Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course
Objective: In addition to high-quality chest compression, parameters of resuscitation efficiency such as early chest compression, early defibrillation, and decreased hands-off time are also vital in the Advanced Cardiac Life Support (ACLS) protocol. However, because of limited time and equipment in...
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| Format: | Article |
| Language: | English |
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Wolters Kluwer Medknow Publications
2018-01-01
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| Series: | Tzu Chi Medical Journal |
| Subjects: | |
| Online Access: | http://www.tcmjmed.com/article.asp?issn=1016-3190;year=2018;volume=30;issue=3;spage=165;epage=168;aulast=Lee |
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| _version_ | 1849695495594704896 |
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| author | Chao-Hsiung Lee Ming-Yuan Huang Yi-Kung Lee Chen-Yang Hsu Yung-Cheng Su |
| author_facet | Chao-Hsiung Lee Ming-Yuan Huang Yi-Kung Lee Chen-Yang Hsu Yung-Cheng Su |
| author_sort | Chao-Hsiung Lee |
| collection | DOAJ |
| description | Objective: In addition to high-quality chest compression, parameters of resuscitation efficiency such as early chest compression, early defibrillation, and decreased hands-off time are also vital in the Advanced Cardiac Life Support (ACLS) protocol. However, because of limited time and equipment in ACLS courses, efficiency of performance is difficult to evaluate. Materials and Methods: A free, easy-to-use iOS and Android app (CodeTracer®) was developed for real-time recording of cardiopulmonary resuscitation (CPR) performance. Interventions performed during resuscitation were set up as buttons. When the simulated scenario in the ACLS course began, instructors recorded every intervention and the team performed by pushing the appropriate buttons. When the scenario ended, the CodeTracer® automatically computed parameters, including the percentage of no-flow time, time to initiating CPR, and time to initiating defibrillation and also generated a graphic log for later discussion. Results: A total of 76 resuscitation episodes were recorded, 27 in the practice scenarios and 49 in the final Megacode simulations. After the course, the average percentage of no-flow time decreased 5.79%, time to initiating CPR decreased 3.05 s, and time to initiating defibrillation decreased up to 20.27 s. Of note, physicians as leaders seem to have better performance after the ACLS course than before, but the results were insignificant except for the percentage of no-flow time. Conclusions: CodeTracer® can record and calculate objective parameters for resuscitation performance in ACLS courses and can assist instructors in disseminating important concepts to participants. It can be a useful tool in ACLS courses. |
| format | Article |
| id | doaj-art-9d44a3c68f744072a4ce8ea7eadfc6e6 |
| institution | DOAJ |
| issn | 1016-3190 2223-8956 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Tzu Chi Medical Journal |
| spelling | doaj-art-9d44a3c68f744072a4ce8ea7eadfc6e62025-08-20T03:19:46ZengWolters Kluwer Medknow PublicationsTzu Chi Medical Journal1016-31902223-89562018-01-0130316516810.4103/tcmj.tcmj_103_17Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support courseChao-Hsiung LeeMing-Yuan HuangYi-Kung LeeChen-Yang HsuYung-Cheng SuObjective: In addition to high-quality chest compression, parameters of resuscitation efficiency such as early chest compression, early defibrillation, and decreased hands-off time are also vital in the Advanced Cardiac Life Support (ACLS) protocol. However, because of limited time and equipment in ACLS courses, efficiency of performance is difficult to evaluate. Materials and Methods: A free, easy-to-use iOS and Android app (CodeTracer®) was developed for real-time recording of cardiopulmonary resuscitation (CPR) performance. Interventions performed during resuscitation were set up as buttons. When the simulated scenario in the ACLS course began, instructors recorded every intervention and the team performed by pushing the appropriate buttons. When the scenario ended, the CodeTracer® automatically computed parameters, including the percentage of no-flow time, time to initiating CPR, and time to initiating defibrillation and also generated a graphic log for later discussion. Results: A total of 76 resuscitation episodes were recorded, 27 in the practice scenarios and 49 in the final Megacode simulations. After the course, the average percentage of no-flow time decreased 5.79%, time to initiating CPR decreased 3.05 s, and time to initiating defibrillation decreased up to 20.27 s. Of note, physicians as leaders seem to have better performance after the ACLS course than before, but the results were insignificant except for the percentage of no-flow time. Conclusions: CodeTracer® can record and calculate objective parameters for resuscitation performance in ACLS courses and can assist instructors in disseminating important concepts to participants. It can be a useful tool in ACLS courses.http://www.tcmjmed.com/article.asp?issn=1016-3190;year=2018;volume=30;issue=3;spage=165;epage=168;aulast=LeeAdvanced cardiac life supportAndroidCodeTraceriOS |
| spellingShingle | Chao-Hsiung Lee Ming-Yuan Huang Yi-Kung Lee Chen-Yang Hsu Yung-Cheng Su Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course Tzu Chi Medical Journal Advanced cardiac life support Android CodeTracer iOS |
| title | Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course |
| title_full | Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course |
| title_fullStr | Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course |
| title_full_unstemmed | Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course |
| title_short | Implementation of a real-time qualitative app to evaluate resuscitation performance in an Advanced Cardiac Life Support course |
| title_sort | implementation of a real time qualitative app to evaluate resuscitation performance in an advanced cardiac life support course |
| topic | Advanced cardiac life support Android CodeTracer iOS |
| url | http://www.tcmjmed.com/article.asp?issn=1016-3190;year=2018;volume=30;issue=3;spage=165;epage=168;aulast=Lee |
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