Title
An analysis of clinical queries in an electronic health record search utility.
Abstract
While search engines have become nearly ubiquitous on the Web, electronic health records (EHRs) generally lack search functionality; furthermore, there is no knowledge on how and what healthcare providers search while using an EHR-based search utility. In this study, we sought to understand user needs as captured by their search queries.This post-implementation study analyzed user search log files for 6 months from an EHR-based, free-text search utility at our large academic institution. The search logs were de-identified and then analyzed in two steps. First, two investigators classified all the unique queries as navigational, transactional, or informational searches. Second, three physician reviewers categorized a random sample of 357 informational searches into high-level semantic types derived from the Unified Medical Language System (UMLS). The reviewers were given overlapping data sets, such that two physicians reviewed each query.We analyzed 2207 queries performed by 436 unique users over a 6-month period. Of the 2207 queries, 980 were unique queries. Users of the search utility included clinicians, researchers and administrative staff. Across the whole user population, approximately 14.5% of the user searches were navigational searches and 85.1% were informational. Within informational searches, we found that users predominantly searched for laboratory results and specific diseases.A variety of user types, ranging from clinicians to administrative staff, took advantage of the EHR-based search utility. Though these users' search behavior differed, they predominantly performed informational searches related to laboratory results and specific diseases. Additionally, a number of queries were part of words, implying the need for a free-text module to be included in any future concept-based search algorithm.
Year
DOI
Venue
2010
10.1016/j.ijmedinf.2010.03.004
International Journal of Medical Informatics
Keywords
Field
DocType
Information storage and retrieval,Medical informatics,Medical informatics applications,Medical record systems,Computerized
Health care,Population,Data mining,World Wide Web,Search algorithm,Search engine,Semantic search,Information retrieval,Computer science,Medical record,Health informatics,Unified Medical Language System
Journal
Volume
Issue
ISSN
79
7
1386-5056
Citations 
PageRank 
References 
25
1.19
27
Authors
4
Name
Order
Citations
PageRank
Karthik Natarajan140731.52
Daniel Stein2251.19
Samat Jain3251.19
Noémie Elhadad428920.78