Each year in England, falls cause around 235,000 hospital admissions for people over 65, costing the NHS an estimated £2.3billion.
Dr Constantinos Koshiaris of Oxford University, who has developed a new tool for doctors to identify patients at high risk of serious falls, said: “In the past, we have struggled to identify people at risk of falling. Previous fall-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 10 years.
“This could allow GPs to provide more personalised care and target fall-prevention strategies for patients, such as exercise-based interventions or drug reviews.”
The risk of a serious fall increases as people age and develop chronic medical conditions. There are many factors influencing this risk, including pre-existing illness or frailty, which may be difficult for doctors to influence.One factor they can control, however, is the amount and type of medications prescribed, such as drugs to lower blood pressure (antihypertensives). These can be effective in preventing diseases like stroke and heart attacks.
But without careful monitoring, these drugs may lower blood pressure too much, causing a temporary drop in blood flow to the brain, leading to fainting and falling. This is especially common when standing from sitting.
Falls can have a significant impact on quality of life. For example, in people over 65, fractures resulting from falls often signal the point at which they’re no longer able to live independently in their own homes.
The researchers used a database of over 1.7 million healthcare records from GP surgeries in England between 1998 and 2018, the Clinical Practice Research Datalink (CPRD). They identified over 60,000 people aged 40 and up who had at least one high blood pressure measurement and had at least one serious fall.
They used this to create a model (tool) of the factors that might predict people’s risk of falling following a
high blood pressure measurement, others being gender, age, ethnicity, alcohol usage, medications and smoking.
They tested the tool against a second set of CPRD data for the same period, which include nearly four million records.
Dr Lucinda Archer, lead author from Keele University says: “After some minimal tweaks, we found the new tool’s predictions were very accurate at differentiating between groups of high- and low-risk patients.”
Preventive medicine at its best.
