Researchers have developed a tool to help doctors better identify patients at high risk of serious falls.
While most likely to be used for the better health management of people who are beyond working age, the tool could feasibly have applications for older workers, especially those aged over 65, those working alone, or those with conditions such as high blood pressure.
The ‘STRATIFY-Falls’ tool can predict which patients are most at risk of falling in the next one to 10 years and has been developed by the Nuffield Department of Primary Care Health Sciences at the University of Oxford.
As Dr Constantinos Koshiaris, the senior medical statistician 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. This could allow GPs to provide more personalised care and target falls prevention strategies for patients, such as exercise-based interventions or drug reviews.”
In England each year it is estimated around 235,000 hospital admissions for people over 65 are due to falls, costing the NHS an estimated £2.3bn.
The researchers used a database of more than 1.7 million healthcare records from GP surgeries in England between 1998 and 2018, the ‘Clinical Practice Research Datalink’ (CPRD), to create the tool.
By linking this to data from hospitals, they were able to identify more than 60,000 people aged 40 and upwards who had at least one high blood pressure measurement and had experienced at least one serious fall during the study period (in other words, which had required hospital treatment or led to death).
They used this information to create a model of the factors that might predict people’s risk of falling in the next 10 years following a high blood pressure measurement. This included factors such as gender, age, ethnicity, prescribed medications, alcohol usage, and smoking
Dr Lucinda Archer, lead author on the publication and lecturer in biostatistics at the Centre for Prognosis Research at the School of Medicine at Keele University, said of the tool: “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.”
Professor Richard McManus, practising GP and professor of primary care research at the Nuffield Department of Primary Care Health Sciences at the University of Oxford, added: “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,” he said.
During 2023, more than 3,000 people will be recruited on to a research project looking at the management of people at high risk of falls, and the tool will be used to identify potential participants and then follow them up, highlighted Prof McManus.
The tool will in time be made available to GPs but is currently only available to other researchers for further testing.