Public Health Seminar Series:

Collaborative Search in Electronic Health Records by Kai Zheng, Ph.D.

CO-SPONSOR: UC Irvine Branch of the California Census Research Data Center

Monday, May 12, 2014 12:00 pm - 1:00 pm CAL-IT2 Auditorium OCW Video Archive
Seminar Abstract

A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users’ lack of search expertise and/or medical-domain knowledge. To mitigate the issue, we experimented with a ‘collaborative search’ feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users’ collective wisdom to improve the quality and efficiency of information retrieval.

The evaluation study was conducted over a 4-year period involving a total of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. The results show that the users embraced the collaborative search concept with considerable enthusiasm: about half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Collaborative search, a social information-foraging technique popularly used on the web, may therefore provide the potential to improve the quality and efficiency of information retrieval in healthcare.

Speaker Biography - Kai Zheng, Ph.D.

Kai Zheng, Ph.D.
Kai Zheng, Ph.D. School of Public Health, Associate Professor of Information, School of Information, University of Michigan
Dr. Kai Zheng, is jointly appointed as Associate Professor of Health Management and Policy in the School of Public Health and Associate Professor of Information in the School of Information at the University of Michigan. He is also affiliated with the University of Michigan’s School of Nursing, Michigan Institute for Clinical and Health Research, Medical School Department of Computational Medicine and Bioinformatics, and Center for Entrepreneurship. He co-directs the Bio-Repository and Biomedical Informatics Core of the University of Michigan Health System and Peking University Health Science Center Joint Institute for Translational and Clinical Research.

He received his Ph.D. degree from Carnegie Mellon University where his dissertation entitled “Design, Implementation, User Acceptance, and Evaluation of a Clinical Decision Support System for Evidence-Based Medicine Practice” won the University’s 2007 William W. Cooper Doctoral Dissertation Award in Management or Management Science. He is the recipient of the 2011 American Medical Informatics Association New Investigator Award that recognizes early informatics contributions and significant scholarly contributions on the basis of scientific merit and research excellence.

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