Improvement of the functioning and efficiency of a Code Blue system after training in a children's hospital in China
Yu Shi1, Gongbao Liu1, Di Cao1
1Division of Medical Administration, National Children's Medical Center Children's Hospital of Fudan University, Shanghai, China.
Insights
Code Blue events in children
Area of Science:
- Pediatric Emergency Medicine
- Hospital Quality Improvement
- Critical Care Systems
Background:
- Code Blue is a critical care emergency code used in hospitals.
- This study retrospectively analyzed Code Blue cases in a children's hospital.
- The research aimed to identify high-risk factors for survival and improve Code Blue system effectiveness through training.
Purpose of the Study:
- To identify risk factors associated with Code Blue survival in a pediatric setting.
- To evaluate the impact of staff training on the effectiveness of Code Blue response.
- To enhance critical care delivery during medical emergencies.
Main Methods:
- Retrospective analysis of 139 Code Blue cases from January 2016 to December 2019.
- Data collected included patient demographics, diagnosis, timing of events, treatment, and outcomes.
- Statistical analysis employed Chi-square tests and logistic regression.
Main Results:
- Infectious diseases, hematology/oncology, and cardiology wards had the most frequent Code Blues.
- Age, inpatient status, arrival time, CPR duration, and shock cause were risk factors for mortality.
- Post-training, arrival and recovery times significantly decreased (P<0.01), ICU transfers increased (P<0.05), and mortality decreased (P<0.01).
Conclusions:
- Identifying Code Blue risk factors is crucial for pediatric critical care.
- Hospital staff training significantly improved the efficacy of Code Blue events.
- Training enhances patient outcomes and survival rates during critical emergencies.
Background:
Code Blue is a popular hospital emergency code that is used to alert the emergency response team to any medical emergency requiring critical care. By retrospectively studying Code Blue cases in a children's hospital, we looked for high-risk factors associated with survival and how to improve the effectiveness of Code Blue systems through training.
Methods:
Data were collected on age, gender, department, diagnosis, time of Code Blue call activation, time between call and arrival of the Code Blue team, treatment details and outcome before and after the training process from January 2016 to December 2019. Chi-square test and logistic regression analysis were used to analyze the data.
Results:
A total of 139 Code Blue cases from the period of January 2016 to December 2019 were retrospectively studied. The wards where Code Blues occurred most frequently were the infectious diseases ward (n=31, 22.3%), the hematology and oncology ward (n=30, 21.6%), and the cardiology ward (n=15, 10.8%). Age, inpatient status, time of arrival, the time of cardiopulmonary resuscitation (CPR), and the cause of shock were all risk factors for death. After the training, the arrival time and recovery time were significantly reduced (P<0.01). The proportion of patients who were transferred to the ICU had increased (P<0.05), and the proportion of deaths had decreased (P<0.01). The survival curve improved (P<0.05).
Conclusions:
It is very important to summarize the risk factors related to Code Blue. It is clear that the efficacy of the Code Blue events improved after training of the hospital staff in the Children's Hospital.
