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A multi-lingual web service for drug side-effect data.
Steven D Bedrick1, Alejandro Mauro
1Oregon Health & Science University, Portland, OR, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|March 31, 2010
Summary
This study developed a system for drug side-effect data integration into service-oriented architectures. Machine translation quality for medical use varied, suggesting it
Area of Science:
- Health Informatics
- Computational Linguistics
- Drug Safety
Background:
- Service-oriented architectures (SOAs) require accessible drug information.
- Existing drug side-effect data systems lack integration capabilities.
- Web 2.0 technologies offer potential for data aggregation.
Purpose of the Study:
- To describe a novel system for drug side-effect data.
- To evaluate the integration of this system into various front-ends.
- To assess the adequacy of machine translation for consumer medical applications.
Main Methods:
- Developed a Web 2.0-based system for collecting drug side-effect data.
- Integrated the system with SMS, instant messenger, and iPhone interfaces.
- Utilized Google's translation API for Spanish language output.
- Conducted a review by Argentinean clinicians to rate translation quality.
Main Results:
- The system successfully aggregated drug side-effect data from public sources.
- Multiple front-end interfaces (SMS, IM, iPhone) demonstrated system versatility.
- Clinician ratings indicated variable quality of machine-translated Spanish drug side-effect information.
- Google's translation API showed inconsistencies across different drugs.
Conclusions:
- The developed system provides a versatile component for SOAs.
- Freely-available machine translation is insufficient as a standalone solution for consumer medical applications.
- Machine translation can serve as a preliminary step for medical information dissemination.
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