Introduction: Cardiopulmonary resuscitation (CPR) quality assurance and research has traditionally been limited to the first five minutes of resuscitation due to significant costs in time, resources and personnel from manual data abstraction. Moreover, CPR quality can be affected during prolonged resuscitations, which represents significant knowledge gaps. The objective of this study was to develop a software program to help automate the abstraction of CPR quality data from electronic defibrillators. Methods: We developed a software program to facilitate and help automate data abstraction from electronic defibrillator files for entire resuscitation episodes. Internal validation of the software program was performed on 50 randomly selected cardiac arrest cases with resuscitation durations of up to 60 minutes. CPR quality data variables such as number of ventilations, number of compressions, minute compression rate, minute compression depth, minute compression fraction, minute end-tidal CO2, were manually abstracted independently by two trained data abstractors and by the automated software program. Error rates and the time needed for data abstraction were measured. Results: A total of 9826 data points were abstracted. Manual data abstraction resulted in a total of six errors (0.06%) compared to zero errors by the software program. The mean time ± SD needed for manual data abstraction was 20.3 ± 2.7 minutes compared to 5.3 ± 1.4 minutes using the software program (p=0.003). Conclusion: Our CPR quality data abstraction software was 100% accurate in abstracting CPR quality data for complete resuscitation episodes and showed a significant reduction in data abstraction duration. This software will enable quality assurance programs and future cardiac arrest studies to evaluate the impact of CPR quality during prolonged resuscitations.
We developed and validated an automated software program that efficiently abstracts and transfers CPR process measures data from electronic defibrillators for complete cardiac arrest episodes. This software will enable future cardiac arrest studies and quality assurance programs to evaluate the impact of CPR process measures during prolonged resuscitations.
Introduction:
Research and quality assessment of cardiopulmonary resuscitation (CPR) quality has traditionally been limited to the first five minutes of resuscitation due to significant costs in both time and personnel from manual data abstraction. Manual CPR quality data abstraction of entire episodes of resuscitation may be too resource-intensive for many emergency medical service (EMS) agencies and hospitals. Moreover, the first five minutes of CPR are also different in many aspects compared to later time periods during cardiac arrest resuscitation, which represents significant knowledge gaps since the majority of resuscitations go beyond five minutes.
Methods:
We developed a software program to facilitate and help automate data abstraction from electronic defibrillator files for entire resuscitation episodes. Internal validation of the software program was performed on 50 randomly selected out-of-hospital cardiac arrest cases with resuscitation durations up to 60 minutes. CPR quality data variables were abstracted as minute averages, which included ventilation rate, CPR compression rate, depth, fraction, and end-tidal CO2. CPR quality data variables were manually abstracted independently by two trained data abstractors and automatically by the software program. Error rates and the time needed for data abstraction were measured.
Results:
A total of 9826 data points were abstracted. Manual data abstraction resulted in a total of six errors (0.06%) compared to zero errors by the software program. The mean time ± SD needed for data abstraction was 20.3 ± 2.7 minutes manually and 5.3 ± 1.4 minutes using the software program (p=0.003).
Conclusion:
Our data abstraction software was 100% accurate in abstracting CPR quality data for complete cardiac arrest resuscitation episodes. It significantly reduced the time and resources required to abstract CPR quality data, and will allow EMS agencies and hospitals to evaluate their CPR quality in a cost-effective manner. The development of this software will enable future studies to efficiently evaluate CPR quality during entire resuscitation episodes, including its impact on patient outcomes during prolonged cardiac arrests.
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