Abstract
The Centers for Medicare & Medicaid Services Incentive Programs promote meaningful use of electronic health records (EHRs), which, among many benefits, allow patients to receive electronic copies of their EHRs and thereby empower them to take a more active role in their health. In the United States, however, 17% population is Hispanic, of which 50% has limited English language skills. To help this population take advantage of their EHRs, we are developing English-Spanish machine translation (MT) systems for EHRs. In this study, we first built an English-Spanish parallel corpus and trained NoteAidSpanish, a statistical MT (SMT) system. Google Translator and Microsoft Bing Translator are two baseline MT systems. In addition, we evaluated hybrid MT systems that first replace medical jargon in EHR notes with lay terms and then translate the notes with SMT systems. Evaluation on a small set of EHR notes, our results show that Google Translator outperformed NoteAidSpanish. The hybrid SMT systems first map medical jargon to lay language. This step improved the translation. A fully implemented hybrid MT system is available at http://www.clinicalnotesaid.org. The English-Spanish parallel-aligned MedlinePlus corpus is available upon request.
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CITATION STYLE
Liu, W., Cai, S., Ramesh, B. P., Chiriboga, G., Knight, K., & Yu, H. (2015). Translating Electronic Health Record Notes from English to Spanish: A Preliminary Study. In ACL-IJCNLP 2015 - BioNLP 2015: Workshop on Biomedical Natural Language Processing, Proceedings of the Workshop (pp. 134–140). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3816
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