experts or to Find Wisdom in the Entire Crowd?
    CALDAR 2017: Precision Research in Addiction, HIV, and Care, Universal City, CA, August 15-17, 2017
    Intelligence in Medicine Summit, August 26, 2017
    Understanding Healthcare Reform: Pre-ACA to ACA to ...?
    Stanford Internal Medicine Residency Noon Conference, July 10+11, 2017 [Audio]
    Stanford Department of Medicine Grand Rounds, August 23, 2017 [Video]
    Deep Cohort Studies: From Google Baseline to the Precision Medicine Initiative to VA's Million Veterans
    NIH/NIDA Clinical Trials Network Invited Webinar, April 14 2017 [Video]
    CALDAR 2017: Precision Research in Addiction, HIV, and Care, Universal City, CA, August 15-17, 2017
    The Physician Data Scientist, An Unexpected Journey
    Pacific Symposium of Biocomputing, January 2017
    Stanford Internal Medicine Residency, Physician-Scientist Pathways of Distinction Conference, October 10, 2017
    Decaying Relevance of Clinical Data when Predicting Future Decisions
    NIH Big Data 2 Knowledge (BD2K) All Hands Meeting, November, 29, 2016
    Pacific Symposium of Biocomputing, January 8, 2016
    AMIA Joint Summits on Translational Science, San Francisco, CA, March 2017 (Student: Muthu Alaggapan)
    Usability of an Automated Recommender System for Clinical Order Entry
    AMIA Annual Symposium, November, 14, 2016
    Wisdom of the Crowd or Tyranny of the Mob? Data-Mining Electronic Health Records for Clinical Decision Support
    Stanford Center for Biomedical Informatics Research, September 6, 2016 [Video]
    Columbia University Department of Biomedical Informatics, September 13, 2016
    University of Pittsburgh Department of Biomedical Informatics, October 10, 2016
    UCSF Division of Hospital Medicine, November 21, 2016
    University of Washington Department of Biomedical Informatics and Medical Education, February 7, 2017
    Washington University of St. Louis, Institute for Informatics, February 14, 2017
    Opioid Prescribing Distribution: What if it's not just a few bad apples?
    NIH/NIDA Clinical Trials Network Invited Webinar, April 5, 2016
    Automated Organization of Electronic Health Record Data by Probabilistic Topic Modeling to Inform Clinical Decision Making
    Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester Mackey, Russ B. Altman
    AMIA Joint Summits on Translational Science, San Francisco, CA, 2016
    Data-Mining Electronic Health Records for Clinical Decision Support [Video]
    Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Russ B. Altman
    Stanford Mobilize Center, October 27, 2016
    OCHIN Research, May 2016
    Kaiser Permanente Division of Research, March 2016
    Stanford Department of Medicine Grand Rounds, February 2016
    Chapman University, Invited Talk, October 2015
    Stanford Primary Care and Outcomes Research (PCOR), September 2015
    Veteran Affairs Palo Alto, Center for Innovation to Implementation (Ci2i), April 2015
    OrderRex: Data-Mining Clinical Decision Support from Electronic Medical Records, Wisdom of the Crowd or Tyranny of the Mob?
    Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Russ B. Altman
    Stanford Medicine X, September 2016
    National Library of Medicine Training Conference, NIH, June 2015
    Data-Mining Electronic Medical Records for Clinical Order Recommendations, Wisdom of the Crowd or Tyranny of the Mob?
    Jonathan H. Chen, Russ B. Altman
    AMIA Joint Summits on Translational Science, San Francisco, CA, 2015
    (Finalist for Best Student Paper Award)
    Preparing for Scholarly Presentations for AMIA Annual Symposium
    AMIA Student Working Group, Webinar, Invited Presenter, August 2014
    Automated Physician Order Recommendations and Outcome Predictions by Data-Mining Electronic Medical Records
    Jonathan H. Chen, Russ B. Altman
    AMIA Joint Summits on Translational Science, San Francisco, CA, 2014
    (Winner of Best Student Paper Award)
    Mining for Clinical Expertise in (Undocumented) Electronic Order Sets
    Jonathan H. Chen, Russ B. Altman
    AMIA Joint Summits on Translational Science, San Francisco, CA, 2013
    Physician Order Suggestions Powered by Clinical Expertise Mined from (Undocumented) Order Sets
    Jonathan H. Chen, Russ B. Altman
    UC Irvine, Institute for Genomics and Bioinformatics, Invited Talk, November 2012
    Reaction Explorer: Organic chemistry online tutorial system for multistep synthesis and mechanism problems adapted to engage students through gaming interfaces
