
==== Front
J Neurol
J Neurol
Journal of Neurology
0340-5354
1432-1459
Springer Berlin Heidelberg Berlin/Heidelberg

38900295
12515
10.1007/s00415-024-12515-w
Letter to the Editors
The impact of an MSU service on acute stroke care in a middle-sized city: a simulation-based analysis
Szabo Kristina 1
Nagel Till 2
Grund Alexander 1
Kravatzky Alexander 2
Sandikci Vesile 1
Radder Markus 1
Rink Johann 3
http://orcid.org/0000-0001-5672-0865
Hoyer Carolin carolin.hoyer@umm.de

1
1 grid.7700.0 0000 0001 2190 4373 Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
2 grid.440963.c 0000 0001 2353 1865 Human Data Interaction Lab, Mannheim University of Applied Sciences, Mannheim, Germany
3 grid.7700.0 0000 0001 2190 4373 Department of Radiology and Nuclear Medicine, Mannheim University Medical Centre, Heidelberg University, Mannheim, Germany
20 6 2024
20 6 2024
2024
271 9 63596362
10 5 2024
9 6 2024
10 6 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
http://dx.doi.org/10.13039/100008383 Bundesministerium für Verkehr und Digitale Infrastruktur 45FGU140_F Medizinische Fakultät Mannheim der Universität Heidelberg (8990)Open Access funding enabled and organized by Projekt DEAL.

issue-copyright-statement© Springer-Verlag GmbH Germany, part of Springer Nature 2024
==== Body
pmcSirs,

Intravenous thrombolysis with alteplase is an effective but highly time-sensitive therapy for acute ischemic stroke; thrombolysis within one hour of onset (the so-called "golden hour") is associated with the best clinical outcomes, but only 1.4% of patients are treated this early [6, 13]. Although in-hospital acute stroke care in urban areas in Germany has continued to improve in recent years, particularly with an increase in the number and access to mechanical thrombectomy, rates of intravenous thrombolysis have remained stable [12]. This ceiling effect may indicate the need for further focus on optimizing prehospital management of acute stroke patients. Perhaps the most exciting approach to reducing prehospital delay is the use of specialized ambulances equipped with stroke care teams, CT scanners and point-of-care laboratory testing devices—Mobile Stroke Units (MSUs)—to provide diagnosis and treatment of acute stroke in the field. Current guidelines of the European Stroke Organization recommend the use of MSUs over conventional care for the prehospital management of patients with suspected stroke because of their positive impact on various dimensions of stroke care, such as IVT rates and short- and long-term stroke outcomes [14]. Due to associated high dispatch volumes, large and densely populated cities have been considered ideal for MSU utilization. Moreover, MSUs may enhance care in remote rural areas often lacking medical services [5]. However, the identification of the most suitable environment for specific ways of MSU implementation—urban or rural—as well as the transferability of the concept to new settings still remains largely unanswered questions. A recent study investigated the potential effect of an MSU in the German–Danish border territory, where different healthcare—systemic and organizational principles—apply [1].

Prior to launching an MSU service in the city of Mannheim, a middle-sized urban region with 310,000 inhabitants and a surface area of 145 square kilometers, we sought to estimate potential benefits of MSU utilization for acute stroke care in such a setting in Germany, which has not yet been put under scientific scrutiny.

In this retrospective cohort study, we analyzed data of 552 patients with complete data regarding prehospital process times and a confirmed diagnosis of acute cerebrovascular events (CVE), including ischemic and hemorrhagic strokes and transient ischemic attacks, admitted to the Comprehensive Stroke Center, Department Neurology, University Hospital Mannheim, Germany between 06/2022 and 06/2023. From a total of 1,051 cases extracted from our Comprehensive Stroke Center database, the following were excluded: secondary transports to our hospital (N = 147), in-house strokes (N = 19), self-presenting patients (N = 132), unknown or extended time windows (N = 14), and incomplete documentation of prehospital process times (N = 187). We compared real-world emergency medical care (EMC) data with a modeled scenario in which an MSU is stationed at our hospital, excellently accessible and centrally located within Mannheim’s geographical boundaries.

