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2.
Pediatr Qual Saf ; 6(1): e373, 2021.
Article in English | MEDLINE | ID: mdl-33403319

ABSTRACT

To prevent transmission of severe acute respiratory syndrome coronavirus 2 to healthcare workers, we must quickly implement workflow modifications in the pediatric intensive care unit (PICU). Our objective was to rapidly train interdisciplinary PICU teams to safely perform endotracheal intubations in children with suspected or confirmed coronavirus disease 2019 using a structured simulation education program. METHODS: We conducted a quality improvement study in a tertiary referral PICU. After developing stakeholder-driven guidelines for modified intubation in this population, we implemented a structured simulation program to train PICU physicians, nurses, and respiratory therapists. We directly observed PICU teams' adherence to the modified intubation process before and after simulation sessions and compared participants' confidence using the Simulation Effectiveness Tool-Modified (SET-M, Likert scale range 0: do not agree to 2: strongly agree regarding statements of confidence). RESULTS: Fifty unique PICU staff members participated in 9 simulation sessions. Observed intubation performance improved, with teams executing a mean of 7.3-8.4 out of 9 recommended practices between simulation attempts (P = 0.024). Before undergoing simulation, PICU staff indicated that overall they did not feel prepared to intubate patients with suspected or confirmed SARS-CoV-2 (mean SET-M score 0.9). After the simulation program, PICU staff confidence improved (mean SET-M score increased from 0.9 to 2, P < 0.001). CONCLUSION: PICU teams' performance and confidence in safely executing a modified endotracheal intubation process for children with suspected or confirmed SARS-CoV-2 infection improved using a rapidly deployed structured simulation education program.

3.
Pain Manag Nurs ; 22(3): 260-267, 2021 06.
Article in English | MEDLINE | ID: mdl-33288443

ABSTRACT

BACKGROUND: Conducting an adequate pain assessment in the Pediatric Intensive Care Unit (PICU) is multifactorial and complex due to the diversity of the population. It is critical that validated pain assessment methods are used appropriately and consistently to aid in evaluation of pain and pain management interventions. PURPOSE: The aim of this evidence-based practice project was to improve pain assessment practices in the PICU through a decision-support algorithm. DESIGN & METHODS: The Iowa Model-Revised was used to guide the development and implementation of an evidence-based decision algorithm. Pre- and postdata were collected via surveys (nursing knowledge and confidence) and documentation audits (nursing pain assessments). Various implementation strategies were used to facilitate the integration and sustainability of the algorithm in practice. RESULTS: The majority of survey items showed an increase in nursing knowledge and confidence. Audits of pain assessment documentation displayed an increase in appropriate pain assessment documentation related to a child's communicative ability. However, there is a need for reinfusion related to the documentation of sedation assessments. CONCLUSIONS: The use of an algorithm supported the ability of PICU nurses to critically consider and choose the pain assessment method most appropriate for the patient's condition. The algorithm promotes nursing clinical judgement, prioritizes pain management, and includes patients receiving sedation. The algorithm supports a comprehensive pain assessment in a difficult pediatric patient population. Future research is needed to strengthen and standardize the usage of terms "assume pain present" and "assume pain managed," and to also improve the overall feasibility and effectiveness of the algorithm.


Subject(s)
Intensive Care Units, Pediatric , Pain Management , Pain Measurement , Algorithms , Child , Humans , Pain/diagnosis
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