Danny Wu, PhD
Danny T.Y. Wu, PhD, is a researcher in Biomedical Informatics with the University of Cincinnati.

Danny T.Y. Wu, an expert on optimizing electronic health records, recently joined the biomedical informatics team at the University of Cincinnati as an Assistant Professor. Wu received both his PhD and master’s degree from the University of Michigan School of Information. 

Wu’s research draws on human-computer interaction, data mining, information retrieval, and natural language processing to maximize the value of clinical data stored in electronic health records to improve care quality and support clinical and translational research. Here, he tells us a little more about himself and his research goals: 

How did you first become interested in pursuing informatics?

When I was a second-year master’s student at the University of Michigan School of Information, I got the chance to be involved in a project investigating online doctor ratings and forum questions, which is an eye-opening experience.

In this project, I learned not only how to do research, but also how research could improve people’s health. I decided to work in this health informatics area because I wanted to use my informatics skills to make a greater impact. 

Could you describe your lines of research? 

Currently, I have four research lines:

  • Clinical Workflow Analysis
  • Visual Analytics
  • Medical Information Retrieval
  • Patient Communication

While these research lines are distinct and focused on different problems, together they facilitate the collection, use, and reuse of clinical data to improve care quality. 

What excites you most about the future of your area of study?

My research area, clinical and health informatics, is relatively new. There are a lot of opportunities to pursue and problems to solve. 

Take clinical workflow analysis for example. Clinical data are often captured in an inefficient and inaccurate manner due to the failure to consider clinical workflow. In this research, my goals are to conduct novel and mixed-method workflow analysis to uncover hidden patterns of clinicians’ work processes, identify significant bottlenecks, and inform a better design of health IT solutions.

Image of the iCDCU lab
Danny T.Y. Wu and some of his lab staff.

I’m also excited about our work to enable the retrieval of clinical notes. While unstructured clinical data are still pervasively used because of their flexibility and expressivity, the information is locked in the sentences and cannot be used easily for clinical care and research. We’re conducting research to improve the use of a medical information retrieval tool called Electronic Medical Search Engine (EMERSE), which can serve as a core tool to access free-text data. 

Another research investigation I would like to share involves improving the readability and the comprehensibility of clinical notes for patient communication. There has been evidence that patients can benefit from having direct, electronic access to their medical records including clinical notes. For example, patients can review their medical history, engage in effective self-management, and make decisions jointly with their providers. Unfortunately, a majority of patients have insufficient knowledge to read and understand clinical notes written by healthcare professionals.

I am working with a Natural Language Processing (NLP) expert at UC’s Electrical Engineering and Computer Sciences department to develop computerized methods and systems to enhance the readability and comprehensibility of clinical notes for patients. For example, imagine the usefulness of a tool that allows clinicians to semi-automatically translate clinical notes to a version suitable for laypeople.

What drew you to work with the University of Cincinnati?

My work requires a team of interdisciplinary researchers and easy access to clinical and health data. At UC and Cincinnati Children’s, we have world-leading research teams, abundant clinical and health data, and great academic departments, including design, business, and engineering. These factors all provide a great environment to support my interdisciplinary work. 

What do you want other researchers to know about you?

I am very collaborative, and would like to form interdisciplinary teams to pursue funding opportunities. I’m working to make my lab a community of people with passions – talented informatics researchers, data analysts, software developers, statisticians, trainees, and students – all working together to optimize electronic health records and to improve people’s health.

What do you look for in students?

Attitude. I am interested in taking students who are open-minded, dependable, and self-motivated. A great example is Paul Murdock, an undergraduate student who came with me to the AMIA Informatics Summit in March and presented a poster about our work. I have been fortunate to find several great students already, including our biomedical informatics PhD students PJ Van Camp and Charles Kronk, and look forward to many more in the future. 

Students interested in working with Dr. Wu can email him (wutz@ucmail.uc.edu) their resume to discuss opportunities.