Researchers from Keele and Oxford universities have developed a new tool for doctors to identify patients at high risk of serious falls.

The tool could have a big impact on the way older patients are managed in primary care, improving targeting of drug treatment and fall prevention strategies for high-risk individuals.

The research, published today in the BMJ and funded by the Wellcome Trust, Royal Society, and National Institute for Health and Care Research (NIHR), was led by researchers from Keele University’s School of Medicine and the Nuffield Department of Primary Care Health Sciences, University of Oxford.

The study used 20 years’ worth of data from 1.7 million anonymised healthcare records to develop the tool, and then checked its accuracy against a separate database of almost 4 million healthcare records.

Falls can have a significant impact on patients’ quality of life. For example, in people over 65, fractures which result from falls can often signal the point at which they may no longer be able to live independently in their own homes or without care.

In England, each year, around 235,000 hospital admissions for people over 65 are due to falls, costing the NHS an estimated £2.3 billion.

Lucinda Archer, lead author on the publication and Lecturer in Biostatistics at Keele University, said: "We discovered that a history of previous falls, having a diagnosis of multiple sclerosis, heavy alcohol consumption, a high deprivation score, and prescribed drugs were all strong predictors of fall risk, conditional on other variables in the model.

“The tool we developed considers all these factors, and more, to determine an individual’s risk of falling over the next one to ten years. We found the new tool's predictions had larger clinical utility than other strategies for differentiating between groups of high and low risk patients, as defined by clinically relevant risk thresholds.”

Dr Constantinos Koshiaris, Senior Medical Statistician in the Nuffield Department of Primary Care Health Sciences at the University of Oxford, who developed the tool, said: “In the past, we have struggled to identify people at risk of falling in the community. Previous falls-risk tools were not very accurate and, in some cases, had methodological flaws. Our new 'STRATIFY-Falls' tool can predict which patients are most at risk of falling in the next one to ten years. This could allow GPs to provide more personalised care and target falls prevention strategies for patients, such as exercise-based interventions or drug reviews.”

Prof Richard McManus, practising GP and Professor of Primary Care Research at the Nuffield Department of Primary Care Health Sciences, University of Oxford said: "GPs often have to balance the risks and benefits of medications for specific conditions, such as high blood pressure, against the potential risk of adverse events such as falls. Having reliable tools to estimate people's individualised risk of falling and change their medication to lower this risk would be very welcome. This kind of tool could in time be built into GP records systems to automatically flag such patients."

The tool is now freely available to other researchers for further testing and can be downloaded from: https://process.innovation.ox.ac.uk/software/. However, the tool is not quite ready for GPs to use in clinical practice, as the team first has plans to test it in a new randomised controlled trial.

Prof McManus added: “In 2023, we will begin recruiting over 3,000 participants who are at high-risk of falls to the NIHR-funded OPTIMISE2 trial. We will use the STRATIFY-Falls tool to identify these potential participants and then follow them up to see if they experience fewer falls after deprescribing their blood pressure lowering treatment.”