Abstract
Abstract
Background
Unstructured data from electronic health records represent a wealth of information. Doc’EDS is a pre-screening tool based on textual and semantic analysis. The Doc’EDS system provides a graphic user interface to search documents in French. The aim of this study was to present the Doc’EDS tool and to provide a formal evaluation of its semantic features.
Methods
Doc’EDS is a search tool built on top of the clinical data warehouse developed at Rouen University Hospital. This tool is a multilevel search engine combining structured and unstructured data. It also provides basic analytical features and semantic utilities. A formal evaluation was conducted to measure the impact of Natural Language Processing algorithms.
Results
Approximately 18.1 million narrative documents are stored in Doc’EDS. The formal evaluation was conducted in 5000 clinical concepts that were manually collected. The F-measures of negative concepts and hypothetical concepts were respectively 0.89 and 0.57.
Conclusion
In this formal evaluation, we have shown that Doc’EDS is able to deal with language subtleties to enhance an advanced full text search in French health documents. The Doc’EDS tool is currently used on a daily basis to help researchers to identify patient cohorts thanks to unstructured data.
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Health Policy,Computer Science Applications
Reference26 articles.
1. Raghavan P, Chen JL, Fosler-Lussier E, Lai AM. How essential are unstructured clinical narratives and information fusion to clinical trial recruitment? 6.
2. Meystre SM, Heider PM, Kim Y, Aruch DB, Britten CD. Automatic trial eligibility surveillance based on unstructured clinical data. Int J Med Inform. 2019;129:13–9.
3. Garcelon N, Neuraz A, Benoit V, Salomon R, Burgun A. Improving a full-text search engine: the importance of negation detection and family history context to identify cases in a biomedical data warehouse. J Am Med Inform Assoc. 2016;144.
4. Rosenbloom ST, Denny JC, Xu H, Lorenzi N, Stead WW, Johnson KB. Data from clinical notes: a perspective on the tension between structure and flexible documentation. J Am Med Inform Assoc. 2011;18(2):181–6.
5. Karami M, Rahimi A, Shahmirzadi AH. Clinical data warehouse: an effective tool to create intelligence in disease management. Health Prog. 2017;36(4):380–4.
Cited by
11 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献