Data-Driven Nurse Staffing in the Neonatal Intensive Care Unit

Abstract

The challenge of nurse staffi ng is amplifi ed in the acute care neonatal intensive care unit (NICU) setting, where a wide range of highly variable factors affect staffi ng. A comprehensive overview of infant factors (severity, intensity), nurse factors (education, experience, preferences, team dynamics), and unit factors (structure, layout, shift length, care model) infl uencing pre-shift NICU staffi ng is presented, along with how intra-shift variability of these and other factors must be accounted for to maintain effective and effi cient assignments. There is opportunity to improve workload estimations and acuity measures for pre-shift staffi ng using technology and predictive

Acuity Tools for the Antepartum and Neonatal Intensive Care Units

“…Missed care, which may include late medications, late feedings, or missed daily care such as bathing, related to NICU nurse workload has been investigated (Tubbs-Cooley et al, 2019). Workload of the nurse in the NICU and other maternity care settings remains mostly unmeasured, although this area has high potential for intervention (Feldman & Rohan, 2022). No articles were found on NICU acuity that specifi cally determine acuity levels.…”

Risk Management in the Perinatal and Neonatal Setting

“…7 Another study reviewed data-driven workload estimates and acuity measures in a neonatal intensive care setting for preshift staffing using technology and predictive analysis. 8 These novel care models have taken a research and data-driven approach to prioritizing patient safety and can be shared with unit, department, and organizational leadership. More importantly, RM can be a strong advocate at the executive level for how adequate staffing can mitigate liability risk.…”

“…A recent publication looked at antepartum and neonatal tools to determine patient acuity and promote appropriate and equitable nurse-to-patient assignments 7. Another study reviewed data-driven workload estimates and acuity measures in a neonatal intensive care setting for preshift staffing using technology and predictive analysis 8…”