Multifactor Logistic Analysis to Explore the Risk Factors of Safety Risks in the Transport of Critically Ill Patients with ICU and the Improvement of Nursing Strategies

Abstract

Objective. Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and the improvement of nursing strategies. Methods. Two hundred critical transport patients with ICU treated in our hospital from January 2019 to April 2021 were enrolled. According to the occurrence of unsafe events in transit, the patients were assigned to the control group (165 cases without unsafe events, $n=165$ ) and the study group (35 cases with safety incidents, $n=35$ ). Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and to enhance nursing strategies. Results. (1) General data of the subjects: among the 200 critically ill patients with ICU who needed in-hospital transport, the age ranged from 18 to 85 years with an average age of $52.48\pm 3.31$ , including 89 males and 111 females. There were 35 cases of gastrointestinal bleeding, 16 cases of respiratory failure, 23 cases of heart failure, 43 cases of myocardial infarction, 26 cases of cerebrovascular accident, 14 cases of ectopic pregnancy, 25 cases of severe injury, and 18 cases of mechanical ventilation. There were 35 cases in the study group with accidents and 45 cases in group B without accidents. (2) Among the 200 patients, 35 patients had complications during the transit process in the intermediate people’s court, with an incidence rate of 17.5%. It included blood pressure fluctuation ( $n=6$ ), artificial airway obstruction ( $n=6$ ), decrease in blood oxygen saturation ( $n=10$ ), dyspnea ( $n=5$ ), fall pain ( $n=3$ ), elevated intracranial pressure ( $n=2$ ), and other factors ( $n=3$ ). There exhibited no significant difference in blood oxygen saturation at each time point during transport ( $P>0.05$ ). There exhibited no significant difference in SpO2 before transport. The comparison of 5 min and 10 min blood oxygen saturation during transit in the study group was lower compared to the control group ( $P<0.05$ ). (3) In a univariate analysis of safety risks for critically ill ICU patients, home escorts did not show significant differences in hospital transport for critically ill ICU patients ( $P>0.05$ ). There were significant differences in terms of age, patient’s condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline ( $P<0.05$ ). The results of multivariate logistic regression analysis indicated that age, patient’s condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline were the risk factors affecting the safe transport of critically ill patients ( $P<0.05$ ). Conclusion. Age, patient’s condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline are the independent risk factors that affect the safe transport of emergency or ICU critically ill patients. Therefore, in order to reduce the risk of transshipment, we must enhance the safety awareness of escorts, strengthen the management and training of escorts, promote rules and regulations, and formulate dangerous plans, so as to eliminate the occurrence of unsafe factors.