• Terapevt Arkh · Sep 2024

    [Detection of anticoagulant medication errors by triggers].

    • V A Otdelenov, E B Kleymenova, M D Nigmatkulova, S A Payushchik, O D Dukhanina, L P Yashina, and D A Sychev.
    • Russian Medical Academy of Continuous Professional Education.
    • Terapevt Arkh. 2024 Sep 14; 96 (8): 744750744-750.

    BackgroundMedication errors can cause preventable adverse events. For example, inappropriate use of anticoagulants (AC) can result in bleeding and thromboembolic complications. Detection and analysis of AC medication errors allow to reveal deficiencies in the safety systems in healthcare organizations.AimThe study was aimed to develop a method of systematic detection of anticoagulant medication errors for consequent audit, analysis and development of medication safety improvement measures.Materials And MethodsThe study was conducted in the multidisciplinary hospital and included 4924 patients admitted from January 2019 to December 2021 who received AC. Three laboratory triggers (international normalized ratio ≥4, serum creatinine ≥133 μmol/l, and glomerulofiltration rate <30 ml/min/1.73 m2) helped to reveal 4304 cases. Their matching with patient's data helped to develop combined triggers. Two clinical pharmacologists reviewed all cases identified by combined triggers for checking medication errors. The trigger was considered positive when anticoagulant medication error was detected in the history selected by combined trigger.ResultsOf the 4924 patients 253 (5.3%) were selected by combined triggers. Combined trigger allowed to reduce the amount of medical health records audit by 97.3%. Medication errors were detected in 137 patients. Positive predictive value of selected combined triggers varied from 0 to 63.9%. Aggregated positive predictive value of all combined triggers amounted to 54.2%. AC medication errors were detected in 2.8% patients.ConclusionMethod of systematic detection of AC medication errors using combined triggers in all hospitalized patients receiving AC allowed to reveal typical medication errors for consequent analysis and elaboration of measures to reduce preventable patient harm in healthcare settings.

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