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To explore the incidence and factors influencing medication administration errors (MAEs) among nurses.
Medication administration is a global concern for patient safety. Few studies have assessed the incidence of MAEs or explored factors that considered the interplay between behaviour, the individual and the environment.
This retrospective study included 342 MAEs reported in the electronic nursing adverse event reporting system between January 2019 and September 2023 at a university-affiliated teaching hospital in China. Data on nurses' demographics and medication administration were extracted from the nursing adverse event reports. The reports were classified according to the severity of patient harm. The causes of the 342 MAEs were retrospectively analysed using content analysis based on Bandura's social cognitive theory. Descriptive statistics were used to calculate the proportion of medication errors and the distribution of subcategories.
In total, 74.3% of MAEs were adverse events owing to mistakes and resulted in no harm or only minor consequences for patients. Nurses aged 26–35 years and those with 6–10 years of experience were the most common groups experiencing MAEs. Factors influencing MAEs included personal (‘knowledge and skills’ and ‘physical state’), environmental (‘equipment and infrastructure,’ ‘work settings’ and ‘workload and workflow’) and behavioural (‘task performance’ and ‘supervision and communication’) factors. The study further highlighted the interrelationships among personal, behavioural and environmental factors.
Multiple factors influence MAEs among nurses. Nurse-related MAEs and the relationship between behaviours, individual factors and the environment, as well as ways to reduce the occurrence of MAEs, should be considered in depth.
Understanding the factors influencing MAEs can inform training programs and improve the clinical judgement of healthcare professionals involved in medication administration, ultimately improving patient prognoses and reducing MAEs.
The findings can help develop clinical guidelines for preventing MAEs.
To evaluate the impact of spatial separation on patient flow in the emergency department.
This was a retrospective, time-and-motion analysis conducted from 15 to 22 August, 2022 at the emergency department of a tertiary hospital in Kuala Lumpur, Malaysia. During this duration, spatial separation was implemented in critical and semi-critical zones to separate patients with symptoms of respiratory infections into respiratory area, and patients without into non-respiratory area. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Patients triaged to critical and semi-critical zones were included in this study. Timestamps of patient processes in emergency department until patient departure were documented.
The emergency department length-of-stay was longer in respiratory area compared to non-respiratory area; 527 min (381–698) versus 390 min (285–595) in critical zone and 477 min (312–739) versus 393 min (264–595) in semi-critical zone. In critical zone, time intervals of critical flow processes and compliance to hospital benchmarks were similar in both areas. More patients in respiratory area were managed within the arrival-to-contact ≤30 min benchmark and more patients in non-respiratory area had emergency department length-of-stay ≤8 h.
The implementation of spatial separation in infection control should address decision-to-departure delays to minimise emergency department length of stay.
The study evaluated the impact of spatial separation on patient flow in the emergency department. Emergency department length-of-stay was significantly prolonged in the respiratory area. Hospital administrators and policymakers can optimise infection control protocols measures in emergency departments, balancing infection control measures with efficient patient care delivery.
STROBE guidelines.
None.
The study obtained ethics approval from the institution's Medical Ethics Committee (MREC ID NO: 20221113–11727).
The author has checked and make sure our submission has conformed to the Journal's statistical guideline. There is a statistician on the author team (Noor Azhar).
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