Examining time-to-transport decisions in Emergency Medical Services

Background

In modern healthcare systems, allocating resources and a patient-centred approach are crucial. While considerable efforts have been made to investigate emergency care and timing within the Emergency Medical Service (EMS)1,2,3, the subtleties surrounding time-to-transport decisions remain underexplored. This study examined factors affecting the time elapsed between EMS dispatch and ambulance readiness for the next emergency call using retrospective data from Hamad Medical Corporation Ambulance Service (HMCAS).

Methods

We conducted a comprehensive time-to-event analysis of HMCAS electronic patient care record system data from January to February 2023, representing 93,712 emergency cases attended to, using R Studio to understand the time from when an ambulance is dispatched until it is available for the subsequent call. Various parameters were considered, and their Hazard Ratios (HR) were computed. The impact of these variables on the time-to-handover was evaluated through a Cox regression model.

Results

Figure 1 indicates the transport probabilities as inferred from the Cox regression. As the time spent on scene increases (due to various reasons, among them: spending more time providing clinical treatment and health education because the patient decided not to go to the hospital, or the crew spending more time convincing the patient to go to the hospital by explaining the potential complications of their condition and the potential outcomes of a refusal to go to hospital), the probability of transporting the patient decreases. This trend suggests that extended time could adversely affect patient care if they eventually need to recall for an ambulance. The Schoenfeld plot (Figure 2) demonstrates that multiple variables have a significant impact on increasing the time-to-handover.

Conclusion

The study elucidates and clarifies key factors affecting time-to-transport in EMS, underscoring a decline in transport success rates as time on scene lengthens. This trend signifies potential inefficiencies in the current EMS workflow, necessitating further investigation for its broader implications on patient care and resource allocation. The multiple variables affecting time-to-handover reveal the complexity of EMS operations, emphasizing the need for a multi-pronged approach for optimization. Overall, the study provides a factual foundation for amending EMS protocols, aiming for a more efficient and patient-centered healthcare system.