Development and implementation of an inpatient CAMEO© staffing algorithm to inform nurse-patient assignments in a pediatric cardiac inpatient unit

Background: Nursing workload measurement systems are vital to determine nurse staffing for safe care. The Inpatient Complexity and Assessment and Monitoring to Ensure Optimal Outcomes (CAMEO (c)) acuity tool provides a standardized language to communicate the acuity and complexity of nursing care in the pediatric inpatient setting. Design and methods: A process improvement project was implemented on a pediatric cardiac inpatient unit to utilize the Inpatient CAMEO (c) tool to inform nurse-patient assignments. Development of the Inpatient CAMEO (c) Staffing Algorithm utilized a modified Delphi methodology. Six Delphi rounds were performed for algorithm development, addressing potential implementation barriers, educating nursing staff, piloting feasibility, and final full implementation. Results: The cardiac inpatient unit's charge nurses' algorithm utilization was 86% (n = 12) during the feasibility pilot. The algorithm impacted and changed 28% (n = 4) of the shifts' assignments. One-year post algorithm implementation, CAMEO (c) documentation rates increased from 25 to 30% to >60%. A retrospective, two-week point-prevalence analysis one-year post-implementation described adherence to the Inpatient CAMEO (c) Staffing Algorithm for 87% (n = 375) of the nurses' patient assignments. Conclusions: The Inpatient CAMEO (c) Staffing Algorithm was developed based upon the Inpatient CAMEO (c) tool and the Inpatient CAMEO (c) Complexity Classification System to inform nurse-patient assignments and allocate nursing resources. The Inpatient CAMEO (c) Staffing Algorithm was feasible and sustainable for over one year following implementation at a single center's pediatric cardiac inpatient unit. (C) 2021 Published by Elsevier Inc.