Language, Structure, and Reuse in the Electronic Health Record
1Senior research fellow at the University of Sheffield, Sheffield, United Kingdom.
AMA Journal of Ethics
|March 22, 2017
Summary
Electronic health records (EHRs) contain significant free-text medical language, posing challenges for computational analysis. This study explores the interaction between qualitative medical language and structured computation within EHRs to improve information reuse.
Area of Science:
- Medical Informatics
- Computational Linguistics
- Health Information Technology
Background:
- The electronic health record (EHR) relies heavily on natural language, with up to 70% of information in free-text fields.
- Transitioning from paper to EHRs enables automated search and analysis of clinical information.
- Natural language presents inherent challenges for computational processing due to its nuanced and qualitative nature.
Purpose of the Study:
- To examine the inherent tension between the qualitative nature of medical language and the structured demands of computation.
- To analyze the interaction between medical language and computational methods within the EHR environment.
- To explore the potential of computational natural language processing to bridge this gap and enhance EHR data utility.
Main Methods:
- Review and analysis of the characteristics of medical language in the context of EHRs.
- Examination of computational approaches applied to natural language processing in healthcare.
- Discussion of the interplay between qualitative linguistic data and structured computational frameworks.
Main Results:
- Significant portion of EHR data exists as unstructured, natural language text.
- Computational methods face challenges in accurately interpreting the nuances of medical language.
- The EHR serves as the medium where these linguistic and computational challenges manifest.
Conclusions:
- Understanding the tension between medical language and computation is crucial for effective EHR utilization.
- Computational analysis of natural language holds promise for overcoming current limitations.
- Further development in natural language processing can unlock the full potential of clinical information within EHRs.
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