Details

Autor(en) / Beteiligte

• Holden, Richard J
• Scanlon, Matthew C
• Patel, Neal R
• Kaushal, Rainu
• Escoto, Kamisha Hamilton
• Brown, Roger L
• Alper, Samuel J
• Arnold, Judi M
• Shalaby, Theresa M
• Murkowski, Kathleen
• Karsh, Ben-Tzion

Titel

A human factors framework and study of the effect of nursing workload on patient safety and employee quality of working life

Ist Teil von

• BMJ quality & safety, 2011-01, Vol.20 (1), p.15-24

Ort / Verlag

England: BMJ Publishing Group Ltd

Erscheinungsjahr

2011

Link zum Volltext

Quelle

BMJ Journals Archiv - DFG Nationallizenzen

Beschreibungen/Notizen

• BackgroundNursing workload is increasingly thought to contribute to both nurses' quality of working life and quality/safety of care. Prior studies lack a coherent model for conceptualising and measuring the effects of workload in healthcare. In contrast, we conceptualised a human factors model for workload specifying workload at three distinct levels of analysis and having multiple nurse and patient outcomes.MethodsTo test this model, we analysed results from a cross-sectional survey of a volunteer sample of nurses in six units of two academic tertiary care paediatric hospitals.ResultsWorkload measures were generally correlated with outcomes of interest. A multivariate structural model revealed that: the unit-level measure of staffing adequacy was significantly related to job dissatisfaction (path loading=0.31) and burnout (path loading=0.45); the task-level measure of mental workload related to interruptions, divided attention, and being rushed was associated with burnout (path loading=0.25) and medication error likelihood (path loading=1.04). Job-level workload was not uniquely and significantly associated with any outcomes.DiscussionThe human factors engineering model of nursing workload was supported by data from two paediatric hospitals. The findings provided a novel insight into specific ways that different types of workload could affect nurse and patient outcomes. These findings suggest further research and yield a number of human factors design suggestions.