Process times for patients receiving IVT were determined as follows:

for EMC care:

Alarm-to-patient time = timespan between alarm and arrival on scene

Alarm-to-needle time = timespan between alarm and arrival a hospital + door-to-needle time

Onset-to-needle time = timespan between onset and alarm + alarm-to-needle time

for simulated MSU care:

Alarm-to-patient time = travel time from hospital to scene

Alarm-to-needle time = travel time from hospital to scene + door-to-needle time

Onset-to-needle time = timespan between onset and alarm + alarm-to-needle time

Process times for all other patients were determined as follows:

for EMC care:

Alarm-to-patient time = timespan between alarm and arrival on scene

Alarm-to-stroke-unit-admission time = timespan between alarm and arrival a hospital + mean door-to-needle time (assumed to represent average work-up time of stroke patients in the emergency department)

for simulated MSU care:

Alarm-to-patient time = travel time from hospital to scene

Alarm-to-stroke-unit-admission time = travel time from hospital to scene + mean door-to-needle time + travel time from scene to hospital

For the comparison of the intra-subject difference in process times for EMC care and for simulated MSU care, we used paired sample t tests. In addition, the rate of thrombolysis performed within 1 h after onset was calculated and possible differences between the two scenarios concerning the golden-hour thrombolysis rates were calculated using the chi2-test. P < 0.05 indicates statistical significance. Statistical analysis was performed using IBM SPSS Statistics Version 29.

MSU travel times were determined by identifying the optimal routes via Geoapify APIs. Case locations were placed using a Gaussian jittering method within a 500-m radius to enhance patient privacy [15]. The study was approved by the local ethics committee.

Even though the MSU requires more time to reach the scene—differing by 4 min to EMC—alarm-to-needle time in thrombolysed patients is accelerated by 35 min in this setting (Table 1, Fig. 1). In addition, the rate of patients thrombolysed within 60 min from symptom onset is significantly higher when an MSU is utilized: MSU care increases the proportion of golden-hour thrombolysis more than fivefold (MSU 43/116; 37.1% versus EMC 8/116; 6.9%). All other CVE patients are transferred to dedicated neurological in-hospital care significantly faster in the MSU scenario (Table 1).Table 1 Comparison of real-world EMC care versus MSU service process times

		EMC	MSU	p-value	
Thrombolysed strokes, M (SD), min	alarm-to-patient	9.98 (4.81)	13.20 (7.06)	 < 0.001	
[n = 116]	alarm-to-needle	80.18 (23.98)	45.48 (17.86)	 < 0.001	
CVEs, no IVT, M (SD), min	alarm-to-patient	10.10 (6.67)	13.89 (7.03)	 < 0.001	
[n = 436]	alarm-to-stroke unit	84.30 (20.81)	59.63 (14.51)	 < 0.001	
CVE: cerebrovascular events; EMC: emergency medical service; IVT: intravenous thrombolysis; MSU: mobile stroke unit; M: mean; SD: standard deviation

Fig. 1 This figure illustrates the spatial and temporal distribution of stroke response cases. On the left, two dot strip plots overlaid on box plots reveal the onset-to-needle times for all cases in both real-world EMC and modeled MSU settings, with a center slope chart depicting the time saved per case, emphasizing the reduced median times in the MSU scenario. The map on the right details case locations in Mannheim and surroundings, marking the MSU base with a cross. Color coding throughout reflects onset-to-needle times: green tones indicate times under the critical 60-min 'golden hour,' while red tones denote longer times

