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A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system

BACKGROUND: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a...

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Autores principales: Aalipour, Elham, Ghazisaeedi, Marjan, Sedighi Moghadam, Mohamad Reza, Shahmoradi, Leila, Mousavi, Batool, Beigy, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491823/
https://www.ncbi.nlm.nih.gov/pubmed/32984162
http://dx.doi.org/10.4103/jfmpc.jfmpc_261_20
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author Aalipour, Elham
Ghazisaeedi, Marjan
Sedighi Moghadam, Mohamad Reza
Shahmoradi, Leila
Mousavi, Batool
Beigy, Hamid
author_facet Aalipour, Elham
Ghazisaeedi, Marjan
Sedighi Moghadam, Mohamad Reza
Shahmoradi, Leila
Mousavi, Batool
Beigy, Hamid
author_sort Aalipour, Elham
collection PubMed
description BACKGROUND: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a recommender system, preparation of data source of this system should be considered. The aim of this study was to determine the minimum data set for user profile or user's electronic health record in chemical warfare victims’ recommender system. METHODS: This applied descriptive, cross-sectional study which was conducted in 2017. A questionnaire was developed by the authors from the data elements that were collected using the data extraction form from the studied sources. Content validity of the questionnaire was confirmed by using the experts. Test–retest method was used to determine the reliability of the questionnaire. The reliability of the questionnaire with Cronbach's alpha coefficient was confirmed as 84%. The questionnaire were submitted for related experts based on Delphi method by email or in person. Data resulting from the Delphi technique with descriptive statistics methods in SPSS software were analyzed. RESULTS: Forty-seven nonclinical data elements and 181 clinical data elements were classified. CONCLUSION: Determining minimum data set of user profile or electronic health record in the recommender system for chemical warfare victims helps the health authorities to implement the recommender system which demonstrates chemical warfare victims’ needs.
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spelling pubmed-74918232020-09-24 A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system Aalipour, Elham Ghazisaeedi, Marjan Sedighi Moghadam, Mohamad Reza Shahmoradi, Leila Mousavi, Batool Beigy, Hamid J Family Med Prim Care Original Article BACKGROUND: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a recommender system, preparation of data source of this system should be considered. The aim of this study was to determine the minimum data set for user profile or user's electronic health record in chemical warfare victims’ recommender system. METHODS: This applied descriptive, cross-sectional study which was conducted in 2017. A questionnaire was developed by the authors from the data elements that were collected using the data extraction form from the studied sources. Content validity of the questionnaire was confirmed by using the experts. Test–retest method was used to determine the reliability of the questionnaire. The reliability of the questionnaire with Cronbach's alpha coefficient was confirmed as 84%. The questionnaire were submitted for related experts based on Delphi method by email or in person. Data resulting from the Delphi technique with descriptive statistics methods in SPSS software were analyzed. RESULTS: Forty-seven nonclinical data elements and 181 clinical data elements were classified. CONCLUSION: Determining minimum data set of user profile or electronic health record in the recommender system for chemical warfare victims helps the health authorities to implement the recommender system which demonstrates chemical warfare victims’ needs. Wolters Kluwer - Medknow 2020-06-30 /pmc/articles/PMC7491823/ /pubmed/32984162 http://dx.doi.org/10.4103/jfmpc.jfmpc_261_20 Text en Copyright: © 2020 Journal of Family Medicine and Primary Care http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Aalipour, Elham
Ghazisaeedi, Marjan
Sedighi Moghadam, Mohamad Reza
Shahmoradi, Leila
Mousavi, Batool
Beigy, Hamid
A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title_full A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title_fullStr A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title_full_unstemmed A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title_short A minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
title_sort minimum data set of user profile or electronic health record for chemical warfare victims’ recommender system
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491823/
https://www.ncbi.nlm.nih.gov/pubmed/32984162
http://dx.doi.org/10.4103/jfmpc.jfmpc_261_20
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