Dataset Information

Trends, variations and prediction of staff sickness absence rates among NHS ambulance services in England: a time series study.

ABSTRACT:

Objectives

Our aim was to measure ambulance sickness absence rates over time, comparing ambulance services and investigate the predictability of rates for future forecasting.

Setting

All English ambulance services, UK.

Design

We 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.

Participants

Individual 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.

Results

A 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.

Conclusion

Sickness 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.

SUBMITTER: Asghar ZB

PROVIDER: S-EPMC8483034 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:This paper examines issues related to the future supply of registered nursing staff, midwives and health visitors in the National Health Service (NHS) in England at a time when there are major public sector funding constraints and as more of these staff are reaching retirement age. Based on available workforce data, the paper reviews different possible scenarios for the supply of NHS nurses over a ten year period, assessing the impact of different numbers of new staff being trained and of varying retirement patterns from the ageing profession.The government in England has more policy levers available than is the case in many other countries. It determines the number of pre-registration training places that are commissioned and funded, it is the major employer, and it also controls the inflow of nurses from other countries through migration policies. Scenario models provide a picture of what the future might look like under various assumptions. These outcomes can be quantified and the results used to assess the risks and opportunities of alternate policy decisions. The approach used in this paper is that of the aggregate deterministic supply model.As part of this exercise, eight scenarios were selected and modelled. These were:A. "No change"- current inflows and outflowsB. "Redundancies" - current inflow with higher outflowC. "Improved retention" - current inflow with lower outflowD. "Reduced training intakes A" - lower inflows with lower outflowE. "Reduced training intakes B" - lower inflow with higher outflowsF. "Pension time-bomb"- current inflow with a higher rate of retirementG. "Pension delayed"- current inflow with a lower rate of retirementH. "Worst case" - lower inflow and higher outflow including higher retirementMost of the scenarios indicate that a reduction in the supply of nursing staff to NHS England is possible over the next ten years. Small changes in assumptions can make a substantial difference to outcomes and therefore emphasize the point that it is unwise to base policy decisions on a single projection. It is important that different scenarios are considered that may be regarded as possible futures, based on a realistic assessment of the available workforce data, policies and broader labour market and funding outlook.

Project description:ObjectivesAn initial report of findings from 1.14 million SARS CoV-2 serology tests in National Health Service (NHS) staff to compare NHS staff seroconversion with community seroconversion rates at a regional level.DesignA national cross-sectional survey.SettingA SARS-CoV-2 antibody testing programme offered across all NHS Trusts.Participants1.14 million NHS staff.InterventionSARS-CoV-2 antibody testing.Primary and secondary outcome measuresSARS-CoV-2 antibody testing was used to estimate the seroprevalence of SARS-CoV-2 in NHS staff by region, compared with community seroprevalence as determined by the COVID-19 Infection Survey (Office for National Statistics). We also explored seroprevalence trends by regional COVID-19 activity, using regional death rates as a proxy for COVID-19 'activity'.Results1 146 310 tests were undertaken on NHS staff between 26 May and 31 August 2020. 186 897 NHS tests were positive giving a seroconversion rate of 16.3% (95% CI 16.2% to 16.4%), in contrast to the national community seroconversion rate of 5.9% (95% CI 5.3% to 6.6%). There was significant geographical regional variation, which mirrored the trends seen in community prevalence rates. NHS staff were infected at a higher rate than the general population (OR 3.1, 95% CI 2.8 to 3.5). NHS seroconversion by regional death rate suggested a trend towards higher seroconversion rates in the areas with higher COVID-19 'activity'.ConclusionsThis is the first cross-sectional survey assessing the risk of COVID-19 disease in healthcare workers at a national level. It is the largest study of its kind. It suggests that NHS staff have a significantly higher rate of COVID-19 seroconversion compared with the general population in England, with regional variation across the country which matches the background population prevalence trends. There was also a trend towards higher seroconversion rates in areas which had experienced high COVID-19 clinical activity. This work has global significance in terms of the value of such a testing programme and contributing to the understanding of healthcare worker seroconversion at a national level.

Project description:ObjectivesThis feasibility study aimed to model in silico the current healthcare system for patients triaged to a primary care disposition following a call to National Health Service (NHS) 111 and determine the effect of reconfiguring the healthcare system to ensure a timely primary care service contact.DesignDiscrete event simulation.SettingSingle English NHS 111 call centre in Yorkshire.ParticipantsCallers registered with a Bradford general practitioner who contacted the NHS 111 service in 2021 and were triaged to a primary care disposition.Primary and secondary outcome measuresFace validity of conceptual model. Comparison between real and simulated data for quarterly counts (and 95% CIs) for patient contact with emergency ambulance (999), 111, and primary and secondary care services. Mean difference and 95% CIs in healthcare system usage between simulations and difference in mean proportion of avoidable admissions for callers who presented to an emergency department (ED).ResultsThe simulation of the current system estimated that there would be 39 283 (95% CI 39 237 to 39 328) primary care contacts, 2042 (95% CI 2032 to 2051) 999 calls and 1120 (95% CI 1114 to 1127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean percentage increase of 196.1% (95% CI 192.2% to 199.9%) in primary care contacts, and a mean percentage decrease of 78.0% (95% CI 69.8% to 86.2%) in 999 calls and 88.1% (95% CI 81.7% to 94.5%) in ED attendances. Avoidable ED attendances reduced by a mean of -26 (95% CI -35 to -17).ConclusionIn this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost-effective and acceptable to both patients and primary care clinicians.

