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Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care

BACKGROUND: A patient’s trajectory through the healthcare system affects resource use and outcomes. Data fields in population-based administrative health databases are potentially valuable resources for constructing care trajectories for entire populations, provided they can capture patient transiti...

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Autores principales: Kuwornu, John Paul, Lix, Lisa M., Quail, Jacqueline M., Wang, Xiaoyun Eric, Osman, Meric, Teare, Gary F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057464/
https://www.ncbi.nlm.nih.gov/pubmed/27724877
http://dx.doi.org/10.1186/s12913-016-1775-x
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author Kuwornu, John Paul
Lix, Lisa M.
Quail, Jacqueline M.
Wang, Xiaoyun Eric
Osman, Meric
Teare, Gary F.
author_facet Kuwornu, John Paul
Lix, Lisa M.
Quail, Jacqueline M.
Wang, Xiaoyun Eric
Osman, Meric
Teare, Gary F.
author_sort Kuwornu, John Paul
collection PubMed
description BACKGROUND: A patient’s trajectory through the healthcare system affects resource use and outcomes. Data fields in population-based administrative health databases are potentially valuable resources for constructing care trajectories for entire populations, provided they can capture patient transitions between healthcare services. This study describes patient transitions from the emergency department (ED) to other healthcare settings, and ascertains whether the discharge disposition field recorded in the ED data was a reliable source of patient transition information from the emergency to the acute care settings. METHODS: Administrative health databases from the province of Saskatchewan, Canada (population 1.1 million) were used to identify patients with at least one ED visit to provincial teaching hospitals (n = 5) between April 1, 2006 and March 31, 2012. Discharge disposition from ED was described using frequencies and percentages; and it includes categories such as home, transfer to other facilities, and died. The kappa statistic with 95 % confidence intervals (95 % CIs) was used to measure agreement between the discharge disposition field in the ED data and hospital admission records. RESULTS: We identified N = 1,062,861 visits for 371,480 patients to EDs over the six-year study period. Three-quarters of the discharges were to home, 16.1 % were to acute care in the same facility in which the ED was located, and 1.6 % resulted in a patient transfer to a different acute care facility. Agreement between the discharge disposition field in the ED data and hospital admission records was good when the emergency and acute care departments were in the same facility (κ = 0.77, 95 % CI 0.77, 0.77). For transfers to a different acute care facility, agreement was only fair (κ = 0.36, 95 % CI 0.35, 0.36). CONCLUSIONS: The majority of patients who attended EDs did not transition to another healthcare setting. For those who transitioned to acute care, accuracy of the discharge disposition field depended on whether the two services were provided in the same facility. Using the hospital data as reference, we conclude that the discharge disposition field in the ED data is not reliable for measuring transitions from ED to acute care.
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spelling pubmed-50574642016-10-24 Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care Kuwornu, John Paul Lix, Lisa M. Quail, Jacqueline M. Wang, Xiaoyun Eric Osman, Meric Teare, Gary F. BMC Health Serv Res Research Article BACKGROUND: A patient’s trajectory through the healthcare system affects resource use and outcomes. Data fields in population-based administrative health databases are potentially valuable resources for constructing care trajectories for entire populations, provided they can capture patient transitions between healthcare services. This study describes patient transitions from the emergency department (ED) to other healthcare settings, and ascertains whether the discharge disposition field recorded in the ED data was a reliable source of patient transition information from the emergency to the acute care settings. METHODS: Administrative health databases from the province of Saskatchewan, Canada (population 1.1 million) were used to identify patients with at least one ED visit to provincial teaching hospitals (n = 5) between April 1, 2006 and March 31, 2012. Discharge disposition from ED was described using frequencies and percentages; and it includes categories such as home, transfer to other facilities, and died. The kappa statistic with 95 % confidence intervals (95 % CIs) was used to measure agreement between the discharge disposition field in the ED data and hospital admission records. RESULTS: We identified N = 1,062,861 visits for 371,480 patients to EDs over the six-year study period. Three-quarters of the discharges were to home, 16.1 % were to acute care in the same facility in which the ED was located, and 1.6 % resulted in a patient transfer to a different acute care facility. Agreement between the discharge disposition field in the ED data and hospital admission records was good when the emergency and acute care departments were in the same facility (κ = 0.77, 95 % CI 0.77, 0.77). For transfers to a different acute care facility, agreement was only fair (κ = 0.36, 95 % CI 0.35, 0.36). CONCLUSIONS: The majority of patients who attended EDs did not transition to another healthcare setting. For those who transitioned to acute care, accuracy of the discharge disposition field depended on whether the two services were provided in the same facility. Using the hospital data as reference, we conclude that the discharge disposition field in the ED data is not reliable for measuring transitions from ED to acute care. BioMed Central 2016-10-11 /pmc/articles/PMC5057464/ /pubmed/27724877 http://dx.doi.org/10.1186/s12913-016-1775-x 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
Kuwornu, John Paul
Lix, Lisa M.
Quail, Jacqueline M.
Wang, Xiaoyun Eric
Osman, Meric
Teare, Gary F.
Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title_full Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title_fullStr Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title_full_unstemmed Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title_short Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
title_sort measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057464/
https://www.ncbi.nlm.nih.gov/pubmed/27724877
http://dx.doi.org/10.1186/s12913-016-1775-x
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