Does the Use of an Automated Resuscitation Recorder Improve Adherence to NRP Algorithms and Code Documentation?

BACKGROUND

Neonatal resuscitation is guided by Neonatal Resuscitation Program (NRP) algorithms; however, human factors affect resuscitation. Video recordings demonstrate that deviations are common. Additionally, code documentation is prone to inaccuracies. Our long-term hypothesis is that the use of an automated resuscitation recorder (ARR) app will improve adherence to NRP and code documentation; the purpose of this study was to determine its feasibility.

METHODS

We performed a simulation-based feasibility study using simulated code events mimicking NRP scenarios. Teams used the app during resuscitation events. We collected data via an initial demographics survey, video recording, ARR-generated code summary and a post-resuscitation survey. We utilized standardized grading tools to assess NRP adherence and the accuracy of code documentation through resuscitation data point (RDP) scoring. We evaluated provider comfort with the ARR via post-resuscitation survey ordinal ratings and open-ended question text mining.

RESULTS

Summary statistics for each grading tool were computed. For NRP adherence, the median was 68% (range 60-76%). For code documentation accuracy and completeness, the median was 77.5% (range 55-90%). When ordinal ratings assessing provider comfort with the app were reviewed, 47% chose "agree" (237/500) and 36% chose "strongly agree" (180/500), with only 0.6% (3/500) answering "strongly disagree". A word cloud compared frequencies of words from the open-ended text question.

CONCLUSIONS

We demonstrated the feasibility of ARR use during neonatal resuscitation. The median scores for each grading tool were consistent with passing scores. Post-resuscitation survey data showed that participants felt comfortable with the ARR while highlighting areas for improvement. A pilot study comparing ARR with standard of care is the next step.