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Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients

BACKGROUND: The extent of outpatient adverse drug events (ADEs) remains unclear. Trigger tools are used as a screening method to identify care episodes that may be ADEs, but their value in a population with high chronic-illness burden remains unclear. METHODS: The authors used six abnormal laborator...

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Autores principales: Brenner, Stacey, Detz, Alissa, López, Andrea, Horton, Claire, Sarkar, Urmimala
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402751/
https://www.ncbi.nlm.nih.gov/pubmed/22626736
http://dx.doi.org/10.1136/bmjqs-2011-000643
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author Brenner, Stacey
Detz, Alissa
López, Andrea
Horton, Claire
Sarkar, Urmimala
author_facet Brenner, Stacey
Detz, Alissa
López, Andrea
Horton, Claire
Sarkar, Urmimala
author_sort Brenner, Stacey
collection PubMed
description BACKGROUND: The extent of outpatient adverse drug events (ADEs) remains unclear. Trigger tools are used as a screening method to identify care episodes that may be ADEs, but their value in a population with high chronic-illness burden remains unclear. METHODS: The authors used six abnormal laboratory triggers for detecting ADEs among adults in outpatient care. Eligible patients were included if they were >18 years, sought primary or urgent care between November 2008 and November 2009 and were prescribed at least one medication. The authors then used the clinical / administrative database to identity patients with these triggers. Two physicians conducted in-depth chart review of any medical records with identified triggers. RESULTS: The authors reviewed 1342 triggers representing 622 unique episodes among 516 patients. The trigger tool identified 91 (15%) ADEs. Of the 91 ADEs included in the analysis, 49 (54%) occurred during medication monitoring, 41 (45%) during patient self-administration, and one could not be determined. 96% of abnormal international normalised ratio triggers were ADEs, followed by 12% of abnormal blood urea nitrogen triggers, 9% of abnormal alanine aminotransferase triggers, 8% of abnormal serum creatinine triggers and 3% of aspartate aminotransferase triggers. CONCLUSIONS: The findings imply that other tools such as text triggers or more complex automated screening rules, which combine data hierarchically are needed to effectively screen for ADEs in chronically ill adults seen in primary care.
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spelling pubmed-34027512012-07-25 Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients Brenner, Stacey Detz, Alissa López, Andrea Horton, Claire Sarkar, Urmimala BMJ Qual Saf Original Research BACKGROUND: The extent of outpatient adverse drug events (ADEs) remains unclear. Trigger tools are used as a screening method to identify care episodes that may be ADEs, but their value in a population with high chronic-illness burden remains unclear. METHODS: The authors used six abnormal laboratory triggers for detecting ADEs among adults in outpatient care. Eligible patients were included if they were >18 years, sought primary or urgent care between November 2008 and November 2009 and were prescribed at least one medication. The authors then used the clinical / administrative database to identity patients with these triggers. Two physicians conducted in-depth chart review of any medical records with identified triggers. RESULTS: The authors reviewed 1342 triggers representing 622 unique episodes among 516 patients. The trigger tool identified 91 (15%) ADEs. Of the 91 ADEs included in the analysis, 49 (54%) occurred during medication monitoring, 41 (45%) during patient self-administration, and one could not be determined. 96% of abnormal international normalised ratio triggers were ADEs, followed by 12% of abnormal blood urea nitrogen triggers, 9% of abnormal alanine aminotransferase triggers, 8% of abnormal serum creatinine triggers and 3% of aspartate aminotransferase triggers. CONCLUSIONS: The findings imply that other tools such as text triggers or more complex automated screening rules, which combine data hierarchically are needed to effectively screen for ADEs in chronically ill adults seen in primary care. BMJ Group 2012-05-23 2012-08 /pmc/articles/PMC3402751/ /pubmed/22626736 http://dx.doi.org/10.1136/bmjqs-2011-000643 Text en © 2012, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
spellingShingle Original Research
Brenner, Stacey
Detz, Alissa
López, Andrea
Horton, Claire
Sarkar, Urmimala
Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title_full Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title_fullStr Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title_full_unstemmed Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title_short Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
title_sort signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402751/
https://www.ncbi.nlm.nih.gov/pubmed/22626736
http://dx.doi.org/10.1136/bmjqs-2011-000643
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