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Simulation training for emergency teams to manage acute ischemic stroke by telemedicine

View Article: PubMed Central - PubMed

ABSTRACT

Telemedicine contributes to initiating early intravenous recombinant tissue plasminogen activator (rt-PA) treatment for patients with acute cerebral infarction in areas without a stroke unit. However, the experience and skills of the emergency teams in the spokes to prepare patients and administer rt-PA treatment are ill-defined. Improving these skills could vastly improve management of acute stroke by telemedicine. We developed a medical simulation training model for emergency teams to perform intravenous rt-PA treatment in a telestroke system.

From February 2013 to May 2015, 225 learners from 6 emergency teams included in the telestroke system “Virtuall”—in Lorrain (northeastern France)—received a standardized medical simulation training module to perform rt-PA treatment. All learners were assessed with the same pretraining and posttraining test consisting of 52 items. The percentage of right answers was determined for every learner before and after training.

Median percentages of right answers were significantly higher in the posttraining test overall (82 ± 10 vs. 59 ± 13% pretraining; P < 0.001), but also in all professional subgroups: physicians (88 ± 8 vs. 67 ± 12%; P < 0.001), paramedical staff (80 ± 9 vs. 54 ± 12%; P < 0.001), nurses (80 ± 8 vs. 54 ± 12%; P < 0.001), and auxiliary nurses (76 ± 17 vs. 37 ± 15%; P = 0.002).

We describe for the first time a training model for emergency teams in a telestroke system. We demonstrate significant gain in knowledge for all groups of healthcare professionals. This simulation model could be applied in any medical simulation center and form the basis of a standardized training program of spokes in a telestroke system.

No MeSH data available.


Results of pretraining and posttraining tests in overall learners and in different professional subgroups. Tukey's box-and-whisker plots, box limits: IQR, middle line: median, vertical lines: adjacent values (first quartile—1.5 IQR; third quartile + 1.5 IQR), dots: outliers, white boxes: pretests, gray boxes: posttests, significant difference between pretraining and posttraining test determined with Wilcoxon signed-rank test, ∗∗P < 0.01, ∗∗∗P < 0.001. Correct answer percentages for overall learners (A), physicians (B), paramedical staff (C), nurses (D), paramedical subgroup including auxiliary nurses and radiology technicians (E), and auxiliary nurses (F).
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Figure 2: Results of pretraining and posttraining tests in overall learners and in different professional subgroups. Tukey's box-and-whisker plots, box limits: IQR, middle line: median, vertical lines: adjacent values (first quartile—1.5 IQR; third quartile + 1.5 IQR), dots: outliers, white boxes: pretests, gray boxes: posttests, significant difference between pretraining and posttraining test determined with Wilcoxon signed-rank test, ∗∗P < 0.01, ∗∗∗P < 0.001. Correct answer percentages for overall learners (A), physicians (B), paramedical staff (C), nurses (D), paramedical subgroup including auxiliary nurses and radiology technicians (E), and auxiliary nurses (F).

Mentions: From February 2013 to May 2015, 225 learners from emergency teams including 73 physicians, 139 nurses, 9 auxiliary nurses, and 4 radiology technicians underwent the training in sixteen sessions. Pretraining test scores were significantly higher in the physician subgroup than in the paramedical subgroup (Fig. 1). Overall, the learners median percentage of correct answers significantly increased from 59 ± 13% for the pretraining test to 82 ± 10% in posttraining test (P < 0.001). This was also observed in the physician subgroup (67 ± 12 vs. 88 ± 8%; P < 0.001), paramedical staff subgroup (54 ± 12 vs. 80 ± 9%; P < 0.001), nurse subgroup (54 ± 12 vs. 80 ± 8%; P < 0.001), auxiliary nurse/radiological technician subgroup (51 ± 18 vs. 78 ± 15%; P < 0.001), and auxiliary nurse subgroup (37 ± 15 vs. 76 ± 17%; P = 0.002; Fig. 2). Posttraining test scores remained significantly higher in the medical subgroup compared with the paramedical subgroup except for knowledge about patient management where the scores were similar (Fig. 1). The mean rate of overall correct answers increased by 21% in the posttraining test, ranging from 19% in the physician subgroup up to 34% in the auxiliary nurse subgroup (Fig. 3). The improvement in scores was significantly higher (P < 0.001) in the paramedical subgroup than in the physician subgroup both overall and for the subcategories except for knowledge about telestroke and rt-PA treatment (Fig. 3). Feedback was excellent with more than 95% of learners rating the training 5/5 (data not shown).


