Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation.

ABSTRACT:

Background

Managing nurse staffing is complex due to fluctuating demand based on ward occupancy, patient acuity, and dependency. Monitoring staffing adequacy in real time has the potential to inform safe and efficient deployment of staff. Patient classification systems (PCSs) are being used for per shift workload measurement, but they add a frequent administrative task for ward nursing staff.

Objective

The objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data.

Methods

Anonymized admission records and assessments from a PCS supporting the safer nursing care tool were used to determine nursing care demand in medical and surgical wards in a single UK hospital between February 2017 and February 2020.

SUBMITTER: Meredith P 

PROVIDER: S-EPMC12314723 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature