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The Danish helicopter emergency medical service database: high quality data with great potential
BACKGROUND: The Danish Helicopter Emergency Medical Service (HEMS) is part of the Danish pre-hospital response offering advanced patient care on scene and during rapid transport to definitive care. Monitoring HEMS performance and the quality of critical care has high national as well as internationa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451291/ https://www.ncbi.nlm.nih.gov/pubmed/30953564 http://dx.doi.org/10.1186/s13049-019-0615-5 |
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author | Alstrup, Karen Petersen, Jens Aage Kølsen Barfod, Charlotte Knudsen, Lars Rognås, Leif Møller, Thea Palsgaard |
author_facet | Alstrup, Karen Petersen, Jens Aage Kølsen Barfod, Charlotte Knudsen, Lars Rognås, Leif Møller, Thea Palsgaard |
author_sort | Alstrup, Karen |
collection | PubMed |
description | BACKGROUND: The Danish Helicopter Emergency Medical Service (HEMS) is part of the Danish pre-hospital response offering advanced patient care on scene and during rapid transport to definitive care. Monitoring HEMS performance and the quality of critical care has high national as well as international priority underlining the need for research in this field. The data quality of the Danish HEMS database is unknown. Furthermore, a set of quality indicators (QI) developed by an international collaboration group (EQUIPE) potentially for use in physician-staffed EMS, has recently been presented. The aim of the current study was to present the design and data quality of the Danish helicopter database, and to evaluate the coverage of available variables in the database according to the QIs proposed. METHOD: The study included all helicopter dispatches between October 1st 2014 and April 30th 2018. The database layout and data entering procedure, as well as the key variables and data completeness were described. Furthermore, missing data and misclassifications were addressed. Lastly, the 26 QIs proposed by the EQUIPE-collaboration were evaluated for coverage in the HEMS database. RESULTS: A total of 13,392 missions were included in the study. The database includes a broad spectrum of mission- and patient-specific data related to the pre-hospital pathway of acutely ill or injured patients in a national coverage. Missing data for the majority of variables is less than 6.5%. The percentage of completed report forms has increased over time and reached 99.9% in 2018. Misclassification were observed for 294 patients in the study period corresponding to 3,7%. Less than half of the QIs proposed by the EQUIPE-collaboration group were directly available from the database. CONCLUSIONS: Helicopter Emergency Medical Services in Denmark are a new and sparsely investigated health care provider. The database contains nearly all missions dispatched by the five regional Emergency Medical Dispatch Centres. Generally, the data quality is considered high with great potential for future research. Potential quality indicators as proposed by the EQUIPE-collaboration group could inspire the configuration and design of the next version of Hemsfile creating an even more solid basis for research and quality improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13049-019-0615-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6451291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64512912019-04-17 The Danish helicopter emergency medical service database: high quality data with great potential Alstrup, Karen Petersen, Jens Aage Kølsen Barfod, Charlotte Knudsen, Lars Rognås, Leif Møller, Thea Palsgaard Scand J Trauma Resusc Emerg Med Original Research BACKGROUND: The Danish Helicopter Emergency Medical Service (HEMS) is part of the Danish pre-hospital response offering advanced patient care on scene and during rapid transport to definitive care. Monitoring HEMS performance and the quality of critical care has high national as well as international priority underlining the need for research in this field. The data quality of the Danish HEMS database is unknown. Furthermore, a set of quality indicators (QI) developed by an international collaboration group (EQUIPE) potentially for use in physician-staffed EMS, has recently been presented. The aim of the current study was to present the design and data quality of the Danish helicopter database, and to evaluate the coverage of available variables in the database according to the QIs proposed. METHOD: The study included all helicopter dispatches between October 1st 2014 and April 30th 2018. The database layout and data entering procedure, as well as the key variables and data completeness were described. Furthermore, missing data and misclassifications were addressed. Lastly, the 26 QIs proposed by the EQUIPE-collaboration were evaluated for coverage in the HEMS database. RESULTS: A total of 13,392 missions were included in the study. The database includes a broad spectrum of mission- and patient-specific data related to the pre-hospital pathway of acutely ill or injured patients in a national coverage. Missing data for the majority of variables is less than 6.5%. The percentage of completed report forms has increased over time and reached 99.9% in 2018. Misclassification were observed for 294 patients in the study period corresponding to 3,7%. Less than half of the QIs proposed by the EQUIPE-collaboration group were directly available from the database. CONCLUSIONS: Helicopter Emergency Medical Services in Denmark are a new and sparsely investigated health care provider. The database contains nearly all missions dispatched by the five regional Emergency Medical Dispatch Centres. Generally, the data quality is considered high with great potential for future research. Potential quality indicators as proposed by the EQUIPE-collaboration group could inspire the configuration and design of the next version of Hemsfile creating an even more solid basis for research and quality improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13049-019-0615-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-05 /pmc/articles/PMC6451291/ /pubmed/30953564 http://dx.doi.org/10.1186/s13049-019-0615-5 Text en © The Author(s). 2019 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 | Original Research Alstrup, Karen Petersen, Jens Aage Kølsen Barfod, Charlotte Knudsen, Lars Rognås, Leif Møller, Thea Palsgaard The Danish helicopter emergency medical service database: high quality data with great potential |
title | The Danish helicopter emergency medical service database: high quality data with great potential |
title_full | The Danish helicopter emergency medical service database: high quality data with great potential |
title_fullStr | The Danish helicopter emergency medical service database: high quality data with great potential |
title_full_unstemmed | The Danish helicopter emergency medical service database: high quality data with great potential |
title_short | The Danish helicopter emergency medical service database: high quality data with great potential |
title_sort | danish helicopter emergency medical service database: high quality data with great potential |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451291/ https://www.ncbi.nlm.nih.gov/pubmed/30953564 http://dx.doi.org/10.1186/s13049-019-0615-5 |
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