    Jonathan H. Chen, Pierre Baldi
    ACS National Meeting, Anaheim, CA, Spring 2011
    Reaction simulation expert system for synthetic organic chemistry
    Jonathan H. Chen, Pierre Baldi
    ACS National Meeting, Salt Lake City, UT, Spring 2009
    (Winner of CINF Scholarship for Scientific Excellence [Poster Version])
    Synthesis Explorer: Organic chemistry tutorial system for multistep synthesis and mechanism problems with personalized assessment and adaptive problem generation
    Jonathan H. Chen, Pierre Baldi
    ACS National Meeting, Salt Lake City, UT, Spring 2009
    Artificial Intelligence in Chemistry: An Expert Computer System for Predicting Organic Chemistry Reactions
    Jonathan H. Chen, Pierre Baldi
    National Library of Medicine Board of Regents Meeting, February 2009
    (One of only two student speakers invited to present before the board)
    Reaction mechanism prediction by transformation rules and general principles
    Jonathan H. Chen, Pierre Baldi
    ACS National Meeting, Philadelphia, PA, Fall 2008
    (Winner of CINF Scholarship for Scientific Excellence [Poster Version])
    Organic Reaction Expert Systems
    Jonathan H. Chen, Pierre Baldi
    National Library of Medicine Training Conference, NIH, Summer 2008
    Reaction prediction, classification, and retro-synthesis using a rule-based reaction expert system
    Jonathan H. Chen, Qian-Nan Hu, Pierre Baldi
    ACS National Meeting, New Orleans, LA, Spring 2008
    Synthesis Explorer: Organic chemistry tutorial system for multistep synthesis design and reaction mechanism prediction [Video]
    Jonathan H. Chen, Pierre Baldi
    ACS National Meeting, New Orleans, LA, Spring 2008
    Organic Reaction Expert Systems (including Mechanism Explorer)
    UC Irvine MSTP Retreat 2008 (Winner of Best Presentation Award)
    UC Irvine Bioinformatics Training Program Symposium 2008
    Organic Reaction Expert Systems Proposal
    UC Irvine Computer Science PhD Advancement to Candidacy, Summer 2007
    Organic Reaction Expert Systems
    UC Irvine MSTP Retreat 2007 (Winner of Best Presentation Award)
    UC Irvine Bioinformatics Training Program Symposium 2007
    Synthesis Explorer: Dynamically generated reaction and synthesis problems for organic chemistry education
    Jonathan H. Chen, Peter Phung, Pierre Baldi
    ACS National Meeting, Chicago, IL, Spring 2007
    ChemDB: A public database of small molecules and related chemoinformatics resources
    Jonathan H. Chen, Erik Linstead, S. Joshua Swamidass, Dennis Wang, Yimeng Dou, Pierre Baldi
    ACS National Meeting, Chicago, IL, Spring 2007
    Chemical Informatics Tutorial (Representations, Reactions sections) (18 MB, several files)
    ISMB 2006, Fortaleza, Brazil. Presented by Prof. Pierre Baldi. Jonathan produced primary content of "Representations" and "Reactions" sections
    Chemical Informatics: Database Searching, Similarity Measures and Property Prediction (1.3 MB)
    National Library of Medicine Training Conference, Vanderbilt University, Spring 2006
    Chemical Fingerprints and Retro-Synthetic Search (350KB)
    UC Irvine, ICS 273A - Machine Learning, Winter 2006
    Combinatorial Reactions, Applications and Discovery (2MB)
    UC Irvine MSTP Retreat 2006
    Chemical Toxicity Prediction
    UC Irvine MSTP Retreat 2005
    Chemical Informatics, The Importance of 3D Structure (2MB)
    UC Irvine, ICS 277B - Probabilistic Modeling of Biological Data, Winter 2005
    Chemical Toxicity Prediction, String Kernel Methods (200KB)
    UC Irvine, ICS 277A - Algorithms and Representations in Molecular Biology, Fall 2004
    p53 Surface Analysis (8MB)
    UC Irvine MSTP Retreat 2004
    Please do not use the contents of these presentations without express permission.
    Jonathan H. Chen, M.D.,Ph.D.
    Physician Data Scientist (Internal Medicine + Computer Science)
    When medicine had relatively few effective interventions for patient care, it was possible for an individual clinician to know it all and do it all. Experiential learning, heuristics, and pattern recognition became the norm, but collides with the current reality of an explosive growth in biomedical knowledge. With thousands of medical and surgical procedures, diagnostic tests, pharmaceutical drugs, and recognized disease states, we routinely face a combinatorial explosion of possible medical decisions.