Project description:BackgroundOver the past decade, growing attention has been given to the mental health of workers. One way to examine the mental health of workers is to look at the incidence rates of mental illness-related sickness absence. There is a scarcity of literature in which the incidence rates of mental illness-related sickness absence among different countries have been considered together. The purpose of this systematic literature review is to address the question: Are there similarities and differences in the incidence rates of mental disorder-related sickness absence among and within OECD identified Social Democratic, Liberal and Latin American country categories? In this paper, we seek to identify differences and similarities in the literature rather than to explain them. With this review, we lay the groundwork for and point to areas for future research as well as to raise questions regarding reasons for the differences and similarities.MethodsA systematic literature search of the following databases were performed: Medline Current, Medline In-process, PsycINFO, Econlit and Web of Science. The search period covered 2002-2013. The systematic literature search focused on working adults between 18-65 years old who had not retired and who had mental and/or substance abuse disorders. Intervention studies were excluded. The search focused on medically certified sickness absences.ResultsA total of 3,818 unique citations were identified. Of these, 10 studies met the inclusion/exclusion criteria; six were from Social Democratic countries. Their quality ranged from good to excellent. There was variation in the incidence rates reported by the studies from the Social Democratic, Liberal and Latin American countries in this review.ConclusionsThe results of this systematic review suggest that this is an emerging area of inquiry that needs to continue to grow. Priority areas to support growth include cross jurisdictional collaboration and development of a typology characterizing the benefit generosity and work integration policies of sickness absence schemes. Finally, the literature should be updated to reflect changes in sickness absence benefit schemes over time.

Project description:BackgroundNHS ambulance service staff are at risk of poor physical and mental wellbeing because of the likelihood of encountering stressful and traumatic incidents. While reducing sickness absence and improving wellbeing support to ambulance staff is a key NHS priority, few studies have empirically documented a national picture to inform policy and service re-design. The study aimed to understand how ambulance service trusts in England deal with staff health and wellbeing, as well as how the staff perceive and use wellbeing services.MethodsTo achieve our aim, we undertook semi-structured telephone interviews with health and wellbeing leads and patient-facing ambulance staff, as well as undertaking documentary analysis of ambulance trust policies on wellbeing. The study was conducted both before and during the UK first COVID-19 pandemic wave. The University of Lincoln ethics committee and the Health Research Authority (HRA) granted ethical approval. Overall, we analysed 57 staff wellbeing policy documents across all Trusts. Additionally, we interviewed a Health and Wellbeing Lead in eight Trusts as well as 25 ambulance and control room staff across three Trusts.ResultsThe study highlighted clear variations between organisational and individual actions to support wellbeing across Trust policies. Wellbeing leads acknowledged real 'tensions' between individual and organisational responsibility for wellbeing. Behaviour changes around diet and exercise were perceived to have a positive effect on the overall mental health of their workforce. Wellbeing leads generally agreed that mental health was given primacy over other wellbeing initiatives. Variable experiences of health and wellbeing support were partly contingent on the levels of management support, impacted by organisational culture and service delivery challenges for staff.ConclusionAmbulance service work can impact upon physical and mental health, which necessitates effective support for staff mental health and wellbeing. Increasing the knowledge of line managers around the availability of services could improve engagement.

Project description:ObjectiveTo assess the impact of reorganisation of neonatal specialist care services in England after a UK Department of Health report in 2003.DesignA population-wide observational comparison of outcomes over two epochs, before and after the establishment of managed clinical neonatal networks.SettingEpoch one: 294 maternity and neonatal units in England, Wales, and Northern Ireland, 1 September 1998 to 31 August 2000, as reported by the Confidential Enquiry into Stillbirths and Sudden Deaths in Infancy Project 27/28. Epoch two: 146 neonatal units in England contributing data to the National Neonatal Research Database at the Neonatal Data Analysis Unit, 1 January 2009 to 31 December 2010.ParticipantsBabies born at a gestational age of 27(+0)-28(+6) (weeks+days): 3522 live births in epoch one; 2919 babies admitted to a neonatal unit within 28 days of birth in epoch two.InterventionThe national reorganisation of neonatal services into managed clinical networks.Main outcome measuresThe proportion of babies born at hospitals providing the highest volume of neonatal specialist care (≥ 2000 neonatal intensive care days annually), having an acute transfer (within the first 24 hours after birth) and/or a late transfer (between 24 hours and 28 days after birth) to another hospital, assessed by change in distribution of transfer category ("none," "acute," "late"), and babies from multiple births separated by transfer. For acute transfers in epoch two, the level of specialist neonatal care provided at the destination hospital (British Association of Perinatal Medicine criteria).ResultsAfter reorganisation, there were increases in the proportions of babies born at 27-28 weeks' gestation in hospitals providing the highest volume of neonatal specialist care (18% (631/3495) v 49% (1325/2724); odds ratio 4.30, 95% confidence interval 3.83 to 4.82; P<0.001) and in acute and late postnatal transfers (7% (235) v 12% (360) and 18% (579) v 22% (640), respectively; P<0.001). There was no significant change in the proportion of babies from multiple births separated by transfer (33% (39) v 29% (38); 0.86, 0.50 to 1.46; P=0.57). In epoch two, 32% of acute transfers were to a neonatal unit providing either an equivalent (n=87) or lower (n=26) level of specialist care.ConclusionsThere is evidence of some improvement in the delivery of neonatal specialist care after reorganisation. The increase in acute transfers in epoch two, in conjunction with the high proportion transferred to a neonatal unit providing an equivalent or lower level of specialist care, and the continued separation of babies from multiple births, are indicative of poor coordination between maternity and neonatal services to facilitate in utero transfer before delivery, and continuing inadequacies in capacity of intensive care cots. Historical data representing epoch one are available only in aggregate form, preventing examination of temporal trends or confounding factors. This limits the extent to which differences between epochs can be attributed to reorganisation and highlights the importance of routine, prospective data collection for evaluation of future health service reorganisations.