Electronic Frailty Index

The following questions and answers may be useful to general practitioners requiring more information about identifying frailty and the role which the electronic Frailty Index (eFI) plays in the GP contract.

If you need any more information, please email us: england.communityservices1@nhs.net

General practice is required to:

  • Identify all patients aged 65 and over who may be living with moderate or severe frailty;
  • For patients identified as living with severe frailty (around 3% of over 65s), undertake an annual medicines review, a falls risk assessment, if clinically appropriate, and promotion of the enriched Summary Care Record (SCR);
  • For patients identified as living with moderate frailty (around 12% of over 65s), consider undertaking a medicines review, a falls risk assessment if clinically appropriate, and promotion of the enriched SCR.

The avoiding unplanned admissions enhanced service (AUA ES) has been discontinued and funding associated with it placed into the core contract.  This new requirement will affect a smaller proportion of patients across England and has more targeted evidence based interventions.

In addition:

  • All these requirements can be delivered by any suitable clinician. Also where the practice is working with a wider health care team, (for example community pharmacy or as part of a network of practices) they would be able to deliver this care on behalf of the practice.
  • Whilst clinical judgement is crucial to confirm identification of frailty, practices can use automated tools such as the electronic Frailty Index (eFI) to initially identify populations of people likely to be living with varying degrees of frailty.
  • The expectation is that, for most patients identified as living with severe frailty, a specific visit for an assessment will not be needed as they will be seen in year as part of routine consultations

The electronic frailty index (eFI) uses the existing information within the electronic primary health care record to identify populations of people aged 65 and over who may be living with varying degrees of frailty. When applied to a local population it provides opportunity to predict who may be at greatest risk of adverse outcomes in primary care as a result of their underlying vulnerability.

The eFI uses existing electronic health records and a ‘cumulative deficit’ model to measure frailty on the basis of the accumulation of a range of deficits. These deficits include clinical signs (e.g. tremor), symptoms (e.g. vision problems), diseases, disabilities and abnormal test values.

It is made up of 36 deficits comprising around 2,000 Read codes. The score is strongly predictive of adverse outcomes and has been validated in around 900,000 patient records.

It presents an output as a score indicating the number of deficits that are present out of a possible total of 36, with the higher scores indicating the increasing possibility of a person living with frailty and hence vulnerability to adverse outcomes.

The contract requires general practices to identify populations at risk of frailty by using an appropriate tool. NHS England do not require any particular tool to be used.  However, as eFI is available in all GP practices, NHS England anticipate this being used frequently as it:

  • has been externally validated using routine primary care data and its use is recommended in NICE Guideline 56 on Multimorbidity;
  • is available in all GP practices and therefore promotes consistency;
  • uses existing GP data and therefore requires no additional resource.

The eFI is not a clinical diagnostic tool; it is a population risk stratification tool which identifies groups of people who are likely to be living with varying degrees of frailty but it is not able to do this for specific individuals. Therefore, when the eFI identifies an individual who may be living with severe or moderate frailty, direct clinical assessment and judgment should be applied to confirm a diagnosis.

Some GP practices may have batch-coded a Read code diagnosis of frailty based solely on an eFI score, without clinical judgement confirming a diagnosis. This may result in inappropriately targeted interventions and increased workload for a practice (the eFI, for example, has relatively high sensitivity and low specificity so tends to over-identify people living with frailty).

In response NHS England has issued a statement confirming the importance of clinical judgement.

There are 2 main options:

  1. A batch delete process followed by repeating the process in line with the guidance (i.e. applying clinical judgement before coding). If choosing this option it may be helpful to seek guidance from the relevant software provider.
  2. A clinical review of all people identified (and therefore coded) with severe frailty and removing the read code of severe frailty from those that were incorrectly identified. If practices have also batch-coded moderate, mild and/or fit then they may wish to review this too.

In terms of choosing between the 2 options, this depends on the list size and how quickly it is possible to go back through the list and do the clinical validation.

Based on the validation of the eFI, on average around 3% of over 65s will be identified as potentially living with severe frailty.  However, in some practices this number may be significantly higher. There are three main reasons for this:

  • Previous coding history – as the eFI is based on Read code data, practices that have undertaken activities resulting in increased coding of certain deficits (particularly those focused specifically upon care and support for older people) may increase eFI scores and therefore the proportion of patients identified with severe frailty. However, it is also likely that in such cases practices will already have greater clinical awareness of this cohort, which will facilitate their clinical validation of frailty diagnoses.
  • Completeness/continuity of electronic patient records – where electronic Patient Records are more complete, for example because they have been in place for a longer time and are intact on a single software system, this can increase the likelihood that particular deficits are coded and therefore the proportion of patients identified with severe frailty.
  • Demographics – where practices have a larger proportion of patients in the oldest age groups, or living in areas with high levels of deprivation, they are likely to identify a greater proportion of people living with severe frailty.  This is like to be particularly significant if a practice has a large number of registered patients who live in care homes.

The aim of this approach is to support patients to live well for longer. We expect that this approach will help reduce unwarranted hospital admissions as it will reduce the risk of people experiencing two of the major frailty syndromes; falls and adverse effects of medication, which often result in hospital admission. It will also ensure that those most at risk of unwarranted outcomes from admission to hospital are identified early in their admission and their care appropriately tailored to meet their individual needs and preferences.

In addition, the enriched Summary Care Record can help ensure that people accessing care anywhere benefit from the professionals involved in their care having access to essential details about their healthcare. This includes information on whether the person is living with frailty or other long term conditions, their healthcare needs and personal preferences.

Locally, the numbers of people identified with severe frailty will vary depending on factors including local demographics.  Nationally, we expect:

  • Around 3% of over 65s, or 297,170 older people, with severe frailty identified and targeted with falls assessment and medications review and are helped to stay well and reduce inappropriate treatment burden.
  • Up to 15% of over 65s, or 1,485,850 older people, will benefit from the availability of enriched summary care records supporting the sharing of safe, effective and efficient care across different settings.