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1.
Resusc Plus ; 6: 100119, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34223378

RESUMO

AIM: We aimed to describe the cognitive processes of healthcare providers participating as airway leads in delivery room neonatal resuscitations using eye-tracking assisted debriefing to facilitate recall and provide situational context. METHODS: Delivery room neonatal resuscitations were recorded using eye-tracking glasses worn by participants who acted as airway leads. These glasses analyze eye-movements to produce an audio-visual recording approximating what was "seen" by the participant and marking their visual attention. Participants then reviewed and debriefed their recordings. Debriefing involved a retrospective think-aloud prompted by eye-tracked recordings and an integrated semi-structured interview. Debriefing sessions were transcribed and subjected to thematic analysis. RESULTS: Eight healthcare providers participated in 10 interviews; two providers participated twice in two separate resuscitations. Most visual attention was directed at the infant (62%), with 16% directed to monitors/gauges, 3% to team members. Five major themes emerged including situation awareness, performance, working in teams, addressing threats to performance, and perception of eye-tracking. Information processing was complex and involved top-down and bottom-up processing of environmental stimuli, integration of knowledge/experience, and anticipation of patient response. Despite the focus on individual cognition, interpersonal interactions and teamwork emerged as key aspects of resuscitation performance. Potential threats to performance include equipment issues, mental stress, distractions, and parental presence. Eye-tracking recordings were well-received by the participants. CONCLUSION: Retrospective think-aloud prompted by point-of-view eye-tracked recordings is a useful means of examining cognition of healthcare providers during neonatal resuscitation. Themes identified in this project aligned with existing models of clinical reasoning.

2.
Front Pediatr ; 8: 598475, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33415089

RESUMO

Objective: Human errors or protocol deviations during neonatal resuscitation are common. Excess workload has been proposed as a contributor to human error during medical tasks. We aim to characterize healthcare providers' perceived workload during neonatal resuscitation. Design: Perceived workload was measured using a multi-dimensional retrospective National Aeronautics and Space Administration Task Load Index (NASA TLX) survey. The NASA TLX collects data on mental, physical, and temporal demand, performance, effort, and frustration. Each section is rated independently by participants on a scale of 0-20 (0 being lowest and 20 being highest). The Raw-TLX score is a composite score of all dimensions and presented on a scale of 0-100. Healthcare providers complete a paper and pencil survey after attending delivery room resuscitations within 3 months. Setting: Level three neonatal intensive care unit at the Royal Alexandra Hospital, Edmonton, AB, Canada. Participants: All neonatal healthcare providers who attended deliveries. Exposure: Participation in the delivery room care of newborns. Measurement: Raw TLX scores as a measure of overall workload and scores for each dimension of workload. Main Results: During the study period, ~880 neonatal resuscitation events occurred, and a total of 204 surveys were completed. Healthcare providers completed one survey for 179 deliveries, two surveys for 20 deliveries, and three surveys for 5 deliveries. The mean (standard deviation) gestational age was 35 (5) weeks, and the median (interquartile range) birth weight was 2,690 (1,830-3,440) g. Interventions at delivery were (i) stimulation 149 (73%), suction 130 (64%), continuous positive airway pressure 120 (59%), positive pressure ventilation 105 (52%), intubation 33 (16%), chest compression 10 (5%), and epinephrine 4 (2%). The overall median (interquartile range) Raw-TLX was 34 (18-49). The scores varied by dimension with mental demand 10 (5-14), physical demand 4 (1-6), temporal demand 8 (3-14), performance 4 (2-6), effort 8 (4-13), and frustration 4 (1-10). Raw-TLX scores were higher when healthcare providers performed any intervention compared to no intervention [35 (22-49) vs. 8 (6-18), p = 0.0011]; intubation and no intubation was [55 (46-62) vs. 30 (17-46), p = 0.0001], and between performing chest compression vs. no chest compression [55 (49-64) vs. 33 (18-47), p = 0.001]. Conclusion: Perceived workload of neonatal healthcare providers increases during higher acuity deliveries. Healthcare providers' workload during neonatal resuscitation can be measured using NASATLX and was inversely associated with 5-min Apgar score. Future studies assessing healthcare providers' perceived workload during neonatal resuscitation in different settings are warranted.

3.
Front Pediatr ; 7: 356, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31508402

RESUMO

Approximately 10% of newborn infants require resuscitative intervention at birth. Ideally, this care is provided by a team of expert healthcare professionals who possess exceptional cognitive, psychomotor, and communication skills. Human errors and deviations from resuscitation protocol are common and may be attributable to excessive cognitive demand experienced by the resuscitation team. Cognitive Task Analysis (CTA) is a group of methods used to assess knowledge, judgments, goals, and decision-making of expert healthcare professionals. These methods may be used during neonatal resuscitation to gain an improved understanding of the approaches used by healthcare professionals. CTA methods have been applied in many medical disciplines including neonatology. CTA has been used to identify information previously confined to the intuition of experts. This information has been used to assess, develop, and improve medical technology, clinical decision support tools (DSTs), communication structure, and training methods. Knowledge attained through CTA might be applied similarly to neonatal resuscitation, which may in turn decrease human errors, and improve patient safety.

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