Simulation training for emergency teams to manage acute ischemic stroke by telemedicine
Results of pretraining and posttraining tests in overall learners and in different professional subgroups. Tukey's box-and-whisker plots, box limits: IQR, middle line: median, vertical lines: adjacent values (first quartile—1.5 IQR; third quartile + 1.5 IQR), dots: outliers, white boxes: pretests, gray boxes: posttests, significant difference between pretraining and posttraining test determined with Wilcoxon signed-rank test, ∗∗P < 0.01, ∗∗∗P < 0.001. Correct answer percentages for overall learners (A), physicians (B), paramedical staff (C), nurses (D), paramedical subgroup including auxiliary nurses and radiology technicians (E), and auxiliary nurses (F).
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4998489&req=5

Figure 2: Results of pretraining and posttraining tests in overall learners and in different professional subgroups. Tukey's box-and-whisker plots, box limits: IQR, middle line: median, vertical lines: adjacent values (first quartile—1.5 IQR; third quartile + 1.5 IQR), dots: outliers, white boxes: pretests, gray boxes: posttests, significant difference between pretraining and posttraining test determined with Wilcoxon signed-rank test, ∗∗P < 0.01, ∗∗∗P < 0.001. Correct answer percentages for overall learners (A), physicians (B), paramedical staff (C), nurses (D), paramedical subgroup including auxiliary nurses and radiology technicians (E), and auxiliary nurses (F).
Mentions: From February 2013 to May 2015, 225 learners from emergency teams including 73 physicians, 139 nurses, 9 auxiliary nurses, and 4 radiology technicians underwent the training in sixteen sessions. Pretraining test scores were significantly higher in the physician subgroup than in the paramedical subgroup (Fig. 1). Overall, the learners median percentage of correct answers significantly increased from 59 ± 13% for the pretraining test to 82 ± 10% in posttraining test (P < 0.001). This was also observed in the physician subgroup (67 ± 12 vs. 88 ± 8%; P < 0.001), paramedical staff subgroup (54 ± 12 vs. 80 ± 9%; P < 0.001), nurse subgroup (54 ± 12 vs. 80 ± 8%; P < 0.001), auxiliary nurse/radiological technician subgroup (51 ± 18 vs. 78 ± 15%; P < 0.001), and auxiliary nurse subgroup (37 ± 15 vs. 76 ± 17%; P = 0.002; Fig. 2). Posttraining test scores remained significantly higher in the medical subgroup compared with the paramedical subgroup except for knowledge about patient management where the scores were similar (Fig. 1). The mean rate of overall correct answers increased by 21% in the posttraining test, ranging from 19% in the physician subgroup up to 34% in the auxiliary nurse subgroup (Fig. 3). The improvement in scores was significantly higher (P < 0.001) in the paramedical subgroup than in the physician subgroup both overall and for the subcategories except for knowledge about telestroke and rt-PA treatment (Fig. 3). Feedback was excellent with more than 95% of learners rating the training 5/5 (data not shown).

View Article: PubMed Central - PubMed

ABSTRACT

Telemedicine contributes to initiating early intravenous recombinant tissue plasminogen activator (rt-PA) treatment for patients with acute cerebral infarction in areas without a stroke unit. However, the experience and skills of the emergency teams in the spokes to prepare patients and administer rt-PA treatment are ill-defined. Improving these skills could vastly improve management of acute stroke by telemedicine. We developed a medical simulation training model for emergency teams to perform intravenous rt-PA treatment in a telestroke system.

From February 2013 to May 2015, 225 learners from 6 emergency teams included in the telestroke system &ldquo;Virtuall&rdquo;&mdash;in Lorrain (northeastern France)&mdash;received a standardized medical simulation training module to perform rt-PA treatment. All learners were assessed with the same pretraining and posttraining test consisting of 52 items. The percentage of right answers was determined for every learner before and after training.

Median percentages of right answers were significantly higher in the posttraining test overall (82&#8202;&plusmn;&#8202;10 vs. 59&#8202;&plusmn;&#8202;13% pretraining; P&#8202;&lt;&#8202;0.001), but also in all professional subgroups: physicians (88&#8202;&plusmn;&#8202;8 vs. 67&#8202;&plusmn;&#8202;12%; P&#8202;&lt;&#8202;0.001), paramedical staff (80&#8202;&plusmn;&#8202;9 vs. 54&#8202;&plusmn;&#8202;12%; P&#8202;&lt;&#8202;0.001), nurses (80&#8202;&plusmn;&#8202;8 vs. 54&#8202;&plusmn;&#8202;12%; P&#8202;&lt;&#8202;0.001), and auxiliary nurses (76&#8202;&plusmn;&#8202;17 vs. 37&#8202;&plusmn;&#8202;15%; P = 0.002).

We describe for the first time a training model for emergency teams in a telestroke system. We demonstrate significant gain in knowledge for all groups of healthcare professionals. This simulation model could be applied in any medical simulation center and form the basis of a standardized training program of spokes in a telestroke system.

No MeSH data available.