Research Highlights | 27
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 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 four 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 .”
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