Medication Errors Caused by Nurses and Physicians in a Swiss Acute Care Community Hospital: Frequency and Correlation to Nurses’ Reported Workload / Von Pflegefachpersonen und Ärzten/-innen verursachte Medikamentenfehler in einem Schweizer Akutspital: Häufigkeit und Korrelation zur Arbeitsbelastung

Abstract

Abstract Objectives This study was carried out in a Swiss acute care community hospital to investigate the frequency, type, causes and potential clinical consequences of medication errors (MEs) caused by nurses and physicians in all stages of a technology-supported medication process, the relationship between the nurses’ workload and the medication administration errors (MAEs) and their reason for workload. Methods In this descriptive cross-sectional study, a questionnaire, the adapted Medication Error Self Reporting Tool (A-MESRT), was used to identify MEs in all stages of the medication process and record nurses’ self-perceived workload during medication administration. Results A total of 1936 completed A-MESRTs were returned. A total of 751 (38.8%) respondents reported different MEs. The highest number of errors occurred during medication administration (43%), followed by errors during dispensing (34%) and physician ordering errors using a computerised physician order entry (CPOE) system (23%). Of the 768 (100%) handwritten orders, 232 (30.2%) were erroneous. Moreover, the greater the individual nurse’s workload during a shift, the higher was the relative probability of committing an MAE (χ2 = 85.479, df = 1, OR = 2.129, p < 0.001). Furthermore, the three main causes of high or very high workload were revealed: (1) many newly operated patients to monitor; (2) complex multimorbid patients, for example, those with delirium; and (3) patients with complications after surgery. Conclusion The A-MESRT showed that the highest rate of MEs caused by nurses and physicians is in the non-technologically supported steps, demonstrating the potential benefits of a technology-supported medication process. Moreover, this study revealed a statistically significant correlation between nurses’ workload and MAEs.