Emergency Medical Services dispatcher recognition of stroke: A systematic review

Wenstrup, Jonathan; Hestoy, Bartal Hofgaard; Sagar, Malini Vendela; Blomberg, Stig Nikolaj Fasmer; Christensen, Hanne; Christensen, Helle Collatz; Kruuse, Christina

doi:10.1177/23969873231223339

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…Both regions have about the same numbers of thrombolysis cases per year (∼130) and thrombectomy cases per year (∼70). As a point estimation it was assumed that the MSU can reach 40% of these cases (55 thrombolysis cases, 30 thrombectomy cases) [ 20 ]. However, since yearly numbers, spatial distribution and the validity of MSU dispatch can vary, a variation of thrombolysis cases (20–80/year) and thrombectomy cases (10–50/year) was modelled.…”

Section: Methodsmentioning

confidence: 99%

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

Bluhm,

Schramm,

Spreen‐Ledebur

et al. 2024

Euro J of Neurology

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Background and purposeA mobile stroke unit (MSU) reduces delays in stroke treatment by allowing thrombolysis on board and avoiding secondary transports. Due to the beneficial effect in comparison to conventional emergency medical services, current guidelines recommend regional evaluation of MSU implementation.MethodsIn a descriptive study, current pathways of patients requiring a secondary transport for mechanical thrombectomy were reconstructed from individual patient records within a Danish (n = 122) and an adjacent German region (n = 80). Relevant timestamps included arrival times (on site, primary hospital, thrombectomy centre) as well as the initiation of acute therapy. An optimal MSU location for each region was determined. The resulting time saving was translated into averted disability‐adjusted life years (DALYs).ResultsFor each region, the optimal MSU location required a median driving time of 35 min to a stroke patient. Time savings in the German region (median [Q1; Q3]) were 7 min (−15; 31) for thrombolysis and 35 min (15; 61) for thrombectomy. In the Danish region, the corresponding time savings were 20 min (8; 30) and 43 min (25; 66). Assuming 28 thrombectomy cases and 52 thrombolysis cases this would translate to 9.4 averted DALYs per year justifying an annual net MSU budget of $0.8M purchasing power parity dollars (PPP‐$) in the German region. In the Danish region, the MSU would avert 17.7 DALYs, justifying an annual net budget of PPP‐$1.7M.ConclusionThe effects of an MSU can be calculated from individual patient pathways and reflect differences in the hospital infrastructure between Denmark and Germany.

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Section: Methodsmentioning

confidence: 99%

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

Bluhm,

Schramm,

Spreen‐Ledebur

et al. 2024

Euro J of Neurology

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Stroke recognition in medical emergency calls: A novel sensitivity definition as a basis for developing artificial intelligence decision support

Iversen,

Ihle-Hansen,

Halle

et al. 2024

Preprint

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Background: The sensitivity of emergency medical communication centers (EMCC) for stroke detection varies widely. However, few studies offer detailed insights into the entirety of prehospital pathways in patients with stroke. Therefore, this study aimed to lay the foundation for artificial intelligence (AI) decision support tools in EMCCs by exploring their ability to detect strokes in medical emergency calls, describe a novel method for stroke sensitivity calculation in the EMCC, and identify factors associated with stroke recognition during a call. Methods: In total, 1,164 patients with stroke in the catchment area of Bergen EMCC in 2018 and 2019 were included, and a dataset from the EMCC was established manually and linked with data from the Norwegian Stroke Registry (NSR) for analysis. Descriptive statistics, Chi-square test for categorical variables, Mann?Whitney U test for continuous variables, and multivariate logistic regression (LR) were performed on data obtained from patients primarily assessed by EMCC (n=838). Results: Using a novel method, we found a stroke detection sensitivity of 76.8% in our study, compared to the 63.4% when using the traditional sensitivity detection method. LR analysis showed a positive association between stroke suspicion and ischemic strokes (odds ratio [OR]=0.317 [0.209?0.481]; p<0,001, with ischemic stroke as the reference) and wake-up strokes (OR=1.716 [1.110?2.653]; p=0.015). Among the NSR symptoms, only aphasia/dysarthria was positively associated with stroke suspicion (OR=1.600 [1.087?2.353]; p=0.017), while leg paresis (OR=0.609 [0.390?0.953]; p=0.009) and vertigo (OR=0.376 [0.204?0.694]; p=0.002) were negatively associated. Conclusions: This study introduced a novel and more accurate method for calculating EMCC stroke sensitivity, which is relevant for developing decision support tools, such as AI. Moreover, we identified factors of particular interest for future EMCC research that are relevant to developing AI decision-support tools.

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Factors affecting emergency medical dispatchers decision making in stroke calls – a qualitative study

Jamtli,

Svendsen,

Jørgensen

et al. 2024

BMC Emerg Med

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Objectives Emergency Medical Communication Centers (EMCC) have a key role in the prehospital chain-of-stroke-survival by recognizing stroke patients and reducing prehospital delay. However, studies on EMCC stroke recognition report both substantial undertriage and overtriage. Since mis-triage at the EMCC challenges the whole chain-of-stroke-survival, by occupying limited resources for non-stroke patients or failing to recognize the true stroke patients, there is a need to achieve a more comprehensive understanding of the dispatchers’ routines and experiences. The aim of this study was to explore factors affecting EMCC dispatcher’s decision-making in stroke calls. Materials and methods A qualitative exploratory study, based on individual semi-structured interviews of 15 medical dispatchers from EMCC Oslo, Norway. Interviews were conducted during August and October 2022 and analyzed using the principles of thematic analysis. Results We identified four themes: [1] Pronounced stroke symptoms are easy to identify [2]. Non-specific neurological symptoms raise suspicion of acute stroke but are difficult to differentiate from other medical conditions [3]. Consistent use of the Criteria Based Dispatch (CBD) protocol may increase EMCC overtriage [4]. Contextual conditions at EMCC can affect dispatchers’ decision-making process and the ability for experiential learning. Conclusions Medical dispatchers at the EMCC perceive vague and non-specific stroke symptoms, such as dizziness, confusion or altered behaviour, challenging to differentiate from symptoms of other less time-critical medical conditions. They also perceive the current CBD protocol in use as less supportive in assessing such symptoms. High workload and strict EMCC response time interval requirements hinder the gathering of essential patient information and the ability to seek guidance in cases of doubt, potentially exacerbating both EMCC undertriage and overtriage. The absence of feedback loops and other strategies for experiential learning in the EMCC hampers the medical dispatcher’s ability to evaluate their own assessments and improve dispatch accuracy.

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Emergency Medical Services dispatcher recognition of stroke: A systematic review

Cited by 3 publications

References 40 publications

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

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

Stroke recognition in medical emergency calls: A novel sensitivity definition as a basis for developing artificial intelligence decision support

Factors affecting emergency medical dispatchers decision making in stroke calls – a qualitative study

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