scholarly journals Recommendations for selecting drug–drug interactions for clinical decision support

2016 ◽  
Vol 73 (8) ◽  
pp. 576-585 ◽  
Author(s):  
Hugh Tilson ◽  
Lisa E. Hines ◽  
Gerald McEvoy ◽  
David M. Weinstein ◽  
Philip D. Hansten ◽  
...  
Keyword(s):  
Decision Support ◽  
Drug Interactions ◽  
Clinical Decision Support ◽  
Clinical Decision

scholarly journals The use of a clinical decision support tool to assess the risk of QT drug–drug interactions in community pharmacies

2021 ◽  
Vol 12 ◽  
pp. 204209862199609
Author(s):  
Florine A. Berger ◽  
Heleen van der Sijs ◽  
Teun van Gelder ◽  
Patricia M. L. A. van den Bemt
Keyword(s):  
Decision Support ◽  
Drug Interactions ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Community Pharmacies ◽  
Support Tool ◽  
Interacting Agents ◽  
Before And After ◽  
Structured Approach

Introduction: The handling of drug–drug interactions regarding QTc-prolongation (QT-DDIs) is not well defined. A clinical decision support (CDS) tool will support risk management of QT-DDIs. Therefore, we studied the effect of a CDS tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists. Methods: An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of three months were included. The impact of the use of a CDS tool to support the handling of QT-DDIs was studied. For each QT-DDI, handling of the QT-DDI and patient characteristics were extracted from the pharmacy information system. Primary outcome was the proportion of QT-DDIs with an intervention. Secondary outcomes were the type of interventions and the time associated with handling QT-DDIs. Logistic regression analysis was used to analyse the primary outcome. Results: Two hundred and forty-four QT-DDIs pre-CDS tool and 157 QT-DDIs post-CDS tool were included. Pharmacists intervened in 43.0% and 35.7% of the QT-DDIs pre- and post-CDS tool respectively (odds ratio 0.74; 95% confidence interval 0.49–1.11). Substitution of interacting agents was the most frequent intervention. Pharmacists spent 20.8 ± 3.5 min (mean ± SD) on handling QT-DDIs pre-CDS tool, which was reduced to 14.9 ± 2.4 min (mean ± SD) post-CDS tool. Of these, 4.5 ± 0.7 min (mean ± SD) were spent on the CDS tool. Conclusion: The CDS tool might be a first step to developing a tool to manage QT-DDIs via a structured approach. Improvement of the tool is needed in order to increase its diagnostic value and reduce redundant QT-DDI alerts. Plain Language Summary The use of a tool to support the handling of QTc-prolonging drug interactions in community pharmacies Introduction: Several drugs have the ability to cause heart rhythm disturbances as a rare side effect. This rhythm disturbance is called QTc-interval prolongation. It may result in cardiac arrest. For health care professionals, such as physicians and pharmacists, it is difficult to decide whether or not it is safe to proceed treating a patient with combinations of two or more of these QT-prolonging drugs. Recently, a tool was developed that supports the risk management of these QT drug–drug interactions (QT-DDIs). Methods: In this study, we studied the effect of this tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists. An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of 3 months were included. Results: Two hundred and forty-four QT-DDIs pre-implementation of the tool and 157 QT-DDIs post-implementation of the tool were included. Pharmacists intervened in 43.0% of the QT-DDIs before the tool was implemented and in 35.7% after implementation of the tool. Substitution of one of the interacting agents was the most frequent intervention. Pharmacists spent less time on handling QT-DDIs when the tool was used. Conclusion: The clinical decision support tool might be a first step to developing a tool to manage QT-DDIs via a structured approach.

scholarly journals An Electronic Health Record Approach to Understanding Drug to Drug Interactions and Associated Knowledge Gaps in Intergrated Care of Multimorbidity

2021 ◽  
Author(s):  
George Despotou ◽  
Theodoros N. Arvanitis
Keyword(s):  
Decision Support ◽  
Drug Interactions ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Knowledge Gaps ◽  
Active Monitoring ◽  
Prescribing Practice ◽  
Practice Method ◽  
Intergrated Care ◽  
Multimorbid Patients

Multimorbid patients are prescribed a number of medications in parallel, which may often interact with each other, resulting in adverse effects. However, clinical guidelines on prescription of medications predominantly focus on individual conditions do not consider the guidance in the context of other guidelines, resulting in conflicts. C3-Cloud is an integrated care architecture managing multimorbidity, which amongst others, provides clinical decision support, based on reconciled guidelines, and active monitoring of drug interactions. To identify the severe interactions that resulted from multimorbidity management, in order to reevaluate guidelines as well as to identify knowledge gaps in prescribing practice. Method: Descriptive statistical analysis of interactions identified by the C3-Cloud clinical decision support, collected from the C3-Cloud FHIR repository. As part of a feasibility study, a number of interactions were identified, along with variable practice in how chemicals are represented in the EHR. 191 known severe interactions were identified. The Atorvastatin/Verapamil interaction was the most frequent. The approach has identified a number of interactions where the severity was not available, highlighting the need for further clinical review.

