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      Agreement of Different Drug-Drug Interaction Checkers for Proton Pump Inhibitors

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          Abstract

          Importance

          Proton pump inhibitors (PPIs) are a widely prescribed class of drugs, potentially interacting with a large number of medicines, especially among older patients with multimorbidity and polypharmacy. Beyond summary of product characteristics (SPCs), interaction checkers (ICs) are routinely used tools to help clinicians in medication review interventions.

          Objective

          To assess the consistency of information on drugs potentially interacting with PPIs as reported in their SPCs and different ICs.

          Design, Setting, and Participants

          This cross-sectional study was conducted using data from SPCs for 5 PPIs (omeprazole, esomeprazole, lansoprazole, pantoprazole, and rabeprazole) and 5 ICs (ie, INTERCheck WEB, Micromedex, Lexicomp, Epocrates, and drugs.com). Information from the SPCs and the ICs were extracted between July 15 and 30, 2023.

          Main Outcomes and Measures

          The main outcome was the level of agreement among SPCs and the 5 ICs in identifying drugs potentially interacting with PPIs and attributing drug-drug interaction (DDI) severity categories. The level of agreement was computed using Gwet AC1 statistic on the 5 ICs and by comparing 4-sets and 2-sets of ICs. As a sensitivity analysis, the level of agreement in listing PPI-related DDIs was evaluated using Cohen κ and Fleiss κ coefficients.

          Results

          Considering SPCs and the 5 ICs, a total of 518 potentially interacting drugs with omeprazole were reported, 455 for esomeprazole, 433 for lansoprazole, 421 for pantoprazole, and 405 for rabeprazole. As compared with the ICs, the SPCs reported a much smaller number of drugs potentially interacting with PPIs, with proportions ranging from 2.7% (11 potentially interacting drugs) for rabeprazole to 7.6% (33 potentially interacting drugs) for lansoprazole of the total identified drugs at risk of interaction with a PPI. The overall level of agreement among the 5 ICs for identifying potential interactions was poor (from 0.23 [95% CI, 0.21-0.25] for omeprazole to 0.27 [95% CI, 0.24-0.29] for pantoprazole and 0.27 [95% CI, 0.25-0.29] for rabeprazole). Similarly, the level of agreement was low in 4-set and 2-set analyses as well as when restricting the analysis to the potential DDIs identified as severe (range, 0.30-0.32).

          Conclusions and Relevance

          This cross-sectional study found significant disagreement among different ICs and SPCs, highlighting the need to focus on standardizing DDI databases. Therefore, to ensure evaluation and prevention of clinically relevant DDIs, it is recommended to revise multiple ICs and consult with specialists, such as clinical pharmacologists, particularly for patients with complex medical conditions.

          Key Points

          Question

          What is the level of agreement between the summary of product characteristics (SPCs) and interaction checkers (ICs) in providing information concerning drug-drug interactions (DDIs) related to proton pump inhibitors?

          Findings

          In this cross-sectional study of the SPCs for 5 proton pump inhibitors and 5 ICs, significant inconsistencies in listing potential pharmacological interactions between SPCs and ICs, as well as among different ICs, were found. Similarly, the level of agreement was low in 4-set and 2-set analyses as well as when restricting the analysis to the potential DDIs identified as severe.

          Meaning

          In this study, large heterogeneity of ICs and SPCs in reporting information on potential DDIs with proton pump inhibitors was found, highlighting the need to create a criterion standard DDI dataset.

          Abstract

          This cross-sectional study evaluates the consistency between summary of product characteristics and interaction checkers for potential drug-drug interactions with proton pump inhibitors (PPIs).

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          Most cited references31

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          What is polypharmacy? A systematic review of definitions

