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Establishing a sorting protocol for healthcare databases
Background: Health information records in many countries, especially developing countries, are still paper based. Compared to electronic systems, paper-based systems are disadvantageous in terms of data storage and data extraction. Given the importance of health records for epidemiological studies,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PAGEPress Publications, Pavia, Italy
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056323/ https://www.ncbi.nlm.nih.gov/pubmed/33849252 http://dx.doi.org/10.4081/jphr.2021.1722 |
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author | Ghabi, Elie Farah, Wehbeh Abboud, Maher Chalhoub, Elias Ziade, Nelly Annesi-Maesano, Isabella Abi Habib, Laurie Nakhle, Myriam Mrad |
author_facet | Ghabi, Elie Farah, Wehbeh Abboud, Maher Chalhoub, Elias Ziade, Nelly Annesi-Maesano, Isabella Abi Habib, Laurie Nakhle, Myriam Mrad |
author_sort | Ghabi, Elie |
collection | PubMed |
description | Background: Health information records in many countries, especially developing countries, are still paper based. Compared to electronic systems, paper-based systems are disadvantageous in terms of data storage and data extraction. Given the importance of health records for epidemiological studies, guidelines for effective data cleaning and sorting are essential. They are, however, largely absent from the literature. The following paper discusses the process by which an algorithm was developed for the cleaning and sorting of a database generated from emergency department records in Lebanon. Design and methods: Demographic and health related information were extracted from the emergency department records of three hospitals in Beirut. Appropriate categories were selected for data categorization. For health information, disease categories and codes were selected according to the International Classification of Disease 10(th) Edition. Results: A total of 16,537 entries were collected. Demographic information was categorized into groups for future epidemiological studies. Analysis of the health information led to the creation of a sorting algorithm which was then used to categorize and code the health data. Several counts were then performed to represent and visualize the data numerically and graphically. Conclusions: The article describes the current state of health information records in Lebanon and the associated disadvantages of a paper-based system in terms of storage and data extraction. Furthermore, the article describes the algorithm by which health information was sorted and categorized to allow for future data analysis using paper records. |
format | Online Article Text |
id | pubmed-8056323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PAGEPress Publications, Pavia, Italy |
record_format | MEDLINE/PubMed |
spelling | pubmed-80563232021-04-26 Establishing a sorting protocol for healthcare databases Ghabi, Elie Farah, Wehbeh Abboud, Maher Chalhoub, Elias Ziade, Nelly Annesi-Maesano, Isabella Abi Habib, Laurie Nakhle, Myriam Mrad J Public Health Res Article Background: Health information records in many countries, especially developing countries, are still paper based. Compared to electronic systems, paper-based systems are disadvantageous in terms of data storage and data extraction. Given the importance of health records for epidemiological studies, guidelines for effective data cleaning and sorting are essential. They are, however, largely absent from the literature. The following paper discusses the process by which an algorithm was developed for the cleaning and sorting of a database generated from emergency department records in Lebanon. Design and methods: Demographic and health related information were extracted from the emergency department records of three hospitals in Beirut. Appropriate categories were selected for data categorization. For health information, disease categories and codes were selected according to the International Classification of Disease 10(th) Edition. Results: A total of 16,537 entries were collected. Demographic information was categorized into groups for future epidemiological studies. Analysis of the health information led to the creation of a sorting algorithm which was then used to categorize and code the health data. Several counts were then performed to represent and visualize the data numerically and graphically. Conclusions: The article describes the current state of health information records in Lebanon and the associated disadvantages of a paper-based system in terms of storage and data extraction. Furthermore, the article describes the algorithm by which health information was sorted and categorized to allow for future data analysis using paper records. PAGEPress Publications, Pavia, Italy 2021-03-23 /pmc/articles/PMC8056323/ /pubmed/33849252 http://dx.doi.org/10.4081/jphr.2021.1722 Text en ©Copyright: the Author(s) https://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 | Article Ghabi, Elie Farah, Wehbeh Abboud, Maher Chalhoub, Elias Ziade, Nelly Annesi-Maesano, Isabella Abi Habib, Laurie Nakhle, Myriam Mrad Establishing a sorting protocol for healthcare databases |
title | Establishing a sorting protocol for healthcare databases |
title_full | Establishing a sorting protocol for healthcare databases |
title_fullStr | Establishing a sorting protocol for healthcare databases |
title_full_unstemmed | Establishing a sorting protocol for healthcare databases |
title_short | Establishing a sorting protocol for healthcare databases |
title_sort | establishing a sorting protocol for healthcare databases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056323/ https://www.ncbi.nlm.nih.gov/pubmed/33849252 http://dx.doi.org/10.4081/jphr.2021.1722 |
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