Using historical data from previous years of EMC-supported stroke care in a middle-sized urban region in Germany, we demonstrate a positive impact of simulated MSU-based care. Longer driving times of the MSU to the scene are likely related to its set dispatch location at the hospital, while routinely the EMC vehicle closest to the scene is deployed by the dispatch center. However, the expedition of further downstream process components presumably more than counterbalances this initial delay. Even though the optimal setting for MSUs remains uncertain, examples from MSU programs conducted in various urban and rural regions worldwide demonstrate that MSU services can be successfully adapted to align with each region-specific stroke system of care, thereby providing time-efficient expertise in the field. In accordance with this assumption, our data indicate that an MSU service in Mannheim may drastically expedite process times for all CVE patients with a reduction of onset-to-needle and alarm-to-needle times in patients eligible for thrombolysis, as well as faster admission of all patients with completed emergency work-up to a stroke unit. The resulting circumvention of the hospital’s emergency department (ED) brings additional distinct advantages besides shortening care pathway times, such as a reduction in ED-associated delays, adverse events, and patients’ risks particularly in situations of crowding [8, 11] as well as more efficient use of scarce ED resources. Interestingly, MSU accelerates processes in every single case of our cohort regardless of patient location. As a consequence, in our use scenario, the MSU should be dispatched whenever possible and not only to patients beyond a certain radius around the dispatch location. Of note, a more than fivefold increase in golden-hour thrombolysis is expected, which is similar to previously reported data [3]. In Germany, the IVT rate averages at 16.3%. This is approximately twice as high as the European mean [12] and thus indicates an already well-established and well-functioning system for acute stroke care. We are optimistic that the implementation of MSU-based prehospital stroke care will improve IVT rates even further, in particular, we expect a leftward shift of the onset-to-needle time distribution, ideally below 60 min.

Despite the substantial resources required for MSU operation, economic data from various MSU sites indicate that the avoidance of disability has the potential to render the public investment in MSUs cost-effective [7]. Although MSUs have been demonstrated to effectively increase IVT rates, golden-hour thrombolysis rates, and to improve stroke outcomes, their superiority for patients requiring mechanical thrombectomy has not yet been established [9]. Potential explanations for this discrepancy include differences in MSU protocols concerning the capability of and indication for CT angiography, routes of transport to the angiography suite, and other aspects of local stroke systems of care. Future clinical research is needed to address additional measures to optimize the prehospital workflow, which has been a relatively neglected aspect of the stroke response chain. In addition to prehospital treatment with MSUs, these include the development of strategies to improve education of EMS personnel and the general public, the introduction of triage and prenotification tools, and the implementation of novel therapeutic approaches such as neuroprotective agents [2, 4].

Our results should be interpreted in the context of some limitations. First, the reliance on calculated optimal routes for MSU deployment in the simulation rather than actual travel paths, and thus the lack of variables such as traffic congestion or adverse weather conditions that could affect travel times, may affect the validity of the findings. Second, this retrospective cohort study is critically dependent on the accuracy and completeness of patient records and only included patients with complete prehospital documentation. Given the high number of patients with incomplete data, this may have introduced a bias. Finally, the study was conducted as a single-center analysis; therefore, the results may not be generalizable to other settings with different organizational structures.

While this simulation and the subsequent de novo implementation of an MSU service in the city of Mannheim are the first steps in this endeavor, whose financial feasibility has already been demonstrated [10], the meaningful expansion of the catchment area will subsequently follow. Our findings suggest that MSU utilization is generally scalable to and beneficial for novel scenarios beyond those already established, which in turn will deliver important lessons for the continuous refinement of MSU-related organizational and procedural aspects.

Funding

Open Access funding enabled and organized by Projekt DEAL. This project is part of the “RettungNetz-5G” project, funded by the German Federal Ministry for Digital and Transport under funding code 45FGU140_F.

Declarations

Conflict of interest

None of the authors report disclosures or conflicts of interest.
==== Refs
References

