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Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes
OBJECTIVE: Linkage of electronic administrative datasets is becoming increasingly common, offering a powerful resource for research and analysis. However, routine linkage of prehospital data with emergency department (ED) presentation and hospital admission datasets is rare. We describe a methodolog...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763257/ https://www.ncbi.nlm.nih.gov/pubmed/35046714 http://dx.doi.org/10.2147/IJGM.S328149 |
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author | Andrew, Emily Cox, Shelley Smith, Karen |
author_facet | Andrew, Emily Cox, Shelley Smith, Karen |
author_sort | Andrew, Emily |
collection | PubMed |
description | OBJECTIVE: Linkage of electronic administrative datasets is becoming increasingly common, offering a powerful resource for research and analysis. However, routine linkage of prehospital data with emergency department (ED) presentation and hospital admission datasets is rare. We describe a methodology used to link ambulance data with hospital ED presentations, admissions, and death records, and examine potential biases between matched and unmatched patients. METHODS: Iterative deterministic linkage methodologies were employed to link clinical, operational, and secondary triage ambulance data to ED presentations, hospital admissions, and death records in Victoria, Australia. Descriptive analyses and standardised differences were used to examine potential biases between matched and unmatched patients. RESULTS: A total of 2,813,913 ambulance records were available for linkage. Of the patients that were transported to a public ED (n=1,753,268), 83.3% matched with an ED record. Only small differences were observed between matched and unmatched patients for sex, year, time of day and attending crew type. The data elements with the largest standardised differences were patient age (0.25) and paramedic diagnosis (0.25). Matched patients were older (mean ± standard deviation: 55.6±25.7 vs 49.0±26.0 years) and more likely to have a paramedic-suspected cardiac, respiratory, neurological, or gastrointestinal/genitourinary condition, suspected infection/sepsis, or pain. CONCLUSION: This linked dataset will facilitate a large body of research into prehospital care and patient outcomes. Although future analysis of matched patients should acknowledge the linkage error rate, our findings suggest that results are likely to be generalisable to the broader ambulance population. |
format | Online Article Text |
id | pubmed-8763257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-87632572022-01-18 Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes Andrew, Emily Cox, Shelley Smith, Karen Int J Gen Med Short Report OBJECTIVE: Linkage of electronic administrative datasets is becoming increasingly common, offering a powerful resource for research and analysis. However, routine linkage of prehospital data with emergency department (ED) presentation and hospital admission datasets is rare. We describe a methodology used to link ambulance data with hospital ED presentations, admissions, and death records, and examine potential biases between matched and unmatched patients. METHODS: Iterative deterministic linkage methodologies were employed to link clinical, operational, and secondary triage ambulance data to ED presentations, hospital admissions, and death records in Victoria, Australia. Descriptive analyses and standardised differences were used to examine potential biases between matched and unmatched patients. RESULTS: A total of 2,813,913 ambulance records were available for linkage. Of the patients that were transported to a public ED (n=1,753,268), 83.3% matched with an ED record. Only small differences were observed between matched and unmatched patients for sex, year, time of day and attending crew type. The data elements with the largest standardised differences were patient age (0.25) and paramedic diagnosis (0.25). Matched patients were older (mean ± standard deviation: 55.6±25.7 vs 49.0±26.0 years) and more likely to have a paramedic-suspected cardiac, respiratory, neurological, or gastrointestinal/genitourinary condition, suspected infection/sepsis, or pain. CONCLUSION: This linked dataset will facilitate a large body of research into prehospital care and patient outcomes. Although future analysis of matched patients should acknowledge the linkage error rate, our findings suggest that results are likely to be generalisable to the broader ambulance population. Dove 2022-01-13 /pmc/articles/PMC8763257/ /pubmed/35046714 http://dx.doi.org/10.2147/IJGM.S328149 Text en © 2022 Andrew et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Short Report Andrew, Emily Cox, Shelley Smith, Karen Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title | Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title_full | Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title_fullStr | Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title_full_unstemmed | Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title_short | Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes |
title_sort | linking ambulance records with hospital and death index data to evaluate patient outcomes |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763257/ https://www.ncbi.nlm.nih.gov/pubmed/35046714 http://dx.doi.org/10.2147/IJGM.S328149 |
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