Australian study shows that savings made from shorter stays are double the cost of hiring more staff

 

 

 

 

 

 

 

 

 

 

 

 

 

A study across 55 hospitals in Queensland, Australia suggests that a recent state policy to introduce a minimum ratio of one nurse to four patients for day shifts has successfully improved patient care, with a 7% drop in the chance of death and readmission, and 3% reduction in length of stay for every one less patient a nurse has on their workload.

The study of more than 400,000 patients and 17,000 nurses in 27 hospitals that implemented the policy and 28 comparison hospitals is published in The Lancet. It is the first prospective evaluation of the health policy aimed at boosting nurse numbers in hospitals to ensure a minimum safe standard and suggests that savings made from shorter hospital stays and fewer readmissions were double the cost of hiring more staff.

Despite some evidence that more nurses in hospitals could benefit patient safety, similar policies have not been widely implemented across the globe, partly due to an absence of data on the long-term effects and costs, as well as limited resources. In recent years, Scotland, Wales, and Ireland have mandated numbers of patients per nurse, but strategies to improve nursing levels remains debated worldwide.

Study fills data gap

“Our findings plug a crucial data gap that has delayed a widespread roll-out of nurse staffing mandates. Opponents of these policies often raise concerns that there is no clear evaluation of policy, so we hope that our data convinces people of the need for minimum nurse-to-patient ratios by clearly demonstrating that quality nursing is vital to patient safety and care,” says lead author, Professor Matthew McHugh of the University of Pennsylvania School of Nursing, USA.

In 2016, 27 public hospitals in Queensland were required to instate a minimum of one dedicated nurse for every four patients during day shifts and one for every seven patients for night shifts on medical-surgical wards.

The research team collected data from those 27 Queensland hospitals that instated ratios and from 28 other hospitals in the state that did not, at baseline in 2016 and at follow-up in 2018 (two years after the policy was implemented). Only nurses in direct contact with adult patients in medical-surgical wards were included – data from patients in birthing suites and psychiatric units were not assessed in the study.

Researchers used patient data to assess demographics, diagnoses, and discharge details for patients, as well as length of hospital stay. These data were then linked to death records for 30 days following discharge, and to readmissions within seven days of discharge.

The researchers sent an email survey to nurses in each hospital to ask about the numbers of bedside nurses and patients on their most recent shift. The responses were used to establish the numbers of nurses per patient and then averaged across wards and hospitals. Responses were received from 8,732 nurses (of a possible 26,871) at baseline in 2016, and 8,278 (of a possible 30,658) in 2018.

The study includes baseline data for 231,902 patients (142,986 in hospitals that implemented the policy and 88,916 in comparison hospitals), and for 257,253 patients (160,167 in hospitals that implemented the policy and 97,086 in comparison hospitals) after the policy was brought in.

Comparison hospitals had no change in staffing, with six patients per nurse in 2016 and the same ratio (1:6) in the follow-up period in 2018. Intervention hospitals averaged five patients per nurse at baseline in 2016, with a reduction to four per nurse after the policy implementation.

Patient deaths

To compare the changes in outcomes in the intervention and comparison hospitals over time, the researchers estimated the odds of dying within 30 days of admission and of being readmitted within seven days of discharge, and the additional length of stay, after adjusting for factors such as patient age, sex, existing health conditions and hospital size. They found that the chance of death rose between 2016 and 2018 by 7% in hospitals that did not implement the policy, and fell by 11% in hospitals that did implement the policy.

Readmissions

The chances of being readmitted increased by 6% in the comparison hospitals over time, but stayed the same in hospitals that implemented the policy. Between 2016 and 2018, the length of stay fell by 5% in the hospitals that did not implement the policy, and by 9% in hospitals that did.

Nurse workloads

Further analyses found that when nurse workloads improved by one less patient per nurse, the chance of death and readmissions fell by 7%, and the length of hospital stay dropped by 3%.

Using their modelling to predict figures that would have been expected without the policy in place, the researchers estimated that there could have been 145 more deaths, 255 more readmissions and 29,222 additional days in hospital in the 27 hospitals that implemented the policy between 2016 and 2018.

Financial impact of employing more nurses

To calculate the financial impact of the staffing policy, the researchers used state data to estimate the cost of funding the 167 extra staff needed to reduce workload by one patient per nurse at approximately $33,000,000 (AUD) in the first two years. Based on Australian health economic data, they further estimated that preventing readmissions and reducing lengths of stay resulted in an approximate saving of $69,150,858 in the 27 hospitals across the two years following the mandate.

