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Unintended consequences of reducing QT-alert overload in a computerized physician order entry system

PURPOSE: After complaints of too many low-specificity drug-drug interaction (DDI) alerts on QT prolongation, the rules for QT alerting in the Dutch national drug database were restricted in 2007 to obviously QT-prolonging drugs. The aim of this virtual study was to investigate whether this adjustmen...

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Autores principales: van der Sijs, Heleen, Kowlesar, Ravi, Aarts, Jos, Berg, Marc, Vulto, Arnold, van Gelder, Teun
Formato: Texto
Lenguaje:English
Publicado: Springer-Verlag 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2729977/
https://www.ncbi.nlm.nih.gov/pubmed/19415251
http://dx.doi.org/10.1007/s00228-009-0654-3
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author van der Sijs, Heleen
Kowlesar, Ravi
Aarts, Jos
Berg, Marc
Vulto, Arnold
van Gelder, Teun
author_facet van der Sijs, Heleen
Kowlesar, Ravi
Aarts, Jos
Berg, Marc
Vulto, Arnold
van Gelder, Teun
author_sort van der Sijs, Heleen
collection PubMed
description PURPOSE: After complaints of too many low-specificity drug-drug interaction (DDI) alerts on QT prolongation, the rules for QT alerting in the Dutch national drug database were restricted in 2007 to obviously QT-prolonging drugs. The aim of this virtual study was to investigate whether this adjustment would improve the identification of patients at risk of developing Torsades de Pointes (TdP) due to QT-prolonging drug combinations in a computerized physician order entry system (CPOE) and whether these new rules should be implemented. METHODS: During a half-year study period, inpatients with overridden DDI alerts regarding QT prolongation and with an electrocardiogram recorded before and within 1 month of the alert override were included if they did not have a ventricular pacemaker and did not use the low-risk combination cotrimoxazole and tacrolimus. QT-interval prolongation and the risk of developing TdP were calculated for all patients and related to the number of patients for whom a QT-alert would be generated in the new situation with the restricted database. RESULTS: Forty-nine patients (13%) met the inclusion criteria. In this study population, knowledge base-adjustment would reduce the number of alerts by 53%. However, the positive predictive value of QT alerts would not change (31% before and 30% after) and only 47% of the patients at risk of developing TdP would be identified in CPOEs using the adjusted knowledge base. CONCLUSION: The new rules for QT alerting would result in a poorer identification of patients at risk of developing TdP than the old rules. This is caused by the many non-drug-related risk factors for QT prolongation not being incorporated in CPOE alert generation. The partial contribution of all risk factors should be studied and used to create clinical rules for QT alerting with an acceptable positive predictive value.
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spelling pubmed-27299772009-08-24 Unintended consequences of reducing QT-alert overload in a computerized physician order entry system van der Sijs, Heleen Kowlesar, Ravi Aarts, Jos Berg, Marc Vulto, Arnold van Gelder, Teun Eur J Clin Pharmacol Pharmacoepidemiology and Prescription PURPOSE: After complaints of too many low-specificity drug-drug interaction (DDI) alerts on QT prolongation, the rules for QT alerting in the Dutch national drug database were restricted in 2007 to obviously QT-prolonging drugs. The aim of this virtual study was to investigate whether this adjustment would improve the identification of patients at risk of developing Torsades de Pointes (TdP) due to QT-prolonging drug combinations in a computerized physician order entry system (CPOE) and whether these new rules should be implemented. METHODS: During a half-year study period, inpatients with overridden DDI alerts regarding QT prolongation and with an electrocardiogram recorded before and within 1 month of the alert override were included if they did not have a ventricular pacemaker and did not use the low-risk combination cotrimoxazole and tacrolimus. QT-interval prolongation and the risk of developing TdP were calculated for all patients and related to the number of patients for whom a QT-alert would be generated in the new situation with the restricted database. RESULTS: Forty-nine patients (13%) met the inclusion criteria. In this study population, knowledge base-adjustment would reduce the number of alerts by 53%. However, the positive predictive value of QT alerts would not change (31% before and 30% after) and only 47% of the patients at risk of developing TdP would be identified in CPOEs using the adjusted knowledge base. CONCLUSION: The new rules for QT alerting would result in a poorer identification of patients at risk of developing TdP than the old rules. This is caused by the many non-drug-related risk factors for QT prolongation not being incorporated in CPOE alert generation. The partial contribution of all risk factors should be studied and used to create clinical rules for QT alerting with an acceptable positive predictive value. Springer-Verlag 2009-05-05 2009-09 /pmc/articles/PMC2729977/ /pubmed/19415251 http://dx.doi.org/10.1007/s00228-009-0654-3 Text en © The Author(s) 2009
spellingShingle Pharmacoepidemiology and Prescription
van der Sijs, Heleen
Kowlesar, Ravi
Aarts, Jos
Berg, Marc
Vulto, Arnold
van Gelder, Teun
Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title_full Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title_fullStr Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title_full_unstemmed Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title_short Unintended consequences of reducing QT-alert overload in a computerized physician order entry system
title_sort unintended consequences of reducing qt-alert overload in a computerized physician order entry system
topic Pharmacoepidemiology and Prescription
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2729977/
https://www.ncbi.nlm.nih.gov/pubmed/19415251
http://dx.doi.org/10.1007/s00228-009-0654-3
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