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

Objectives: 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. Design: The study uses a retrospective observational cohort design using routinely collected data. Setting: One ambulance trust focused on a large, predominantly urban area in the UK. Participants: 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. Primary and secondary outcome measures: ‘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. Results: 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). Conclusions: 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.