Targets for improving dispatcher identification of acute stroke

Mattila, Olli S.; Puolakka, Tuukka; Ritvonen, Juhani; Pihlasviita, Saana; Harve, Heini; Alanen, Ari; Sibolt, Gerli; Curtze, Sami; Strbian, Daniel; Pystynen, Mikko; Tatlısumak, Turgut; Kuisma, Markku; Lindsberg, Perttu J.

doi:10.1177/1747493019830315

Cited by 13 publications

(13 citation statements)

References 16 publications

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“…The medical dispatchers were more likely to activate stroke protocols and there was a higher likelihood of thrombolysis during the admission [29]. Another recent study identified that focussing on recognizing FAST symptoms, speech disturbances and a fall at onset improved the identification of stroke by dispatchers [30]. An important initiative was recently developed by the American Heart Association to improve dispatch recognition of acute stroke.…”

Section: Pre-hospital Dispatch Evaluation Of Stroke Mimicsmentioning

confidence: 99%

Stroke mimics: incidence, aetiology, clinical features and treatment

et al. 2021

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Mimics account for almost half of hospital admissions for suspected stroke. Stroke mimics may present as a functional (conversion) disorder or may be part of the symptomatology of a neurological or medical disorder. While many underlying conditions can be recognized rapidly by careful assessment, a significant proportion of patients unfortunately still receive thrombolysis and admission to a high-intensity stroke unit with inherent risks and unnecessary costs. Accurate diagnosis is important as recurrent presentations may be common in many disorders. A non-contrast CT is not sufficient to make a diagnosis of acute stroke as the test may be normal very early following an acute stroke. Multi-modal CT or magnetic resonance imaging (MRI) may be helpful to confirm an acute ischaemic stroke and are necessary if stroke mimics are suspected. Treatment in neurological and medical mimics results in prompt resolution of the symptoms. Treatment of functional disorders can be challenging and is often incomplete and requires early psychiatric intervention.

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Section: Pre-hospital Dispatch Evaluation Of Stroke Mimicsmentioning

confidence: 99%

Stroke mimics: incidence, aetiology, clinical features and treatment

et al. 2021

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“…The question arises, whether other options could increase stroke detection by EMS call-takers. Past research analysed the influence of educational training modules as well as stroke recognition scales and protocols, such as the “FAST”-Tool [ 17 , 73 – 75 ]. However, Oostema et al [ 73 ] reported, that the increase in stroke recognition after an educational intervention was limited to three months and might increase the rate of false positive stroke detection due to a higher sensibility to symptoms related to stroke [ 73 , 76 ].…”

Section: Discussionmentioning

confidence: 99%

“…Blomberg et al [ 77 ] reported a lack of compliance with the suggestions of CORTI AI by the EMDs, which resulted in no increase of OHCA detection within the EMS Copenhagen. Considering the results of educational interventions, the introduction of an ASR for strokes at the EMS could be accompanied by, for example educational interventions addressing challenges in the uptake of the ASR, in order to ensure the effect of the ASR [ 73 – 75 , 77 ]. The European Institute of Innovation and Technology (EIT) Health states that to improve the uptake and effect of AI in healthcare, investments in the education of healthcare workers to ensure digital literacy, the exchange of best practice in the field of AI in healthcare throughout the EU and improvement of collaboration is essential [ 78 ].…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence in Emergency Medical Services dispatching: assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point

