Tablet-Based Decision Support Tool Improves Performance of Neonatal Resuscitation: A Randomized Trial in Simulation

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.

A recorder/time coach decreases time errors during neonatal resuscitation: A randomized, simulation-based clinical trial

Aim

To evaluate the effects of a hands-off recorder/time coach versus an additional hands-on healthcare provider on Neonatal Resuscitation Program (NRP) algorithm compliance and team member workload in neonatal resuscitations.

Methods

Two interventions were studied using a 2 × 2 factorial design: an additional hands-on team member and the presence of a designated, hands-off recorder/time coach. The recorder/time coach documented interventions and delivered pre-specified prompts at defined points during the resuscitation. The primary outcome was cumulative time error. Secondary outcomes were time to first dose of IV epinephrine, overall team performance as assessed by the Neonatal Resuscitation Performance Evaluation (NRPE) score, and workload assessed by the NASA Task Load Index (NASA TLX).

Results

64 teams were studied. Teams with a recorder had a significantly lower cumulative time error compared to teams without a recorder (p < 0.001). An additional hands-on team member did not change cumulative time error. There was no difference in time to first dose of IV epinephrine or NRPE score in these comparisons. Ad-hoc analysis did reveal a significant increase in time to IV epinephrine in teams with the minimum of four total members (p = 0.025). A recorder/time coach increased team leader NASA TLX overall workload score (p = 0.047), but an additional hands-on team member did not.

Conclusion

A designated, hands-off recorder/time coach improved compliance by decreasing cumulative time error in teams performing complex simulated neonatal resuscitations.

Development and use of an infant resuscitation performance tool (Infa-RePT) to improve team performance

BACKGROUND

Measurement of neonatal team resuscitation performance is critical to identify opportunities for improvement and to target education. An effective tool to measure team performance during infant resuscitations is lacking.

METHODS

We developed an in-hospital infant resuscitation performance tool (Infa-RePT) using the modified Delphi method. We employed a QI framework and targeted interventions, including the use of role responsibility checklists, mock codes, and an educational video. We tracked Infa-RePT scores, mock code team attendance, and confidence surveys. Our specific aim was to improve Infa-RePT score from a baseline of 7.4 to <5 (lower is better) over a 26-month period.

RESULTS

Twenty-five elements reached >80% consensus as essential components to include on the Infa-RePT. Independent observation showed 86% concordance on checklist items. Simulation (n = 26) and unit-based code (n = 10) Infa-RePT scores showed significant improvement after project start from 7.4 to 4.2 (p < 0.01) with special cause variation noted on control chart analysis. No significant difference was observed between simulations and in-unit codes. Staff confidence self-reports improved over the study period.

CONCLUSIONS

Use of a novel scoring tool can help monitor team progress over time and identify areas for improvement. Focused interventions can improve resuscitation team performance.

IMPACT

We developed and used a novel, comprehensive measurement tool for team infant resuscitation performance in both simulation and in-unit settings. Using QI methodology, team performance improved after the enhancement of a mock code simulation program. Review of team performance scores can highlight key areas to target interventions and monitor progress over time.

Usability of human-computer interaction in neonatal care

While a goal for Electronic Health Record (EHR) technologies was to improve quality, efficiency, and safety, the usability of EHRs has remained poor. The relation to patient harm and user satisfaction cannot be ignored. Optimization of EHR usability is imperative to improving the outcomes for critically ill patients, especially neonates who are at the extremes of physiologic variability. Further development and integration of metadata with predictive modeling and clinical protocols can support provider decision making, increase efficiency and safety, and reduce clinician burnout. This paper reviews EHR usability and identifies opportunities to improve the EHR specific to neonatal care.

Similarity of expert clinicians’ rank order of differential diagnoses in a newborn resuscitation context

Background

Methods

Results

Conclusions

Concordance of expert clinicians' interpretations of the newborn's true physiological state

BACKGROUND

Many physiological aspects of the neonatal transition after birth are unobservable because relevant sensors do not yet exist, compromising clinicians' understanding of a neonate's physiological status. Given that a neonate's true physiological state is currently unavailable, we explored the feasibility of using clinicians' degree of concordance as an approximation of the true physiological state.

METHODS

Two phases of structured interviews were conducted. In Phase 1 (N = 8) and Phase 2 (N = 12), we presented neonatal experts with eight graphical trajectories of real newborns' heart rate and oxygen saturation values in the first 10-15 min after birth. We elicited the participants' interpretations of potential underlying physiological conditions that could explain the vital sign patterns.

RESULTS

The global differential diagnosis data for each phase produced the same pattern of results: (1) four trajectories produced a substantial degree of concordance among clinicians (61-80%) and (2) four trajectories produced a strong degree of concordance among clinicians (81-100%).

CONCLUSIONS

It is possible to achieve a strong degree of concordance among neonatal experts' interpretations of newborn trajectories. Thus, using the degree of concordance as an approximation of the neonate's true physiological state in resuscitation after birth may be a promising direction to explore for cognitive aid design.

IMPACT

Differential diagnoses with a good degree of concordance among expert neonatal clinicians could potentially substitute in part for the direct measurement of key physiological and anatomical variables of the neonatal transition, which is currently unavailable. The concordance of clinicians' judgements or inferences with regards to the true physiological state of the newborn during resuscitation after birth has never been explored. The findings provide a crucial first step toward using consensus of neonatal experts' judgements in the design of a cognitive aid to support clinicians' management of the newborns who require resuscitation after birth.