ArticleBMJ open2021
Trends, variations and prediction of staff sickness absence rates among NHS ambulance services in England: a time series study.
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review and Evaluation of the Tools Measuring Work-Related Psychosocial Factors in Prospective Research on Sickness Absence of Health Care Workers.Journal of occupational rehabilitation · 2026Pooled it
- Article
- Time series forecasting of red blood cell demand in hematology patients using SARIMA and exponential smoothing models: a retrospective analysis in a Chinese tertiary hospital.Frontiers in medicine · 2025Article
- The impact and complete genome characterisation of viruses involved in outbreaks of gastroenteritis in a farrow-to-finish holding.Scientific reports · 2023Article
- Extreme temperatures and sickness absence in the Mediterranean province of Barcelona: An occupational health issue.Frontiers in public health · 2023Article
- The experiences and perceptions of wellbeing provision among English ambulance services staff: a multi-method qualitative study.BMC health services research · 2022Article
- The Level of Fear in the Polish Police Population during the COVID-19 Pandemic with the Impact of Sociodemographic Variables.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesOur aim was to measure ambulance sickness absence rates over time, comparing ambulance services and investigate the predictability of rates for future forecasting.
settingAll English ambulance services, UK.
designWe used a time series design analysing published monthly National Health Service staff sickness rates by gender, age, job role and region, comparing the 10 regional ambulance services in England between 2009 and 2018. Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) models were developed using Stata V.14.2 and trends displayed graphically.
participantsIndividual participant data were not available. The total number of full-time equivalent (FTE) days lost due to sickness absence (including non-working days) and total number of days available for work for each staff group and level were available. In line with The Data Protection Act, if the organisation had less than 330 FTE days available during the study period it was censored for analysis.
resultsA total of 1117 months of sickness absence rate data for all English ambulance services were included in the analysis. We found considerable variation in annual sickness absence rates between ambulance services and over the 10-year duration of the study in England. Across all the ambulance services the median days available were 1 336 888 with IQR of 548 796 and 73 346 median days lost due to sickness absence, with IQR of 30 551 days. Among clinical staff sickness absence varied seasonally with peaks in winter and falls over summer. The winter increases in sickness absence were largely predictable using seasonally adjusted (SARIMA) time series models.
conclusionSickness rates for clinical staff were found to vary considerably over time and by ambulance trust. Statistical models had sufficient predictive capability to help forecast sickness absence, enabling services to plan human resources more effectively at times of increased demand.
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