Having an excessive daily nurse workload increases the risk of patient safety incidents and deaths, according to a ground-breaking study from Finland. The study – published in BMJ Open – found the chances of a patient safety incident increased by up to about 30% if nurses’ workload went above “optimal” levels and the odds of a patient dying increased by about 40%. Meanwhile, researchers found that when workload dropped and nurses had even more time to observe and care for patients the risk of safety incidents and deaths was about 25% lower. The study, which adds to evidence of the link between staffing levels and patient welfare, is said to be the first to look at the relationship between nurse workload and patient outcomes on a daily basis. It is based on data from 36 units in four Finnish hospitals – three secondary and one tertiary acute care hospitals – with information about nursing workload, staffing, patient safety incidents and mortality rates collected daily over one year. While many studies have shown insufficient nurse staffing in hospitals has a negative impact on patient welfare, the research team argue some results are “inconsistent” and the link between staffing and mortality and other patient outcomes is not always clear cut. Some of this evidence is open to challenge due to factors including “poor research designs, measurement problems and/or imprecise data that do not take into account daily variations in patients’ care needs may contribute to mixed findings”, they stated. However, by analysing daily information they maintained it would be possible to establish any links between staffing and safety with more certainty. The researchers, from Åbo Akademi University, were able to obtain detailed information about nursing workload thanks to the RAFAELA patient classification system, which was developed in Finland in the 1990s to ensure safe staffing levels.Instead of using fixed nurse-to-patient ratios, it uses daily data on patient’s care needs and the workload per nurse to ensure an appropriate number of staff on the wards. When various factors that could skew the data were taken into account including ward specifics, days of the week and the time of year, the research team found an association between daily workload and patient welfare. When nursing workload went above the “optimal” level, the risk of a patient safety incident increased by 8% to 32%, depending on the type of incident. Meanwhile, the risk of patient mortality increased by 43% if workload exceeded the preferred level. However, if workload was below that level, the risks of a safety incident or death reduced by roughly a quarter or between 15% to 27%, depending on the type of incident. A reduced workload “would mean that nurses have more time for caring and observing each patient, which may reduce the risk for adverse events and accordingly prevent the patient’s health condition from deteriorating”, said the study authors, led by Professor Lisbeth Fagerström. As part of the study, they found some evidence to suggest more traditional methods of determining staffing levels using nurse-to-patient ratios may be less robust than basing staffing on daily records of patient acuity. “We found evidence that a staffing measure based on daily measurements of individual patient care needs and the recommended nursing workload is slightly better in predicting incidents and mortality rates, as compared to the standard patient-to-nurse ratio,” said the paper. However, the authors went on to stress it was still unclear which method had the greatest benefit when it came to avoiding patient safety incidents and deaths, and said bigger studies over a longer period of time were needed.They also make it clear that their calculations do not take account of the potential influence of skill mix, nurses’ level of competence or experience and the exact amount of time nurses were able to spend working directly with patients. Meanwhile, they also highlighted the fact some safety incidents may not be reported due to lack of knowledge, staffing shortages, stress or burn-out and the fact nurses working in the most hard-pressed environments may be more likely to under-report. Professor Peter Griffiths, chair of health services research at the University of Southampton, said the headline findings were not surprising. But he said some aspects were “striking” including the fact patient outcomes continued to improve when workload dropped below what was perceived to be “optimal” levels. “Basically, the results are not new – higher nursing workload is associated with worse outcomes. We’ve seen that in lots of studies,” he told Nursing Times. “However, a lot of previous research can be criticised, because it just uses a patient count as a measure of workload, although results are typically adjusted for patient acuity,” he said. “Here, the authors have used a system designed and validated to measure the amount of nursing work that is required per patient as the measure, and have confirmed a link between nursing workload and outcomes”, he noted. Professor Griffiths said the findings backed up previous research on the link between staffing and patient outcomes and actually showed criticism of past studies was “invalid”. He said the RAFAELA system had been the focus of extensive research and a review of staffing tools for the National Institute for Health and Care Excellence found “it had some of the most robust evidence”. “Here we see the results of the system correlating with outcomes which lends it some support, although it is striking that as staffing levels rise above what the system sees as ‘optimum’, outcomes continue to improve,” he said. “It is also striking that this happens in Finland, a country where the RN4CAST study found that registered nurse staffing levels were similar to the UK,” he added, highlighting a major piece of European research on nursing and safety.
Nurses Group became the most trusted healthcare agency by following the simple formula, we treat our clients like family. We aim to provide a quality and reliable healthcare service through our team of committed and experienced staff.