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When it comes to determining what constitutes nursing workload, there are a number of approaches that represent and characterise the work of nursing across the three traditional shift patterns (morning/day, afternoon/evening and night). These are observational, self-reporting and work-sampling techniques. A review of the quantitative and qualitative literature to examine workload distributions between the three nursing shifts was undertaken. Using data sourced from the CINAHL, Scopus and Medline databases, the findings suggest that there is an inadequacy in establishing nursing productivity that is perhaps representative of the methods used to decipher nursing workload. This may contribute to poor quality care, and the high cost of excess nursing time contributes to the increasingly high costs of care. Linked to this is the nurse's job satisfaction. Quality of care and job satisfaction are important factors for the sustainability of the nursing workforce. There are few high-quality nursing articles that detail the workload distributions across the three nursing shifts and this is a potential area for further research. [ABSTRACT FROM AUTHOR]

Medication errors can have deleterious effects on patient safety and care. Interruptions, patient acuity and time pressures have all been cited as contributing factors in the incidence of medication errors. Yet, despite the number of different strategies that can be taken to reduce the incidence of medication errors, they still occur. The strategies often focus on refining systems and processes, depending on the root cause of the error. However, less recognised as contributory elements are human factors such as anger, hunger or tiredness. The aim of this quality improvement initiative was to reduce medication errors by 25% on a medical ward, through the introduction of the hunger, angry, lonely, tired (HALT) model to address the human factors associated with medication errors. Post-implementation, the HALT model appeared to have resulted in a total reduction in medication errors over a 2-month period by 31%. Mistakes related to human error were reduced by 25%, and those linked to communication and documentation errors by 22%. While this was a small-scale study, this is a significant reduction in medication errors. However, caution should be used when addressing other contributing factors associated with medication errors as using HALT alone will not address these. [ABSTRACT FROM AUTHOR]