Can Helicopters Solve the Transport Dilemma for Patients With Symptoms of Large-Vessel Occlusion Stroke in Intermediate Density Areas? A Simulation Model Based on Real Life Data

Parallel activation of helicopter and ground transportation after dispatcher identification of suspected anterior large vessel occlusion stroke in rural areas: a proof-of-concept case with modeling from the LESTOR trial

BACKGROUND

When stroke patients with suspected anterior large vessel occlusion (aLVO) happen to live in rural areas, two main options exist for prehospital transport: (i) the drip-and-ship (DnS) strategy, which ensures rapid access to intravenous thrombolysis (IVT) at the nearest primary stroke center but requires time-consuming interhospital transfer for endovascular thrombectomy (EVT) because the latter is only available at comprehensive stroke centers (CSC); and (ii) the mothership (MS) strategy, which entails direct transport to a CSC and allows for faster access to EVT but carries the risk of IVT being delayed or even the time window being missed completely. The use of a helicopter might shorten the transport time to the CSC in rural areas. However, if the aLVO stroke is only recognized by the emergency service on site, the helicopter must be requested in addition, which extends the prehospital time and partially negates the time advantage. We hypothesized that parallel activation of ground and helicopter transportation in case of aLVO suspicion by the dispatcher (aLVO-guided dispatch strategy) could shorten the prehospital time in rural areas and enable faster treatment with IVT and EVT.

METHODS

As a proof-of-concept, we report a case from the LESTOR trial where the dispatcher suspected an aLVO stroke during the emergency call and dispatched EMS and HEMS in parallel. Based on this case, we compare the provided aLVO-guided dispatch strategy to the DnS and MS strategies regarding the times to IVT and EVT using a highly realistic modeling approach.

RESULTS

With the aLVO-guided dispatch strategy, the patient received IVT and EVT faster than with the DnS or MS strategies. IVT was administered 6 min faster than in the DnS strategy and 22 min faster than in the MS strategy, and EVT was started 47 min earlier than in the DnS strategy and 22 min earlier than in the MS strategy.

CONCLUSION

In rural areas, parallel activation of ground and helicopter emergency services following dispatcher identification of stroke patients with suspected aLVO could provide rapid access to both IVT and EVT, thereby overcoming the limitations of the DnS and MS strategies.

Optimizing remote and rural prehospital resources using air transport of thrombectomy candidates

BACKGROUND

In Finland, the yearly number of mechanical thrombectomies for acute stroke is increasing and more patients are transported over 100 km to the comprehensive stroke centre (CSC) for definitive care. This leaves the rural townships without immediate emergency medical services (EMS) for hours. In this study we compare the EMS' estimated return times to own station after the handover of a thrombectomy candidate between two transport methods: (1) using ground transportation with an ambulance to the CSC or (2) using a hydrid strategy starting the transportation with an ambulance and continuing by air with a helicopter emergency medical services unit (HEMS).

METHODS

We reviewed retrospectively all thrombectomy candidates' transportations from the hospital district of South Ostrobothnia to definitive care at the nearest CSC, Tampere University Hospital from June 2020 to October 2022. The dispatch protocol stated that a thrombectomy candidate's transport begins immediately with an ambulance and if the local HEMS unit is available the patient is handed over to them at a rendezvous. If not, the patient is transported to the CSC by ground. Transport times and locations of the patient handovers were reviewed from the CSC's EMS database and the driving time back to ambulance station was estimated using Google maps. The HEMS unit's pilot's log was reviewed to assess their mission engagement time.

RESULTS

The median distance from the CSC to the ambulances' stations was 188 km (IQR 149-204 km) and from the rendezvous with the HEMS unit 70 km (IQR 51-91 km, p < 0.001). The estimated median driving time back to station after the patient handover at the CSC was 145 min (IQR 117-153 min) compared to the patient handover to the HEMS unit 53 min (IQR 38-68 min, p < 0.001). The HEMS unit was occupied in thrombectomy candidate's transport mission for a median of 136 min (IQR 127-148 min).

CONCLUSION

A hybrid strategy to transport thrombectomy candidates with an ambulance and a helicopter reallocates the EMS resources markedly faster back to their own district.

Effect of urgency level on prehospital emergency transport times: a natural experiment

Accurate estimation of ambulance transport time from the scene of incident to arrival at the emergency department (ED) is important for effective resource management and emergency care system planning. Further, differences in transport times between different urgency levels highlight the benefits of ambulance transports with highest urgency level in a setting where ambulances are allowed to not follow standard traffic rules. The objective of the study is to compare ambulance urgency level on the differences in estimates of ambulance transport times generated by Google Maps and the observed transport times in a prehospital setting where emergency vehicles have their own traffic laws. The study was designed as a natural experiment and register study. Ambulance transports dispatched with different levels of urgency (Level A and B) were included in the Central Denmark Region (a mixed urban and rural area) from March 10 to June 11, 2021. Ambulance transports for highest urgency level were compared to lowest urgency level with Google Maps estimated transport times as reference. We analyzed 1981 highest urgency level and 8.958 lowest urgency level ambulance transports. Google Maps significantly overestimated the duration of transports operating at highest level of urgency (Level A) by 1.9 min/10 km (95% CI 1.8; 2.0) in average and 4.8 min/10 km (95% CI 3.9; 5.6) for the first driven 10 km. Contrary, Google Maps significantly underestimated the duration of transports operating at lowest level of urgency (Level B) by -1.8 min/10 km (95% CI -2.1; -1.5) in average and -4.4 min/10 km (95% CI -5.4; -3.5) for the first driven 10 km. Google Maps systematically overestimates transport times of ambulance transports driven with Level A, the highest level of urgency in a setting where ambulances are allowed to not follow standard traffic rules. The results highlight the benefit of using urgency Level A and provide valuable information for emergency care management.

Spatiotemporal analysis of regional TIA trends

Background

There has been a decline in the stroke incidence across high income countries but such knowledge exists at Country or State rather than areal unit level such local government area (LGA). In this disease mapping study, we evaluate if there are local hot spots or temporal trends in TIA rate. Such knowledge will be of help in planning healthcare service delivery across regions.

Methods

Linked hospital discharge data (Victorian Admitted Episodes Dataset or VAED) was used to collect TIA (defined by ICD-10-AM codes G450-G459) cases from 2001 to 2011. The State of Victoria is the second most populous state in Australia, with a population of 6.7 million and can be divided into 79 administrative units or LGA. The data is anonymized and contains residence of the patient in terms of LGA but not exact location. The date of the TIA event when the patient is admitted to hospital is provided in the dataset. The number of TIAs per year was aggregated for each LGA. Standardized TIA ratios were calculated by dividing actual over expected cases for each LGA per year. We used Integrated Nested Laplace Approximation (INLA) to perform spatial and spatiotemporal regression, adjusting for hypertension, sex and population, age (≥60), and socio-economic status (SES) decile within the LGA. The final model was chosen based on the lowest the Deviance Information Criterion (DIC) and Watanabe-Akaike information criteria (WAIC).

Results

Choropleth maps showed a higher standardized TIA ratios in North-West rural region. Compared to the baseline model (DIC 13,159, WAIC 13,261), adding in a spatial random effect significantly improved the model (DIC 6,463, WAIC 6,667). However, adding a temporal component did not lead to a significant improvement (DIC 6,483, WAIC 6,707).

Conclusion

Our finding suggests a statically significant spatial component to TIA rate over regional areas but no temporal changes or yearly trends. We propose that such exploratory method should be followed by evaluation of reasons for regional variations and which in turn can identify opportunities in primary prevention of stroke, and stroke care.