Using Acuity to Predict Oncology Infusion Center Daily Nurse Staffing and Outcomes

This study assessed three acuity models across multiple centers to determine whether acuity was superior to patient volumes or patient hours in predicting the number of nurses needed to care for scheduled patients in an OIC, as well as the effect on objective metrics of missed nurse lunch breaks and patient wait times. A secondary end point was used to identify a superior model.METHODS: Classification machine learning models were built to assess the predictive value of three acuity models compared to patient hours and patient visits.FINDINGS: None of the tested acuity models were found to have statistically significant improvement to the prediction of needed OIC nurse staffing, patient wait times, or missed nurse lunch breaks.PMID:38511919 | DOI:10.1188/24.CJON.181-187
Source: Clinical Journal of Oncology Nursing - Category: Nursing Authors: Source Type: research