Development and evaluation of a risk prediction model for unscheduled transfers to the resuscitation unit in emergency observation patients

Abstract Objective To analyze the risk factors associated with unscheduled transfers to the resuscitation unit in emergency observation patients and to develop a predictive model based on nursing risk scores. Methods This prospective study analyzed the clinical data of 1166 patients admitted to the emergency observation unit of West China Hospital, Sichuan University, from 1 December 2020, to 28 February 2021. Patients were categorized into groups based on the occurrence of unscheduled transfers to the resuscitation unit. Fall risk scores, pressure ulcer risk scores, and self‐care ability assessments were conducted for all patients. Multivariate logistic regression was used to identify risk factors and construct a predictive model. Results Among the patients, 110 (9.4%) experienced unscheduled transfers to the resuscitation unit. Multivariate logistic regression analysis identified high fall risk, high pressure ulcer risk and impaired self‐care ability as independent risk factors for unscheduled transfers. A nomogram was constructed incorporating these factors along with age and sex, achieving an area under the receiver operating characteristic curve of 0.823 (95% confidence interval: 0.786–0.859). Conclusions High fall risk, high pressure ulcer risk, and impaired self‐care ability are independent risk factors for unscheduled transfers to the resuscitation unit in emergency observation patients. The developed predictive model demonstrates provides valuable evidence to guide clinical decision‐making and support proactive nursing interventions.