Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Summary

Every min counts in acute stroke care. This guide shows how to establish a Stroke Team algorithm and enhance its performance with regular simulation training. The principles of Crew Resource Management (CRM) facilitate a straight workflow, reduce door-to-needle times and increase staff satisfaction.

Abstract

Time is of the essence when caring for an acute stroke patient. The ultimate goal is to restore blood flow to the ischemic brain. This can be achieved by either thrombolysis with recombinant tissue-plasminogen activator (rt-PA), the standard therapy for stroke patients who present within the first hours of symptom onset without contraindications, or by an endovascular approach, if a proximal brain vessel occlusion is detected. As the efficacy of both therapies declines over time, every minute saved along the way will improve the patient's outcome.

This critical situation requires thorough work and precise communication with the patient, the family and colleagues from different professions to acquire all relevant information and reach the right decision while carefully monitoring the patient. This is a high fidelity situation. In nonmedical high-fidelity environments such as aviation, Crew Resource Management (CRM) is used to enhance safety and team efficiency.

This guide shows how a Stroke Team algorithm, which is transferable to other hospital settings, was established and how regular simulation-based trainings were performed. It requires determination and endurance to maintain these time-consuming simulation trainings on a regular basis over the course of time. However, the resulting improvement of team spirit and excellent door-to-needle times will benefit both the patients and the work environment in any hospital.

A dedicated Stroke Team of 7 persons who are notified 24/7 by a collective call via speed dial and run a binding algorithm that takes approximately 20 min, was established. To train everybody involved in this algorithm, a simulation-based team training for all new Stroke Team members was conceived and conducted at monthly intervals. This led to a relevant and sustained reduction of the mean door-to-needle time to 25 min, and enhanced the feeling of stroke readiness especially in junior doctors and nurses.

Introduction

The efficacy of thrombolysis with recombinant tissue-plasminogen activator (rt-PA) for acute ischemic stroke is highly time-dependent and decreases over time even in the therapeutic time window of 4.5 hr¹. The same has been shown for endovascular stroke therapy². The additional mechanical recanalization after thrombolysis has been shown to be highly effective in improving outcomes of patients with severe stroke due to Large Vessel Occlusion (LVO)³. This new therapy adds to the complexity and interdisciplinarity of acute stroke care since endovascular therapies require a neurointerventionalist, an anesthetist or neurointensivist and in ....

Protocol

1. Prenotification of the ED

1. After the ED nurse hears an alarm, go to the computer screen immediately.
2. Check the information above the incoming patient via the online platform (e.g., IVENA Ehealth)⁷. Find that the system announces a 66 year-old male patient with the tentative diagnosis of a stroke within the time window (stroke <6 hr) with the estimated time of arrival.
3. Pre-notify the resident of the SU via phone call.
4. As the SU resident hears the mobile phone ringing, have the SU resident take the phone call. Have the SU resident go to the ED at the estimated time of arrival.

Results

Effect on the door-to-needle times and thrombolysis rate

The implementation of the Stroke Team algorithm in 2012 accompanied by regular simulation-based Stroke Team trainings led to a relevant increase in the patients treated with a door-to-needle time below 30 and 60 min and to an increase in our thrombolysis rate.

Discussion

A binding stroke team algorithm and regular simulation-based stroke team trainings can lead to a long-term reduction of the door-to-needle time as the key benchmark process time for acute stroke treatment. Excellent examples of a set of measures that improve the acute stroke work flow, which also inspired our algorithm, have been described by the Helsinki group^14,15. Another very innovative approach to shorten the time interval from symptom onset to thrombolysis are mobile stroke units such as the pioneering S.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Drug
Alteplase (rtPA)	Boehringer Ingelheim, Ingelheim am Rhein, Germany		A licensed drug, which has proven effectiveness for acute ischemic stroke
Urapidil 50 mg/10 ml	Takeda Pharma, Berlin, Germany		A licensed drug, antihypertensive
Granisetron 3 mg/ml	Hameln Pharma, Hameln, Germany		A licensed drug, antiemetic
Lorazepam 2 mg/ml	Pfizer, Berlin, Germany		A licensed drug, sedative
Iopromid 300 mg/ml	Bayer Vital GmbH, Leverkusen, Germany		A licensed drug, non-ionic contrast agent for Computed Tomography (CT)
Name	Company	Catalog Number	Comments
Device
S-Monovette citrate 3 ml	Sarstedt, Nürnbrecht, Germany		For blood collection for coagulation assays
S-Monovette EDTA 1.6 ml	Sarstedt, Nürnbrecht, Germany		For blood collection for hematology assays
S-Monovette lithium heparinate 7.5 ml	Sarstedt, Nürnbrecht, Germany		For blood collection for clinical chemistry assays
ACL Top 500	Instrumentation Laboratory, Kirchheim, Germany		Automated hemostasis analyzer
Sysmex XE 2100	Sysmex Corporation, Norderstedt, Germany		Automated hematology analyzser
Cobas 6000	Roche Diagnostics, Mannheim, Germany		Automated clinical chemistry analyzser
Resusci Anne Skillreporter	Laerdal, Stavanger, Norway		Remote-controlled manikin
Ingenuity 128	Philips, Hamburg, Germany		CT-scanner
MEDRAD Stellant	Bayer Radiology, Leverkusen Germany		Contrast agent delivery system
Universal 320 R	Hettich, Tuttlingen, Germany		Centrifuge
Perfusor fm	Braun, Melsungen, Germany		Infusion pump
Infinity Gamma	Dräger, Hamburg, Germany		Monitor
Ivena ehealth	mainis IT-Service GmbH, Offenbach, Germany		Online prenotification platform
Braun ThermoScan PRO 4000	Welch Allyn, Hechingen, Germany		Ear thermometer