Data-Driven Nurse Staffing in the Neonatal Intensive Care Unit

MCN Am J Matern Child Nurs. 2022 Sep-Oct;47(5):249-264. doi: 10.1097/NMC.0000000000000839.

Abstract

The challenge of nurse staffing is amplified in the acute care neonatal intensive care unit (NICU) setting, where a wide range of highly variable factors affect staffing. A comprehensive overview of infant factors (severity, intensity), nurse factors (education, experience, preferences, team dynamics), and unit factors (structure, layout, shift length, care model) influencing pre-shift NICU staffing is presented, along with how intra-shift variability of these and other factors must be accounted for to maintain effective and efficient assignments. There is opportunity to improve workload estimations and acuity measures for pre-shift staffing using technology and predictive analytics. Nurse staffing decisions affected by intra-shift factor variability can be enhanced using novel care models that decentralize decision-making. Improving NICU staffing requires a deliberate, systematic, data-driven approach, with commitment from nurses, resources from the management team, and an institutional culture prioritizing patient safety.

Publication types

  • Review

MeSH terms

  • Humans
  • Infant, Newborn
  • Intensive Care Units, Neonatal*
  • Nursing Staff, Hospital*
  • Personnel Staffing and Scheduling
  • Workforce
  • Workload