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How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments
BACKGROUND: Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893236/ https://www.ncbi.nlm.nih.gov/pubmed/27260476 http://dx.doi.org/10.1186/s12911-016-0305-4 |
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author | Skyttberg, Niclas Vicente, Joana Chen, Rong Blomqvist, Hans Koch, Sabine |
author_facet | Skyttberg, Niclas Vicente, Joana Chen, Rong Blomqvist, Hans Koch, Sabine |
author_sort | Skyttberg, Niclas |
collection | PubMed |
description | BACKGROUND: Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore, possible factors affecting vital sign data quality need to be understood. This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments. METHODS: Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data. RESULTS: Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control. CONCLUSIONS: Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-016-0305-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4893236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48932362016-06-05 How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments Skyttberg, Niclas Vicente, Joana Chen, Rong Blomqvist, Hans Koch, Sabine BMC Med Inform Decis Mak Research Article BACKGROUND: Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore, possible factors affecting vital sign data quality need to be understood. This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments. METHODS: Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data. RESULTS: Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control. CONCLUSIONS: Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-016-0305-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-04 /pmc/articles/PMC4893236/ /pubmed/27260476 http://dx.doi.org/10.1186/s12911-016-0305-4 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Skyttberg, Niclas Vicente, Joana Chen, Rong Blomqvist, Hans Koch, Sabine How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title | How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title_full | How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title_fullStr | How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title_full_unstemmed | How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title_short | How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments |
title_sort | how to improve vital sign data quality for use in clinical decision support systems? a qualitative study in nine swedish emergency departments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893236/ https://www.ncbi.nlm.nih.gov/pubmed/27260476 http://dx.doi.org/10.1186/s12911-016-0305-4 |
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