A critical evaluation of clinical decision support for the detection of drug–drug interactions

2011 ◽  
Vol 10 (6) ◽  
pp. 871-882 ◽  
Author(s):  
Pamela L Smithburger ◽  
Mitchell S Buckley ◽  
Sharon Bejian ◽  
Katie Burenheide ◽  
Sandra L Kane-Gill
Keyword(s):  
Decision Support ◽  
Drug Interactions ◽  
Clinical Decision Support ◽  
Critical Evaluation ◽  
Clinical Decision

scholarly journals Comparison of Clinical Importance of Drug Interactions Identified by Hospital Pharmacists and a Local Clinical Decision Support System

2021 ◽  
Vol 74 (3) ◽  
Author(s):  
Louise Lau ◽  
Harkaryn Bagri ◽  
Michael Legal ◽  
Karen Dahri
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Decision Support ◽  
Drug Interactions ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Pharmacy Services ◽  
Prise De Décision ◽  
Severity Classification ◽  
Level Of Agreement

Background: Drug–drug interactions (DDIs) may cause adverse drug events, potentially leading to hospital admission. Clinical decision support systems (CDSSs) can improve decision-making by clinicians as well as drug safety. However, previous research has suggested that pharmacists are concerned about discrepancies between CDSSs and common clinical practice in terms of severity ratings and recommended actions for DDIs. Objectives: The primary objective was to characterize the level of agreement in terms of DDI severity ranking and actions recommended between the local CDSS and pharmacists. The secondary objectives were to determine the level of agreement among pharmacists concerning DDI severity, to determine the influence of the CDSS on clinicians’ decision-making, and to review the literature supporting the severity rankings of DDIs identified in the study institution’s database. Methods: This 2-part survey study involved pharmacists and pharmacy residents working at 1 of 4 health organizations within the Lower Mainland Pharmacy Services, British Columbia, who were invited to participate by email. Participants were first asked to rank the severity of 15 drug pairs (representing potential DDIs) on a 5-point Likert scale and to select an action to manage each interaction. Participants were then given the CDSS severity classification for the same 15 pairs and again asked to select an appropriate management action. Results: Of the estimated 500 eligible pharmacists, a total of 73 pharmacists participated, for a response rate of about 15%. For DDIs of moderate severity, most participants chose to monitor. For severe and contraindicated interactions, the severity ranking and action proposed by participants varied, despite the same severity classification by the CDSS. There was poor agreement among respondents about the severity of the various DDIs. Moreover, knowledge of the CDSS severity ranking did not seem to change the actions proposed by most respondents. Conclusion: This study identified a gap between the local CDSS and clinical practice. There were discrepancies in terms of severity rankings and actions proposed to manage DDIs, particularly for severe and contraindicated DDIs. The current CDSS did not appear to have a large impact on clinical decision-making, which suggests that it may not be functioning to its full potential. RÉSUMÉ Contexte : Les interactions médicamenteuses (IM) peuvent provoquer des réactions indésirables et entraîner potentiellement une admission à l’hôpital. Les systèmes d’aide à la décision clinique (SADC) peuvent améliorer le processus de prise de décision des cliniciens ainsi que la sécurité de l’usage des médicaments. Cependant, des recherches antérieures mentionnent que les divergences entre les SADC et la pratique clinique courante de l’évaluation de la gravité des IM ainsi que les mesures recommandées préoccupent les pharmaciens. Objectifs : L’objectif principal consistait à caractériser le degré de concordance entre les SADC locaux et les décisions des pharmaciens en termes d’évaluation du degré de gravité des IM ainsi que des mesures recommandées. Les objectifs secondaires visaient quant à eux à déterminer le degré de concordance entre l’évaluation du degré de gravité de l’IM par les pharmaciens, à définir l’influence des SADC sur le processus de prise de décision des cliniciens et à examiner la documentation appuyant les critères d’évaluation de la gravité d’une IM, déterminés dans la base de données de l’institution où s’est déroulée l’étude. Méthodes : Cette étude en deux volets, menée au moyen d’un sondage par courriel, impliquait les pharmaciens et les résidents en pharmacie travaillant dans l’un des quatre organismes de santé des Lower Mainland Pharmacy Services en Colombie-Britannique. On a tout d’abord demandé aux participants d’évaluer le degré de gravité de 15 paires de médicaments (représentant des IM potentielles) sur une échelle de Likert à 5 points et de choisir une mesure visant à gérer chaque interaction. Les participants ont ensuite reçu l’évaluation par les SADC de la gravité des mêmes 15 paires; on leur a ensuite demandé de choisir une mesure de gestion appropriée. Résultats : Sur une estimation de 500 pharmaciens admissibles, 73 ont participé à l’étude et le taux de réponse s’est établi à 15 %. Concernant les IM dont le degré de gravité est modéré, la plupart des participants ont choisi la surveillance. L’évaluation du degré de gravité et les mesures proposées par les participants variaient lorsqu’il s’agissait d’interactions contre-indiquées et graves, et cela malgré une évaluation identique du degré de gravité par les SADC. On a relevé une mauvaise concordance entre les répondants quant à la gravité des diverses IM. De plus, la prise de connaissance par les répondants de l’évaluation du degré de gravité faite par les SADC ne semblait pas modifier les mesures proposées par la plupart d’entre eux. Conclusion : Cette étude a mis en évidence un fossé entre les SADC locaux et la pratique clinique. On y a relevé des divergences entre l’évaluation du degré de gravité des IM et les mesures proposées pour les gérer, en particulier lorsque les IM sont graves et contre-indiquées. Le SADC utilisé couramment ne semble pas avoir d’impact important sur le processus de décision clinique, ce qui laisse supposer qu’il pourrait ne pas fonctionner au maximum de son potentiel.

Sign in / Sign up

Export Citation Format

Share Document