          Background Multimorbidity and the associated use of multiple medicines (polypharmacy), is common in the older population. Despite this, there is no consensus definition for polypharmacy. A systematic review was conducted to identify and summarise polypharmacy definitions in existing literature. Methods The reporting of this systematic review conforms to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist. MEDLINE (Ovid), EMBASE and Cochrane were systematically searched, as well as grey literature, to identify articles which defined the term polypharmacy (without any limits on the types of definitions) and were in English, published between 1st January 2000 and 30th May 2016. Definitions were categorised as i. numerical only (using the number of medications to define polypharmacy), ii. numerical with an associated duration of therapy or healthcare setting (such as during hospital stay) or iii. Descriptive (using a brief description to define polypharmacy). Results A total of 1156 articles were identified and 110 articles met the inclusion criteria. Articles not only defined polypharmacy but associated terms such as minor and major polypharmacy. As a result, a total of 138 definitions of polypharmacy and associated terms were obtained. There were 111 numerical only definitions (80.4% of all definitions), 15 numerical definitions which incorporated a duration of therapy or healthcare setting (10.9%) and 12 descriptive definitions (8.7%). The most commonly reported definition of polypharmacy was the numerical definition of five or more medications daily (n = 51, 46.4% of articles), with definitions ranging from two or more to 11 or more medicines. Only 6.4% of articles classified the distinction between appropriate and inappropriate polypharmacy, using descriptive definitions to make this distinction. Conclusions Polypharmacy definitions were variable. Numerical definitions of polypharmacy did not account for specific comorbidities present and make it difficult to assess safety and appropriateness of therapy in the clinical setting.
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            Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial.

            Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen's kappa and intra-class correlations to assess IRR.
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              • Article: not found

              Overriding of drug safety alerts in computerized physician order entry.

              Many computerized physician order entry (CPOE) systems have integrated drug safety alerts. The authors reviewed the literature on physician response to drug safety alerts and interpreted the results using Reason's framework of accident causation. In total, 17 papers met the inclusion criteria. Drug safety alerts are overridden by clinicians in 49% to 96% of cases. Alert overriding may often be justified and adverse drug events due to overridden alerts are not always preventable. A distinction between appropriate and useful alerts should be made. The alerting system may contain error-producing conditions like low specificity, low sensitivity, unclear information content, unnecessary workflow disruptions, and unsafe and inefficient handling. These may result in active failures of the physician, like ignoring alerts, misinterpretation, and incorrect handling. Efforts to improve patient safety by increasing correct handling of drug safety alerts should focus on the error-producing conditions in software and organization. Studies on cognitive processes playing a role in overriding drug safety alerts are lacking.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                9 July 2024
                July 2024
                9 July 2024
                : 7
                : 7
                : e2419851
                Affiliations
                [1 ]Department of Diagnostics and Public Health, University of Verona, Verona, Italy
                [2 ]Department of Medicine, University of Verona, Verona, Italy
                Author notes
                Article Information
                Accepted for Publication: April 15, 2024.
                Published: July 9, 2024. doi:10.1001/jamanetworkopen.2024.19851
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2024 Carollo M et al. JAMA Network Open.
                Corresponding Author: Gianluca Trifirò, PhD, Department of Diagnostics and Public Health, University of Verona, Verona, Italy ( gianluca.trifiro@ 123456univr.it ).
                Author Contributions: Drs Carollo and Trifirò had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Carollo and Crisafulli contributed equally to this work.
                Concept and design: Carollo, Trifirò.
                Acquisition, analysis, or interpretation of data: All authors.
                Drafting of the manuscript: Carollo, Crisafulli, Piccoli.
                Critical review of the manuscript for important intellectual content: Carollo, Crisafulli, Selleri, L'Abbate, Trifirò.
                Statistical analysis: Carollo, L'Abbate.
                Administrative, technical, or material support: Trifirò.
                Supervision: Carollo, Trifirò.
                Conflict of Interest Disclosures: Dr Trifirò reported serving on advisory boards and seminars funded by Sanofi, MSD, Eli Lilly and Co, Sobi, Celgene, Daichii Sankyo, Novo Nordisk, Gilead, and Amgen; serving as a scientific coordinator for INSPIRE srl, which has received funding from several pharmaceutical companies (eg, PTC Pharmaceuticals, Kiowa Kirin, Shonogi, Shire, Novo Nordisk, and Daichii Sankyo) for conducting observational studies; and consulting for Viatris in a legal case concerning an adverse reaction to sertraline outside the submitted work. No other disclosures were reported.
                Data Sharing Statement: See Supplement 2.
                Article
                zoi240639
                10.1001/jamanetworkopen.2024.19851
                11234238
                38980677
                0c5fdcdd-1882-4fad-b698-7c44ecf9343a
                Copyright 2024 Carollo M et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 18 December 2023
                : 15 April 2024
                Categories
                Research
                Original Investigation
                Online Only
                Pharmacy and Clinical Pharmacology

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