Fewer registered nurse hours available to patients linked to higher hospital death rates in England
Hospitals with fewer registered nurses at the bedside are seeing higher-than-expected death rates, according to a new London South Bank University study.
It found a consistent link between lower nurse care hours and excess mortality, raising concerns that missing nurses or substituting registered nurses with other healthcare staff does little to protect patient outcomes.
The analysis examined more than 300,000 data points from 122 NHS Trusts between December 2020 and May 2024. It looked at the relationship between staffing levels and the Summary Hospital-level Mortality Indicator (SHMI) — a key measure of hospital mortality. Researchers focused on Care Hours Per Patient Day (CHPPD), a metric that captures how much time different staff groups spend caring for patients.
Registered nurse staffing levels show direct impact on mortality
Hospitals with better-than-expected mortality had the highest nurse care hours, while those with worse-than-expected mortality had the lowest. In trusts where mortality was above nationally agreed control limits, registered nurses provided a median of just 4.59 care hours per patient per day, compared to 5.65 hours in hospitals with the best outcomes. Other healthcare workers, such as support staff, often stepped in when nurse hours were low, but this substitution did not appear to reduce mortality.
“This study shows that registered nurses play a critical role in patient safety,” said study co-author Alison Leary MBE, Professor of Healthcare and Workforce Modelling at LSBU. “When registered nurse staffing falls, mortality rises — and adding more support staff does not compensate.”
The findings also highlight a consistent pattern over time, suggesting that the link between registered nurse staffing and mortality is not a short-term fluctuation but a persistent trend. Hospitals recording below SHMI control limits saw the greatest improvements when registered nurse care hours increased, reinforcing the importance of maintaining optimal nurse staffing levels.
Previous research has shown that nurse numbers influence patient outcomes, but most studies relied on static snapshots. This study used time-series analysis to capture dynamic trends, offering stronger evidence that staffing decisions have long-term consequences.
“For hospital administrators and policymakers, the message is clear: reducing registered nurse hours or replacing nurses with other staff can lead to higher mortality. Workforce planning must prioritise evidence-based staffing models to protect patient safety,” added Professor Leary.
Complex staffing mix and quality of care remain critical
The Nuffield Trust, which collaborated on the study, noted that while the findings show a clear link between registered nurse staffing and mortality, the relationship between staffing and other patient outcomes is complex. Factors such as the mix of roles, quality of care and pressures within specific departments also play a part. Mortality rates alone may not reveal all underlying issues, and further research is needed to explore links between staffing and other adverse outcomes such as infections or pressure sores.
Chris Sherlaw-Johnson, Senior Fellow at the Nuffield Trust, said the findings also underline the dangers of poor recruitment and retention of registered nurses, as well as high sickness absence.
“The fact we have found a relationship between the time registered nursing staff spend with each patient in hospital and higher hospital mortality rates is important,” he said.
“However, good care is not just about the number of hours a patient gets with healthcare workers, but the quality of care delivered in those hours. This study also suggests that it matters to have the right roles available to deliver that care.”
The study, Understanding the relationship between care hours per patient day and summary hospital-level mortality indicator in English hospitals: A time series approach, was published in the Journal of Patient Safety and Risk Management.
It was co-authored by LSBU’s Jose Pereira, Cidália Eusébio and Professor Alison Leary in collaboration with the Nuffield Trust, data scientist Dr Steve Black, and Professor Sally Hardy, from the School of Health Sciences at the University of East Anglia.