Journal
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Volume 13, Issue 1, Pages 80-90Publisher
OXFORD UNIV PRESS
DOI: 10.1197/jamia.M1820
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Funding
- NATIONAL LIBRARY OF MEDICINE [R01LM007222] Funding Source: NIH RePORTER
- NLM NIH HHS [R01 LM07222] Funding Source: Medline
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Objective: Health information retrieval (FUR) on the Internet has become an important practice for millions of people, many of whom have problems forming effective queries. We have developed and evaluated a tool to assist people in health-related query formation. Design: We developed the Health Information Query Assistant (HIQuA) system. The system suggests alternative/additional query terms related to the user's initial query that can be used as building blocks to construct a better, more specific query. The recommended terms are selected according to their semantic distance from the original query, which is calculated on the basis of concept co-occurrences in medical literature and log data as well as semantic relations in medical vocabularies. Measurements: An evaluation of the HIQuA system was conducted and a total of 213 subjects participated in the study. The subjects were randomized into 2 groups. One group Was given query recommendations and the other was not. Each subject performed HIR for both a predefined and a self-defined task. Results: The study showed that providing HIQuA recommendations resulted in statistically significantly higher rates of successful queries (odds ratio = 1.66, 95% confidence interval = 1.16 - 2.38), although no statistically significant impact on user satisfaction or the users' ability to accomplish the predefined retrieval task was found. Conclusion: Providing semantic-distance-based query recommendations can help consumers with query formation during HIR.
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