    In the face of ever escalating complexity in medicine, integrating informatics solutions is the only credible approach to systematically address challenges in healthcare. Tapping into real-world clinical data streams 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. My group seeks to empower individuals with the collective experience of the many, combining human and artificial intelligence approaches to medicine that will deliver better care than what either can do alone.

    Honors & Awards

     Supplementary Projects
    Reaction Explorer LLC, Founding Member (2010-Present)
    • Founding partner of startup company based on a unique system for teaching complex problem-solving in organic chemistry with the aid of expert system technology.
    • Original inventor of the technology from graduate research project
    • Carried the concept through from original invention to formation of the company and translation of the technology into a profitable commercial application.
    • In partnership with John Wiley & Sons, Inc., global leader in higher education publishing, the application is now being distributed to schools around the world so that they may benefit from its unique learning advantages.
    Medical Calculation / Analysis Tools (2009-Present)

     Previous Affiliations
    Veteran Affairs (VA) Affiliations (Previous)
  • Medical Informatics Fellowship
  • Center for Innovation to Implementation (Ci2i)
  • Stanford Affiliations (Previous)
  • Altman Research Group
  • Primary Care and Outcome Research (CHP/PCOR)
  • Internal Medicine Residency
  • Translational Research and Applied Medicine
  • Resident Informatics Council
  • Clinical Investigator Pathway
  • Stanford University Hospital
  • Society of Physician Scholars
  • UC Irvine Affiliations (Previous)
  • Baldi Research Group
  • Information & Computer Science (ICS)
  • School of Medicine (SOM)
  • Medical Scientist Training Program (MSTP)
  • UC Irvine (UCI)
  • Institute for Genomics and Bioinformatics (IGB)

  • People
    Current Collaborators and Trainees
    • Santhosh Balasubramanian - Staff Developer
    • Ron Li - Fellow, Clinical Informatics
    • David Morales - Undergraduate, Computer Science
    • David Ouyang - Fellow, Cardiology
    • Shivaal Roy - Undergraduate-Masters Co-terminal, Computer Science
    • Jason K Wang - Undergraduate, Math & CS
    Previous Trainees
    • Gustavo Chavez - Research Student -> Medical Student, Stanford
    • Muthuraman Alagappan - Medical Student -> Internal Medicine Resident, Beth Israel-Deaconess
    Open Positions
    Healthcare politics and economics is about hard tradeoffs between the cost, quality, and access to healthcare. The only way to improve all three simultaneously is science and technology to advance the frontiers of practice. The world needs postdoctoral fellows and graduate students like you who are ready to tackle complex problems in healthcare through data science and decision support solutions.

    You will have the opportunity to work in close collaboration with clinicians, scientists, and healthcare systems with access to a deep clinical data warehouse (i.e., electronic medical records), broad population health data sources (e.g., national claims), and professional development resources like (grant) writing workshops and clinical shadowing experiences.

    Research topics can range from machine learning, designing, and evaluating clinical decision support content to health outcomes and epidemiologic research on the implications of physician practice against challenging issues in opioid prescribing, duty-hours restrictions, and end-of-life counseling.

    The strongest applicants will have experience in one or more key interdisciplinary areas (not all are expected, that's the point of learning together):
    1. Computer Science or Informatics:
      Proficiency in programming and software development with a habit for robust unit testing. Our group mainly develops software in a Python + SQL environment with R for additional statistical analysis. For decision support prototype development, web-based user interface design and human-computer interaction testing experience will be valuable.
    2. Statistics and Mathematics:
      Machine learning methodology (supervised and unsupervised) and evaluation including discrimination vs. calibration measures and (hyper)parameter optimization through cross-validation. Observational research methods including interpreting multivariate regression, missing data imputation, propensity score matching, and bootstrap simulations.
    3. Biomedical / Healthcare Science:
      Understanding of clinical decision making processes, healthcare quality metrics and financial incentives, decision support interfaces and pitfalls.
    For postdoctoral applicants, a track record of complete research projects and well-written, peer reviewed papers is expected. Specific responsibilities and research projects will be tuned to the career goals, technical strengths, and interests of the applicant.

    Interested applicants should submit a CV, 2-3 references, and a brief career goal statement.