Objective: Endotracheal intubation (ETI) is a life-saving emergency procedure, but it is a complex skill that is difficult to teach. Recent studies have shown that video laryngoscopy is effective in teaching ETI to le...Objective: Endotracheal intubation (ETI) is a life-saving emergency procedure, but it is a complex skill that is difficult to teach. Recent studies have shown that video laryngoscopy is effective in teaching ETI to learners at various levels of medical expertise;however, it has proven to be costly and provides images of inconsistent quality. In this educational proof of concept feasibility convenience sample pilot study, we aim to explore and compare the effectiveness of using modified Google Glass? (GG) and GoPro? (GP) technologies to visualize and teach ETI to critical care physicians in the austere medical environment of a low-income country. We propose, based on our findings, that this inexpensive technology could teach lifesaving ETI to pre-hospital providers in the austere medical environment, medical students, rural emergency physicians, critical care physicians in low-income countries, far forward military medical providers, and other learners. Methods: A case series of twenty-five patients, five in the United States (US) at Memorial Hospital in South Bend, IN and twenty at Saint Luc’s Hospital in Port Au Prince, Haiti, is presented. These patients were collected from November 1st 2015 through February 1st of 2016. The anesthesiologist and the emergency physicians in the United States utilized GG to intubate five patients in the US prior to the twenty patients intubated during two separate trips to Haiti. On the two separate trips to Haiti, the GG was trialed and modified to obtain better exposure. These adaptations resulted in the final collection of twenty patients studied with the adapted GG system and GP. Physicians graded airway visualization based on LEMON and Cormack-Lehane scores. Previously published parameters for the assessment of failed intubation risk and passage of the cords were used as data points for analysis using a Likert-Scale analysis for each parameter. The data were analyzed by averages of Likert-Scale scoring with their respective standard deviations. Results: The results show that the GP is superior to GG for assessing the LEMON scoring system until visualization of the oropharynx, while the GG is markedly superior for calculation of Cormack-Lehane score (cord visualization) and passing of the endotracheal tube. Conclusion: A review of the twenty-five cases demonstrates that while GP allows for better visualization for the parameters that require a wider view of the patient, the modified GG allows for superior visualization in the parameters that require a more focused view of the cords. GG can serve as an effective educational tool in the ICU for physicians and other providers in the austere medical environment who require effective ETI training. In addition, we propose that these techniques can serve as an inexpensive yet effective means of teaching hands on endotracheal intubation skills to learners of varying levels of clinical experience.展开更多
Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts...Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical eases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learning environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastrneture is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool （ICBFLT）, which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students＇ and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students＇ academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.展开更多
文摘Objective: Endotracheal intubation (ETI) is a life-saving emergency procedure, but it is a complex skill that is difficult to teach. Recent studies have shown that video laryngoscopy is effective in teaching ETI to learners at various levels of medical expertise;however, it has proven to be costly and provides images of inconsistent quality. In this educational proof of concept feasibility convenience sample pilot study, we aim to explore and compare the effectiveness of using modified Google Glass? (GG) and GoPro? (GP) technologies to visualize and teach ETI to critical care physicians in the austere medical environment of a low-income country. We propose, based on our findings, that this inexpensive technology could teach lifesaving ETI to pre-hospital providers in the austere medical environment, medical students, rural emergency physicians, critical care physicians in low-income countries, far forward military medical providers, and other learners. Methods: A case series of twenty-five patients, five in the United States (US) at Memorial Hospital in South Bend, IN and twenty at Saint Luc’s Hospital in Port Au Prince, Haiti, is presented. These patients were collected from November 1st 2015 through February 1st of 2016. The anesthesiologist and the emergency physicians in the United States utilized GG to intubate five patients in the US prior to the twenty patients intubated during two separate trips to Haiti. On the two separate trips to Haiti, the GG was trialed and modified to obtain better exposure. These adaptations resulted in the final collection of twenty patients studied with the adapted GG system and GP. Physicians graded airway visualization based on LEMON and Cormack-Lehane scores. Previously published parameters for the assessment of failed intubation risk and passage of the cords were used as data points for analysis using a Likert-Scale analysis for each parameter. The data were analyzed by averages of Likert-Scale scoring with their respective standard deviations. Results: The results show that the GP is superior to GG for assessing the LEMON scoring system until visualization of the oropharynx, while the GG is markedly superior for calculation of Cormack-Lehane score (cord visualization) and passing of the endotracheal tube. Conclusion: A review of the twenty-five cases demonstrates that while GP allows for better visualization for the parameters that require a wider view of the patient, the modified GG allows for superior visualization in the parameters that require a more focused view of the cords. GG can serve as an effective educational tool in the ICU for physicians and other providers in the austere medical environment who require effective ETI training. In addition, we propose that these techniques can serve as an inexpensive yet effective means of teaching hands on endotracheal intubation skills to learners of varying levels of clinical experience.
文摘Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical eases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learning environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastrneture is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool （ICBFLT）, which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students＇ and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students＇ academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.
