UK ward design: Patient dependency, nursing workload, staffing and quality—An observational study

BackgroundThere are important relationships between ward design, patient welfare and staff activity in the literature but studies seem not to have tested all the variables. Whether ward designs influence nursing structures, processes and outcomes, therefore, has not been fully answered. While studies provide helpful guidance, nursing efficiency and effectiveness implications are speculative.ObjectivesTo improve nursing efficiency and effectiveness by capitalising on the best ward design features.SettingA database consisting of 375 UK wards, constructed for other research and development purposes, was revisited and reconfigured for the present study. The database was updated between 2003 and 2004.ParticipantsOf 390 wards approached, 375 generated usable data.MethodPatient dependency, nursing activity, workload, nursing quality and staffing data in the original database were obtained using mainly non-participation observation methods. Later, wards were classified in eight ways and differences between ward types examined.ResultsPatient dependency did not stand out in any ward type but as the literature predicted, direct patient care was higher in Nightingale wards. Racetrack ward nursing activity was also close to idyllic. Bay wards, owing to their greater occupancy peaks and troughs, had a propensity to generate heavier workloads. Time-out and down-time were not excessive in any ward type, and it is likely that ward leadership may be compensating for some variables’ negative effects. Racetrack wards were considerably less-well staffed and grade-mix dilute and consequently the cheapest. Quality scores were higher in Nightingale wards—nurses’ greater observation capability was a significant factor. Wards’ central-core configurations also influenced nursing efficiency and effectiveness.ConclusionsRacetrack wards have an edge over other ward designs. However, replicating Nightingale conditions by, for example, equalising occupancy, throughput and staffing and maximising nurses’ substations, could engender similar outcomes elsewhere.