eFI receives ‘Innovation Award’ from Royal College of Physicians
The electronic frailty index (eFI) continues to be recognised as an outstanding IT innovation after its win at the Royal College of Physician’s Excellence in Patient Care Awards last week.
The eFI won in the ‘innovation’ category at the awards which took place on Thursday 16thMarch, where it was also revealed that the eFI research paper was the most downloaded and cited paper in the Age and Ageing Journal in 2016.
The awards ceremony, which was held at Manchester Town Hall, celebrated outstanding contributions to providing excellent patient care. This is the second accolade the eFI has received, after winning in the ‘Healthcare IT Product Innovation’ category at the EHI Awards in September last year.
This latest success comes at a time when eFI has also been recognised as a recommended tool to identify frail patients in the 2017/18 GP contract. The new GP contract, announced by NHS England in February, includes the identification and management of patients with frailty from July 2017. It encourages the use of an appropriate tool, such as the eFI, to be used to identify patients aged 65 and over who are living with moderate and severe frailty.
The eFI project was a collaboration between the University of Leeds, TPP, the University of Birmingham, the University of Bradford, and Bradford Teaching Hospitals NHS Foundation Trust. The tool was developed using rich anonymised data provided from two health and care databases, including ResearchOne.
The index enables the calculation of a frailty score, and is available as innovative functionality within SystmOne. This can be used to identify people with mild, moderate or severe frailty. A higher eFI score identifies people at increased risk of care home admission, hospitalisation, and mortality.
On giving the accolade, Royal College of Physicians commented on the reasons for the eFI’s win:
“The eFI represents a major, innovative advance in the care of older people because, for the first time, it enables identification of frailty using existing primary care data without the need for a resource-intensive clinical assessment.”