Scholz

Collatz-Christensen

Blomberg

et al. 2022

Scand J Trauma Resusc Emerg Med

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Background and purpose Stroke recognition at the Emergency Medical Services (EMS) impacts the stroke treatment and thus the related health outcome. At the EMS Copenhagen 66.2% of strokes are detected by the Emergency Medical Dispatcher (EMD) and in Denmark approximately 50% of stroke patients arrive at the hospital within the time-to-treatment. An automatic speech recognition software (ASR) can increase the recognition of Out-of-Hospital cardiac arrest (OHCA) at the EMS by 16%. This research aims to analyse the potential impact an ASR could have on stroke recognition at the EMS Copenhagen and the related treatment. Methods Stroke patient data (n = 9049) from the years 2016–2018 were analysed retrospectively, regarding correlations between stroke detection at the EMS and stroke specific, as well as personal characteristics such as stroke type, sex, age, weekday, time of day, year, EMS number contacted, and treatment. The possible increase in stroke detection through an ASR and the effect on stroke treatment was calculated based on the impact of an existing ASR to detect OHCA from CORTI AI. Results The Chi-Square test with the respective post-hoc test identified a negative correlation between stroke detection and females, the 1813-Medical Helpline, as well as weekends, and a positive correlation between stroke detection and treatment and thrombolysis. While the association analysis showed a moderate correlation between stroke detection and treatment the correlation to the other treatment options was weak or very weak. A potential increase in stroke detection to 61.19% with an ASR and hence an increase of thrombolysis by 5% in stroke patients calling within time-to-treatment was predicted. Conclusions An ASR can potentially improve stroke recognition by EMDs and subsequent stroke treatment at the EMS Copenhagen. Based on the analysis results improvement of stroke recognition is particularly relevant for females, younger stroke patients, calls received through the 1813-Medical Helpline, and on weekends. Trial registration This study was registered at the Danish Data Protection Agency (PVH-2014-002) and the Danish Patient Safety Authority (R-21013122).

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“…A stroke diagnosis is highly probable when the caller spontaneously mentions the word ‘stroke’ [ 22 ]. Studies have repeatedly called attention to the fact that false negative dispatch codes in stroke patients are often due to initial words mentioned by the caller in an emergency call such as ‘fall’, ‘sick person’ and ‘unconsciousness/confusion’ [ 22 , 23 ]. We also believe that this explains why, in our study, the CED question found only a minority of patients being in need of MT.…”

Section: Discussionmentioning

confidence: 99%

Emergency medical dispatchers’ ability to identify large vessel occlusion stroke during emergency calls

Vuorinen

Ollikainen

Ketola

et al. 2021

Scand J Trauma Resusc Emerg Med

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Background In acute ischemic stroke, conjugated eye deviation (CED) is an evident sign of cortical ischemia and large vessel occlusion (LVO). We aimed to determine if an emergency dispatcher can recognise LVO stroke during an emergency call by asking the caller a binary question regarding whether the patient’s head or gaze is away from the side of the hemiparesis or not. Further, we investigated if the paramedics can confirm this sign at the scene. In the group of positive CED answers to the emergency dispatcher, we investigated what diagnoses these patients received at the emergency department (ED). Among all patients brought to ED and subsequently treated with mechanical thrombectomy (MT) we tracked the proportion of patients with a positive CED answer during the emergency call. Methods We collected data on all stroke dispatches in the city of Tampere, Finland, from 13 February 2019 to 31 October 2020. We then reviewed all patient records from cases where the dispatcher had marked ‘yes’ to the question regarding patient CED in the computer-aided emergency response system. We also viewed all emergency department admissions to see how many patients in total were treated with MT during the period studied. Results Out of 1913 dispatches, we found 81 cases (4%) in which the caller had verified CED during the emergency call. Twenty-four of these patients were diagnosed with acute ischemic stroke. Paramedics confirmed CED in only 9 (11%) of these 81 patients. Two patients with positive CED answers during the emergency call and 19 other patients brought to the emergency department were treated with MT. Conclusion A small minority of stroke dispatches include a positive answer to the CED question but paramedics rarely confirm the emergency medical dispatcher’s suspicion of CED as a sign of LVO. Few patients in need of MT can be found this way. Stroke dispatch protocol with a CED question needs intensive implementation.

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Targets for improving dispatcher identification of acute stroke

Cited by 13 publications

References 16 publications

Stroke mimics: incidence, aetiology, clinical features and treatment

Stroke mimics: incidence, aetiology, clinical features and treatment

Artificial intelligence in Emergency Medical Services dispatching: assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point

Emergency medical dispatchers’ ability to identify large vessel occlusion stroke during emergency calls

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