Yiye Zhang   Assistant Professor

Phone
  • +1 646 962 9437

My research is about how to better leverage information technology (IT) to reduce cost while improving health care. No improvement can be achieved without a thorough understanding of the status-quo. Therefore, I am interested in developing algorithms and software to assist our understanding of the current status of care, and provide decision support for its stake holders: clinical workflow, provider workload, patients' clinical trajectories. 

As an informatics researcher, I am especially passionate about data inference techniques for electronic health records (EHR), that captures critical information about health care, and yet have an extremely complex and dynamic data structure for analysis. Here are two broad areas that I work on:
*Clinical Pathway/Trajectories
The volume and complexity of health data have been a challenge in the data mining community. Since we deal with patients, the data is complex cross-sectionally and longitudinally. To address this data mining challenge, I have developed an algorithm and software to mine and visualize complex patient clinical pathways, and to predict outcomes based on individual pathways. This algorithm is currently being applied to study patients with (1) multiple chronic conditions (MCC) especially those with chronic kidney disease (CKD), (2) left-ventricular assist device (LVAD), (3) undifferentiated complaints such as dizziness and abdominal pain, among other projects under preparation. 

*Computerized Physician Order Entry (CPOE)
We cannot blindly adopt health IT and expect humans to benefit from it. I believe the best form of IT is one that supports human decision making while tacitly guiding it toward optimal outcomes. With this in mind, I have developed an algorithm and software to develop order sets, a core function of the CPOE, by studying the actual usage of them by providers in daily routine. My algorithm was shown to reduce providers’ physical and cognitive workload when evaluated using historical data.

Keywords: Clinical Workflow, Clinical Decision Support, Data Visualization, Chronic Kidney Disease

Publications

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Teaching

teaching overview

  • Big Data Management, Spring 2017

Background

Contact

Primary Email

  • yiz2014@med.cornell.edu