Is my patient ready for a safe transfer to a lower-intensity care setting? Nursing complexity as an independent predictor of adverse events risk after ICU discharge

Background: Patients discharged from intensive care units (ICUs) are at risk for adverse events (AEs). Establishing safe discharge criteria is challenging. No available criteria consider nursing complexity among risk factors. Objectives: To investigate whether nursing complexity upon ICU discharge is an independent predictor for AEs. Methods: Prospective observational study. The Patient Acuity and Complexity Score (PACS) was developed to measure nursing complexity. Its predictive power for AEs was tested using multivariate regression analysis. Results: The final regression model showed a very-good discrimination power (AUC 0.881; p<0.001) for identifying patients who experienced AEs. Age, ICU admission reason, PACS, cough strength, PaCO2, serum creatinine and sodium, and transfer to Internal Medicine showed to be predictive of AEs. Exceeding the identified PACS threshold increased by 3.3 times the AEs risk. Conclusions: The level of nursing complexity independently predicts AEs risk and should be considered in establishing patient's eligibility for a safe ICU discharge.