Abstract
Background/aims Long-term trends in sickness absence have until now been assumed to be caused by economic cycles, age and gender changes in the workforce, and the success or failure of employers to reduce common causes of absence. This study aimed to identify unexplained patterns in sickness absence data. Methods A rolling 12-month average of sickness absence was used covering the 12 months ending March 2010 through to the 12 months ending October 2019. To determine the largest step increase in sickness absence, the average sickness absence rate was compared between successive 12-month periods. Results Time and space (spatiotemporal) patterns of up/down shifts are evident in the regional data across England. Over the 10-year period of the study, these patterns, rather than schemes to reduce sickness absence, appear to dominate the trend, which has shown no evidence of a change in the long-term average. Conclusions A rolling 12-month average, or more sophisticated methodologies, is required to detect and investigate less obvious spatiotemporal patterns in sickness absence data. Further research is required to investigate the causes of the up/down patterns observed in this data, which may be influencing sickness absences among NHS staff and wider health trends.
Original language | English |
---|---|
Article number | 0026 |
Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | British Journal of Health Care Management |
Volume | 26 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2 Apr 2020 |
Keywords
- On/off switching
- Sickness absence
- Spatiotemporal effects
- Time series
ASJC Scopus subject areas
- Health Policy
- Leadership and Management