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Code sets for respiratory symptoms in electronic health records research: a systematic review protocol

INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory conditions, which result in significant morbidity worldwide. These conditions are associated with a range of non-specific symptoms, which in themselves are a target for health research. Such research is incr...

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Autores principales: Jayatunga, Wikum, Stone, Philip, Aldridge, Robert W, Quint, Jennifer K, George, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6443061/
https://www.ncbi.nlm.nih.gov/pubmed/30833324
http://dx.doi.org/10.1136/bmjopen-2018-025965
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author Jayatunga, Wikum
Stone, Philip
Aldridge, Robert W
Quint, Jennifer K
George, Julie
author_facet Jayatunga, Wikum
Stone, Philip
Aldridge, Robert W
Quint, Jennifer K
George, Julie
author_sort Jayatunga, Wikum
collection PubMed
description INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory conditions, which result in significant morbidity worldwide. These conditions are associated with a range of non-specific symptoms, which in themselves are a target for health research. Such research is increasingly being conducted using electronic health records (EHRs), but computable phenotype definitions, in the form of code sets or code lists, are required to extract structured data from these large routine databases in a systematic and reproducible way. The aim of this protocol is to specify a systematic review to identify code sets for respiratory symptoms in EHRs research. METHODS AND ANALYSIS: MEDLINE and Embase databases will be searched using terms relating to EHRs, respiratory symptoms and use of code sets. The search will cover all English-language studies in these databases between January 1990 and December 2017. Two reviewers will independently screen identified studies for inclusion, and key data will be extracted into a uniform table, facilitating cross-comparison of codes used. Disagreements between the reviewers will be adjudicated by a third reviewer. This protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. ETHICS AND DISSEMINATION: As a review of previously published studies, no ethical approval is required. The results of this review will be submitted to a peer-reviewed journal for publication and can be used in future research into respiratory symptoms that uses electronic healthcare databases. PROSPERO REGISTRATION NUMBER: CRD42018100830.
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spelling pubmed-64430612019-04-17 Code sets for respiratory symptoms in electronic health records research: a systematic review protocol Jayatunga, Wikum Stone, Philip Aldridge, Robert W Quint, Jennifer K George, Julie BMJ Open Health Informatics INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory conditions, which result in significant morbidity worldwide. These conditions are associated with a range of non-specific symptoms, which in themselves are a target for health research. Such research is increasingly being conducted using electronic health records (EHRs), but computable phenotype definitions, in the form of code sets or code lists, are required to extract structured data from these large routine databases in a systematic and reproducible way. The aim of this protocol is to specify a systematic review to identify code sets for respiratory symptoms in EHRs research. METHODS AND ANALYSIS: MEDLINE and Embase databases will be searched using terms relating to EHRs, respiratory symptoms and use of code sets. The search will cover all English-language studies in these databases between January 1990 and December 2017. Two reviewers will independently screen identified studies for inclusion, and key data will be extracted into a uniform table, facilitating cross-comparison of codes used. Disagreements between the reviewers will be adjudicated by a third reviewer. This protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. ETHICS AND DISSEMINATION: As a review of previously published studies, no ethical approval is required. The results of this review will be submitted to a peer-reviewed journal for publication and can be used in future research into respiratory symptoms that uses electronic healthcare databases. PROSPERO REGISTRATION NUMBER: CRD42018100830. BMJ Publishing Group 2019-03-03 /pmc/articles/PMC6443061/ /pubmed/30833324 http://dx.doi.org/10.1136/bmjopen-2018-025965 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Health Informatics
Jayatunga, Wikum
Stone, Philip
Aldridge, Robert W
Quint, Jennifer K
George, Julie
Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title_full Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title_fullStr Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title_full_unstemmed Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title_short Code sets for respiratory symptoms in electronic health records research: a systematic review protocol
title_sort code sets for respiratory symptoms in electronic health records research: a systematic review protocol
topic Health Informatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6443061/
https://www.ncbi.nlm.nih.gov/pubmed/30833324
http://dx.doi.org/10.1136/bmjopen-2018-025965
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