Active Public Health & Healthcare NIHR-supported project Mental Health

Understanding WArd Strain - Effects on Patients and Staff (WASPS)

In plain English

AI plain-English summary

A nurse on a hospital ward is trying to care for six patients while another patient down the corridor is deteriorating rapidly, and there is no one else to help. This project will study what makes a ward feel dangerously busy—not just patient numbers, but the mix of tasks, administrative burdens, and the sudden arrival of acutely unwell patients. Most NHS care happens on wards, yet almost all research on workload and safety has focused on emergency departments and intensive care units. The WASPS project will fill that gap by interviewing staff, patients, and carers, and observing ward life directly. If it succeeds, the findings could help hospital managers redesign shift patterns, task allocation, and support systems to reduce staff burnout and prevent patient harm. The impact would be felt in quieter, safer wards where nurses can actually focus on the people in their care.

View original technical description
There have been significant investigations into workload and its effects on staff and patient safety in emergency departments and intensive care units, especially during COVID-19, however evidence for ward-level care is sparse even though most care is delivered on wards. WASPS will investigate the causes and effects of ward busyness using qualitative methods from a staff and patient/carer perspective. We will investigate the effects of high demand such as tasks, processes, workload and acutely unwell patients on the delivery of patients care and on staff satisfaction and their wellbeing. The methods will include rapid qualitative assessment and thematic analysis using interview and observational data.

Researchers

Katharina Kohler (Principal Investigator)

Related Research

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Ward strain as a marker of patient risk and safety
Patient involvement in improving the evidence base on inpatient care
Workforce Health Outcomes Study
Refining and testing the diagnostic accuracy of an assessment tool to predict admission and discharge of children and young people who attend an emergency department

Original classification

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