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HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records
OBJECTIVES: One of the most important functions for a medical practitioner while treating a patient is to study the patient's complete medical history by going through all records, from test results to doctor's notes. With the increasing use of technology in medicine, these records are mos...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Medical Informatics
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944189/ https://www.ncbi.nlm.nih.gov/pubmed/29770248 http://dx.doi.org/10.4258/hir.2018.24.2.148 |
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author | Aggarwal, Anshul Garhwal, Sunita Kumar, Ajay |
author_facet | Aggarwal, Anshul Garhwal, Sunita Kumar, Ajay |
author_sort | Aggarwal, Anshul |
collection | PubMed |
description | OBJECTIVES: One of the most important functions for a medical practitioner while treating a patient is to study the patient's complete medical history by going through all records, from test results to doctor's notes. With the increasing use of technology in medicine, these records are mostly digital, alleviating the problem of looking through a stack of papers, which are easily misplaced, but some of these are in an unstructured form. Large parts of clinical reports are in written text form and are tedious to use directly without appropriate pre-processing. In medical research, such health records may be a good, convenient source of medical data; however, lack of structure means that the data is unfit for statistical evaluation. In this paper, we introduce a system to extract, store, retrieve, and analyse information from health records, with a focus on the Indian healthcare scene. METHODS: A Python-based tool, Healthcare Data Extraction and Analysis (HEDEA), has been designed to extract structured information from various medical records using a regular expression-based approach. RESULTS: The HEDEA system is working, covering a large set of formats, to extract and analyse health information. CONCLUSIONS: This tool can be used to generate analysis report and charts using the central database. This information is only provided after prior approval has been received from the patient for medical research purposes. |
format | Online Article Text |
id | pubmed-5944189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-59441892018-05-16 HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records Aggarwal, Anshul Garhwal, Sunita Kumar, Ajay Healthc Inform Res Case Report OBJECTIVES: One of the most important functions for a medical practitioner while treating a patient is to study the patient's complete medical history by going through all records, from test results to doctor's notes. With the increasing use of technology in medicine, these records are mostly digital, alleviating the problem of looking through a stack of papers, which are easily misplaced, but some of these are in an unstructured form. Large parts of clinical reports are in written text form and are tedious to use directly without appropriate pre-processing. In medical research, such health records may be a good, convenient source of medical data; however, lack of structure means that the data is unfit for statistical evaluation. In this paper, we introduce a system to extract, store, retrieve, and analyse information from health records, with a focus on the Indian healthcare scene. METHODS: A Python-based tool, Healthcare Data Extraction and Analysis (HEDEA), has been designed to extract structured information from various medical records using a regular expression-based approach. RESULTS: The HEDEA system is working, covering a large set of formats, to extract and analyse health information. CONCLUSIONS: This tool can be used to generate analysis report and charts using the central database. This information is only provided after prior approval has been received from the patient for medical research purposes. Korean Society of Medical Informatics 2018-04 2018-04-30 /pmc/articles/PMC5944189/ /pubmed/29770248 http://dx.doi.org/10.4258/hir.2018.24.2.148 Text en © 2018 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Case Report Aggarwal, Anshul Garhwal, Sunita Kumar, Ajay HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title | HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title_full | HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title_fullStr | HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title_full_unstemmed | HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title_short | HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records |
title_sort | hedea: a python tool for extracting and analysing semi-structured information from medical records |
topic | Case Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944189/ https://www.ncbi.nlm.nih.gov/pubmed/29770248 http://dx.doi.org/10.4258/hir.2018.24.2.148 |
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