AmReS: an observational retrospective time-to-event analysis of staff voluntary turnover in an English ambulance trust.

Abstract

The purpose of this study was to identify which, and to what extent, demographic and operational factors are indicative of likelihood for a new call handler or paramedic to remain in role within the first two years of employment at an ambulance trust using data held in the trust's bespoke data warehouse. The study uses a retrospective observational cohort design using routinely collected data. One ambulance trust focused on a large, predominantly urban area in the UK. The study used the data of all employees of the trust who started employment as call handlers (869) or paramedics (1672) between 1 January 2018 and 31 July 2023. 'Time-to-event' analysis of 'likelihood to remain in post within the first two years of employment' as call handlers or paramedics via accelerated failure time regression. Several factors showed a significant contribution to the likelihood of remaining in post within an ambulance National Health Service Trust. Among the findings, short-term sick leave in the first two years of employment was associated with increased retention for paramedics (0.040, 95% CI 0.030, 0.060). In addition, female call handlers were found to have increased retention (0.29, 95% CI 0.043, 0.54), and paramedic retention increased with time outside of 'job cycle time' (JCT) activities (ie, activities other than responding to calls) (0.097, 95% CI 0.057, 0.14). This study presents a method for extracting new insights from routinely collected operational data, identifying common drivers and specific predictors for retention among the ambulance NHS workforce. It emphasises the importance of workforce-centred retention strategies, highlighting the need for non-JCT time, which in turn would allow paramedics to have time to reflect and recuperate to avoid burnout and attrition. The study also suggests that a lack of sick leave might indicate a lack of trust and self-care culture, potentially leading to paramedic staff attrition. Our approach to retention analytics provides a new mechanism for trusts to monitor and respond to their attrition risks in a timely, proactive fashion.