Night work for hospital nurses and sickness absence: a retrospective study using electronic rostering systems.
Chiara Dall'OraJane E BallOliver C RedfernPeter GriffithsPublished in: Chronobiology international (2020)
There is conflicting evidence on the effect of night work on sickness absence. Most previous studies used self-reporting to identify shift patterns and measure levels of sickness absence. In contrast, this study used objective data from electronic rosters to explore the association of nurses' patterns of night work and sickness absence. This was a retrospective longitudinal study of nurse roster data from 32 general medical and surgical wards in a large acute hospital in England. We used data from 3 years and included both registered nurses and unregistered nursing assistants. We used generalized linear-mixed models to explore the association between night work and the subsequent occurrence of sickness absence. Of 601,282 shifts worked by 1944 nursing staff, 38,051 shifts were lost due to sickness absence. After controlling for potential confounders including proportion of long (≥12 h) shifts worked, proportion of overtime shifts, proportion of shifts worked in the past 7 days, and staff grade, we found that staff working more than 75% of their shifts in the past 7 days as night shifts were more likely to experience sickness absence (aOR = 1.12; 95% CI: 1.03-1.21), compared to staff working on day only schedules. Sub-group analysis found that an association between a high proportion of night shifts worked and long-term sickness (aOR = 1.31; 95% CI: 1.15-1.50), but not short-term sickness. Working high proportions of night shifts, likely representing permanent night work schedules, is associated with a higher risk of long-term sickness absence for nurses working in inpatient adult wards in acute hospitals. The higher sickness absence rates associated with permanent night shifts could result in additional costs or loss of productivity for hospitals. This study challenges the assumption that permanent night schedules maximize circadian adjustment and, therefore, reduce health problems.
Keyphrases
- healthcare
- mental health
- sleep quality
- magnetic resonance
- public health
- electronic health record
- emergency department
- primary care
- liver failure
- climate change
- respiratory failure
- intensive care unit
- magnetic resonance imaging
- palliative care
- long term care
- depressive symptoms
- young adults
- artificial intelligence
- drug induced
- human health
- case control
- acute respiratory distress syndrome