A simple tool can do much to help cut emergency hospitalisations. David Lyon and Hannah Chellaswamy explain
Reducing medical emergency is a priority, both because of the escalating costs of emergency hospital admissions and the negative impact hospitalisation can have on long-term health.
The majority of those admitted to hospital as an emergency are older people, many with several medical conditions. The over-65 age group occupies nearly two-thirds of general hospital beds and accounts for half of the recent growth in emergency admissions.
If emergency admissions are to be reduced, better management of underlying long-term conditions and more targeted support is needed.
Several initiatives have tried to stem this rising tide of admissions. However, the impact has been limited, partly because there was no easy way of identifying those most likely to benefit. Clearly there is an urgent need to research better ways of identifying patients at high risk of admissions.
The research team at Castlefields health centre in Runcorn set out to develop and validate a tool that could easily be completed by patients or applied quickly in a clinical setting, and could produce an immediate risk score. Active admission avoidance schemes could then be deployed without delay to those at highest risk of admission.
The study took place in Widnes and Runcorn in the North West, with a population of 125,000 served by 17 GP practices. A total of 3,649 questionnaires were sent out, and 3,032 completed..
A model to develop a risk algorithm was devised, based on the questionnaire responses and whether there was an emergency admission within the subsequent 12 months.
The EARLI questions
The EARLI (emergency admission risk likelihood index) research culminated in six questions, each weighted for a predictive risk score.
Participants were asked to start with a score of 10, adjusting the score (up or down) according to instruction for 'yes' answers and making no change for 'no' or 'don't know'. The questions covered heart problems; leg ulcers; mobility; memory; hospital admissions; and general health. The six elements are ranked entirely on the patient's own view of their health.
The result of the study were as follows:
- 6 per cent of the population scored in the highest-risk range of more than 20. Of those, 55 per cent were admitted in the subsequent 12 months. Focusing resources on this small group to prevent admissions could reduce the total number of admissions for older people across a population by nearly 20 per cent;
- 7.5 per cent of the population scored 15-19 points, and 47 per cent were admitted. If resources allowed, this would be the next group to target;
- 75 per cent, a vast majority, scored less than 10 and only 17 per cent of these were admitted.
The advantages and implications of EARLI are significant. It does not require a retrospective, time-consuming trawl through hospital and primary care databases, which are often incomplete and out of date.
It can be applied to large numbers of people easily and cheaply, providing a simple way to identify a small proportion of 'high-risk' patients for admission avoidance schemes.
EARLI can be applied in any primary, secondary or social care setting, giving a real-time prediction of the risk of admission in the subsequent 12 months. The EARLI questionnaire has already been used successfully by the primary care trust sites working with the Improvement Foundation, a not-for-profit organisation that works to develop capacity and continued improvement in public services.
EARLI complements disease-specific approaches as it is not resource intensive. It can be completed while patients are in waiting rooms, queuing for their flu vaccination or during any consultation.
With just six questions and a simple scoring system, the questionnaire takes only a few moments. As it is designed for self-completion, no training is required, so carers, receptionists, relatives or friends can complete it.
EARLI can be used in research to identify people on whom to test preventive interventions, and in general practice to target scarce resources, such as community matrons, more effectively on those most likely to benefit.
Dr David Lyon is a GP at Castlefields health centre, Runcorn, and a consultant to the Improvement Foundation. Hannah Chellaswamy is deputy director of public health at Sefton primary care trust.