4.6 Article

Collaborative search in electronic health records

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Publisher

OXFORD UNIV PRESS
DOI: 10.1136/amiajnl-2011-000009

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Funding

  1. National Library of Medicine [HHSN276201000032C]
  2. National Center for Research Resources, National Institutes of Health [UL1RR024986]
  3. National Center for Research Resources, National Institutes of Health Roadmap for Medical Research [UL1RR024986]

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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.

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