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J Am Med Inform Assoc 18:282-291 doi:10.1136/amiajnl-2011-000009
  • Research and applications

Collaborative search in electronic health records

  1. David A Hanauer4,5
  1. 1School of Public Health Department of Health Management and Policy, The University of Michigan, Ann Arbor, Michigan, USA
  2. 2School of Information, The University of Michigan, Ann Arbor, Michigan, USA
  3. 3Department of Electronic Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan, USA
  4. 4Department of Pediatrics, The University of Michigan, Ann Arbor, Michigan, USA
  5. 5Comprehensive Cancer Center, The University of Michigan, Ann Arbor, Michigan, USA
  1. Correspondence to Dr Kai Zheng, Information Systems and Health Informatics, School of Public Health Department of Health Management and Policy, School of Information, The University of Michigan, M3531 SPH II, 109 South Observatory Street, Ann Arbor, MI 48109-2029, USA; kzheng{at}umich.edu
  • Received 25 August 2010
  • Accepted 27 January 2011

Abstract

Objective 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, the authors 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.

Design The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted 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.

Results The users embraced the 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.

Conclusion Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.

Footnotes

  • Funding This project was supported by Grant HHSN276201000032C received from the National Library of Medicine, and in part by Grant UL1RR024986 received from the National Center for Research Resources, a component of the National Institutes of Health, and National Institutes of Health Roadmap for Medical Research.

  • Competing interests DAH is the inventor of intellectual property (the Electronic Medical Record Search Engine system) discussed in this manuscript, which is currently licensed to the Universal Medical Record Search Engine, and DAH is entitled to royalties related to this intellectual property. He is also a consultant to the Universal Medical Record Search Engine.

  • Ethics approval Ethics approval was provided by the Medical School Institutional Review Board, University of Michigan.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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