1. Bluhm S Schramm P Spreen-Ledebur Y Bluhm S Munte TF Eiersted MR Wolfram F van Hooff RR Wienecke T Royl G Potential effects of a mobile stroke unit on time to treatment and outcome in patients treated with thrombectomy or thrombolysis: a Danish-German cross-border analysis Eur J Neurol 2024 2 e16298 10.1111/ene.16298
Bluhm S, Schramm P, Spreen-Ledebur Y, Bluhm S, Munte TF, Eiersted MR, Wolfram F, van Hooff RR, Wienecke T, Royl G (2024) Potential effects of a mobile stroke unit on time to treatment and outcome in patients treated with thrombectomy or thrombolysis: a Danish-German cross-border analysis. Eur J Neurol 2:e1629810.1111/ene.16298
2. Chowdhury SZ Baskar PS Bhaskar S Effect of prehospital workflow optimization on treatment delays and clinical outcomes in acute ischemic stroke: a systematic review and meta-analysis Acad Emerg Med 2021 28 781 801 10.1111/acem.14204 33387368
Chowdhury SZ, Baskar PS, Bhaskar S (2021) Effect of prehospital workflow optimization on treatment delays and clinical outcomes in acute ischemic stroke: a systematic review and meta-analysis. Acad Emerg Med 28:781–80133387368 10.1111/acem.14204
3. Ebinger M Kunz A Wendt M Rozanski M Winter B Waldschmidt C Weber J Villringer K Fiebach JB Audebert HJ Effects of golden hour thrombolysis: a prehospital acute neurological treatment and optimization of medical care in stroke (PHANTOM-S) substudy JAMA Neurol 2015 72 25 30 10.1001/jamaneurol.2014.3188 25402214
Ebinger M, Kunz A, Wendt M, Rozanski M, Winter B, Waldschmidt C, Weber J, Villringer K, Fiebach JB, Audebert HJ (2015) Effects of golden hour thrombolysis: a prehospital acute neurological treatment and optimization of medical care in stroke (PHANTOM-S) substudy. JAMA Neurol 72:25–3025402214 10.1001/jamaneurol.2014.3188
4. Fassbender K Balucani C Walter S Levine SR Haass A Grotta J Streamlining of prehospital stroke management: the golden hour Lancet Neurol 2013 12 585 596 10.1016/S1474-4422(13)70100-5 23684084
Fassbender K, Balucani C, Walter S, Levine SR, Haass A, Grotta J (2013) Streamlining of prehospital stroke management: the golden hour. Lancet Neurol 12:585–59623684084 10.1016/S1474-4422(13)70100-5
5. Fassbender K Merzou F Lesmeister M Walter S Grunwald IQ Ragoschke-Schumm A Bertsch T Grotta J Impact of mobile stroke units J Neurol Neurosurg Psychiatry 2021 92 815 822 10.1136/jnnp-2020-324005 34035130
Fassbender K, Merzou F, Lesmeister M, Walter S, Grunwald IQ, Ragoschke-Schumm A, Bertsch T, Grotta J (2021) Impact of mobile stroke units. J Neurol Neurosurg Psychiatry 92:815–82234035130 10.1136/jnnp-2020-324005
6. Kim JT Fonarow GC Smith EE Reeves MJ Navalkele DD Grotta JC Grau-Sepulveda MV Hernandez AF Peterson ED Schwamm LH Saver JL Treatment with tissue plasminogen activator in the golden hour and the shape of the 4.5-hour time-benefit curve in the national united states get with the guidelines-stroke population Circulation 2017 135 128 139 10.1161/CIRCULATIONAHA.116.023336 27815374
Kim JT, Fonarow GC, Smith EE, Reeves MJ, Navalkele DD, Grotta JC, Grau-Sepulveda MV, Hernandez AF, Peterson ED, Schwamm LH, Saver JL (2017) Treatment with tissue plasminogen activator in the golden hour and the shape of the 4.5-hour time-benefit curve in the national united states get with the guidelines-stroke population. Circulation 135:128–13927815374 10.1161/CIRCULATIONAHA.116.023336
7. Oliveira Goncalves AS Rohmann JL Piccininni M Kurth T Ebinger M Endres M Freitag E Harmel P Lorenz-Meyer I Rohrpasser-Napierkowski I Busse R Audebert HJ economic evaluation of a mobile stroke unit service in Germany Ann Neurol 2023 93 942 951 10.1002/ana.26602 36637359
Oliveira Goncalves AS, Rohmann JL, Piccininni M, Kurth T, Ebinger M, Endres M, Freitag E, Harmel P, Lorenz-Meyer I, Rohrpasser-Napierkowski I, Busse R, Audebert HJ (2023) economic evaluation of a mobile stroke unit service in Germany. Ann Neurol 93:942–95136637359 10.1002/ana.26602