“Part of the reluctance to bring in a minimum nurse-patient ratio mandate from some policy-makers is the expected rise in costs from increased staffing. Our findings suggest that this is short-sighted and that the savings created by preventing readmissions and reducing length of stay were more than twice the cost of employing the additional nurses needed to meet the required staffing levels – a clear return on investment. Often, policy-makers are concerned about whether they can afford to implement such a policy. We would encourage governments to look at these figures and consider if they can afford not to,” says Professor Patsy Yates of the Queensland University of Technology School of Nursing, Australia.

Study limitations

The authors note that there are a number of limitations associated with the study. Hospitals in the research were not randomly assigned to comparison or intervention groups, as only 27 hospitals in the state were mandated to follow the policy. Furthermore, the hospitals included in both groups were not matched for size or patient demographics and health conditions, although this is accounted for in adjusted analyses.

Access the study: Effects of nurse-to-patient ratio legislation on nurse staffing and patient mortality, readmissions, and length of stay: a prospective study in a panel of hospitals. The Lancet. May 11, 2021. https://doi.org/10.1016/S0140-6736(21)00768-6

 

Scientists have developed a brain-computer interface (BCI) which for the first time enables neural signals associated with handwriting to be decoded and turned into text in real time.

This breakthrough in BCI technology has the potential to enable paralysed or paraplegic individuals – unable to write or speak – to communicate in writing, at speed, in real time.

The study was published in Nature, May 12.

The researchers developed an intracortical BCI that decodes attempted handwriting movements from neural activity in the motor cortex and translates it to text in real time, using a recurrent neural network decoding system.

They tested the device in a participant with paralysis which in essence enabled him to type without using his hands. By thinking about handwriting letters, the researchers were able to decode the neural signals with an algorithm which turned the letters into typed text on a screen in real time.

The study participant typed 90 characters per minute – more than double the previous record for typing with such a BCI. However, previous studies had not used decoded neural handwriting signals. They had instead used thought-controlled cursor movements on a virtual keyboard.

Neural signals associated with handwriting

Study coauthor Krishna Shenoy, a Howard Hughes Medical Institute (HHMI) investigator at Stanford University and his team have in recent years been studying neural activity associated with speech in an effort to reproduce it. However, they had not considered trying to decode neural signals associated with handwriting, says Frank Willett, an HHMI research specialist and neuroscientist in Shenoy’s group.

First, the participant was asked to copy letters that were displayed on the screen, which included the 26 lower-case letters along with some punctuation: “>” which was used as a space and “~” which was used as a “full stop.” At the same time, implanted electrodes recorded the brain activity from approximately 200 individual neurons associated with handwriting that responded differently while he mentally “wrote” each individual character. After a series of training sessions, the BCI’s computer algorithms learned how to recognize neural patterns corresponding to individual letters, allowing the participant to “write” new sentences that hadn’t been printed out before, with the computer displaying the letters in real time.

“This method is a marked improvement over existing communication BCIs that rely on using the brain to move a cursor to ‘type’ words on a screen,” said Willett, the study’s lead author. “Attempting to write each letter produces a unique pattern of activity in the brain, making it easier for the computer to identify what is being written with much greater accuracy and speed.”

Level of flexibility

This system also provides a level of flexibility that is crucial to restoring communication. Some studies have gone as far as attempting direct thought-to-speech BCIs that, while promising, are currently limited by what is possible through recordings from the surface of the brain which averages responses across thousands of neurons.

“Right now, other investigators can achieve about a 50-word dictionary using machine learning methods when decoding speech,” said Dr. Shenoy. “By using handwriting to record from hundreds of individual neurons, we can write any letter and thus any word which provides a truly ‘open vocabulary’ that can be used in almost any life situation.”

Although it is still relatively early days for this technology, it offers the potential to help those who have completely lost the ability to write and speak.

In the future, Dr. Shenoy’s team intends to test the system on a patient who has lost the ability to speak, such as someone with advanced ALS. In addition, they are looking to increase the number of characters available to the participants (such as capital letters and numbers).

The participant is part of a clinical trial, called BrainGate2, which is being conducted by a collaboration of internationally recognized laboratories, universities, and hospitals working to advance brain-computer interface technologies.

 

Reference

Willett, F.R., Avansino, D.T., Hochberg, L.R. et al. High-performance brain-to-text communication via handwriting. Nature 593, 249–254 (2021). https://doi.org/10.1038/s41586-021-03506-2