A Protocol for Developing a Staffing Prediction Model for Neonatal Care Using Time-Motion Data.

Determining appropriate nurse and midwife staffing levels in neonatal units is essential to provide safe, effective, and high-quality care to premature and critically ill infants. Ratio-based staffing methods currently utilized to guide staffing decisions consider factors such as infant acuity, specific illnesses, and treatment needs. However, these approaches may not adequately reflect contemporary neonatal care and are supported by limited empirical evidence. This study aims to generate robust evidence on the time required to provide care for infants with varying acuity levels and to develop a novel neonatal staffing model based on observed workload. This multi-site time-motion study will use one-to-one continuous observations of nurses and midwives providing care to infants across different acuity levels in South Australian neonatal units. Independent observers will record all activities performed and their duration. Descriptive statistics will be used to summarize activity characteristics, time allocation across care tasks, and infant acuity distributions. Regression modelling, including quantile and generalized linear models, will examine relationships between staffing, infant acuity, and time required for care activities. Model development will incorporate infant characteristics and nurse/midwife qualifications to estimate staffing requirements under different acuity scenarios. Sensitivity analyses and validation procedures will be undertaken to assess model reliability and generalizability. Continuous-observation time-motion studies are considered the gold standard for measuring healthcare activity duration and quantifying nursing and midwifery workload. This study will contribute to the development of an empirically informed neonatal staffing model in Australia, providing contemporary evidence to support workforce planning and to better align staffing requirements with infant care needs and acuity.