8. Reznek MA Murray E Youngren MN Durham NT Michael SS Door-to-imaging time for acute stroke patients is adversely affected by emergency department crowding Stroke 2017 48 49 54 10.1161/STROKEAHA.116.015131 27856953
Reznek MA, Murray E, Youngren MN, Durham NT, Michael SS (2017) Door-to-imaging time for acute stroke patients is adversely affected by emergency department crowding. Stroke 48:49–5427856953 10.1161/STROKEAHA.116.015131
9. Richards CT Oostema JA Chapman SN Mamer LE Brandler ES Alexandrov AW Czap AL Martinez-Gutierrez JC Martin-Gill C Panchal AR McMullan JT Zachrison KS Prehospital stroke care part 2: on-scene evaluation and management by emergency medical services practitioners Stroke 2023 54 1416 1425 10.1161/STROKEAHA.123.039792 36866672
Richards CT, Oostema JA, Chapman SN, Mamer LE, Brandler ES, Alexandrov AW, Czap AL, Martinez-Gutierrez JC, Martin-Gill C, Panchal AR, McMullan JT, Zachrison KS (2023) Prehospital stroke care part 2: on-scene evaluation and management by emergency medical services practitioners. Stroke 54:1416–142536866672 10.1161/STROKEAHA.123.039792
10. Rink JS Tollens F Tschalzev A Bartelt C Heinzl A Hoffmann J Schoenberg SO Marzina A Sandikci V Wiegand C Hoyer C Szabo K Establishing an MSU service in a medium-sized German urban area-clinical and economic considerations Front Neurol 2024 15 1358145 10.3389/fneur.2024.1358145 38487327
Rink JS, Tollens F, Tschalzev A, Bartelt C, Heinzl A, Hoffmann J, Schoenberg SO, Marzina A, Sandikci V, Wiegand C, Hoyer C, Szabo K (2024) Establishing an MSU service in a medium-sized German urban area-clinical and economic considerations. Front Neurol 15:135814538487327 10.3389/fneur.2024.1358145
11. Sun BC Hsia RY Weiss RE Zingmond D Liang LJ Han W McCreath H Asch SM Effect of emergency department crowding on outcomes of admitted patients Ann Emerg Med 2013 61 605–611 e606
Sun BC, Hsia RY, Weiss RE, Zingmond D, Liang LJ, Han W, McCreath H, Asch SM (2013) Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med 61(605–611):e606
12. Ungerer MN Bartig D Richter D Krogias C Hacke W Gumbinger C The evolution of acute stroke care in Germany from 2019 to 2021: analysis of nation-wide administrative datasets Neurol Res Pract 2024 6 4 10.1186/s42466-023-00297-x 38200611
Ungerer MN, Bartig D, Richter D, Krogias C, Hacke W, Gumbinger C (2024) The evolution of acute stroke care in Germany from 2019 to 2021: analysis of nation-wide administrative datasets. Neurol Res Pract 6:438200611 10.1186/s42466-023-00297-x
13. Wahlgren N Ahmed N Davalos A Ford GA Grond M Hacke W Hennerici MG Kaste M Kuelkens S Larrue V Lees KR Roine RO Soinne L Toni D Vanhooren G Thrombolysis with alteplase for acute ischaemic stroke in the safe implementation of thrombolysis in stroke-monitoring study (SITS-MOST): an observational study Lancet 2007 369 275 282 10.1016/S0140-6736(07)60149-4 17258667
Wahlgren N, Ahmed N, Davalos A, Ford GA, Grond M, Hacke W, Hennerici MG, Kaste M, Kuelkens S, Larrue V, Lees KR, Roine RO, Soinne L, Toni D, Vanhooren G (2007) Thrombolysis with alteplase for acute ischaemic stroke in the safe implementation of thrombolysis in stroke-monitoring study (SITS-MOST): an observational study. Lancet 369:275–28217258667 10.1016/S0140-6736(07)60149-4
14. Walter S Audebert HJ Katsanos AH Larsen K Sacco S Steiner T Turc G Tsivgoulis G European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management Eur Stroke J 2022 7 27 29 10.1177/23969873221079413
Walter S, Audebert HJ, Katsanos AH, Larsen K, Sacco S, Steiner T, Turc G, Tsivgoulis G (2022) European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management. Eur Stroke J 7:27–2910.1177/23969873221079413
15. Zandbergen PA Ensuring confidentiality of geocoded health data: assessing geographic masking strategies for individual-level data Adv Med 2014 2014 567049 10.1155/2014/567049 26556417
Zandbergen PA (2014) Ensuring confidentiality of geocoded health data: assessing geographic masking strategies for individual-level data. Adv Med 2014:56704926556417 10.1155/2014/567049
