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Eleven per cent of all patients admitted to hospital experience 'an adverse effect' such as a diagnostic error, operative mistake or drug reaction, of which about half are judged to be preventable, according to a study carried out by the Clinical Risk Unit at University College London. One third of these events lead to disability or death. The aim of Isabel is to help reduce these figures.
One of the most likely explanations for these worrying statistics stems from the inherent structure of the NHS. Namely, that it is not the doctors with most experience in diagnosing acute conditions who are likely to see a sick child when they first arrive at a GP surgery or A&E, but rather the primary care staff who have least experience when it comes to recognising the rarer complications of certain illnesses (see 'Inverted Pyramid of Knowledge' on page 18).
Consequently
many illnesses are:
- not
being recognised in time
- not
being treated in time and/or not receiving appropriate treatment
This
can result in further serious complications and in some cases
unnecessary fatalities, not to mention additional costs in
treatment and litigation to the NHS.
a)
THE NEED FOR A SPLIT-SECOND DIAGNOSIS
The
need for rapid diagnosis cannot be under-estimated. When a
child is acutely ill, seconds count. Misinterpreting seemingly insignificant symptoms through lack of experience (or increasingly through overwork) can make the difference between life and death. Frequently, it is only when a condition is recognised as serious that a senior doctor is summoned.
Many acute illnesses share symptoms with harmless conditions, hence it is all too easy for a recently qualified doctor not to recognise a very sick child. Even senior doctors don't always have the answer at their fingertips and have to waste valuable hours reading through lengthy medical texts.
Isabel
has been designed to provide that crucial support in seconds.
b)
THE NEED FOR CLINICAL ALGORITHMS
For
an acutely ill child, it is the first hour of treatment which
is vital to the chances of a good outcome.
Even when a condition is recognised quickly, vital time can be lost in
deciding on the appropriate treatment. The structure of the NHS is such
that only a very few conditions have nationally recognised treatment
algorithms. At present these algorithms normally exist as posters or books and are therefore often in the wrong place when needed, or even out-of-date.
Isabel also comprises a range of treatment algorithms commissioned and compiled by acknowledged experts in each specific field. For instance, the algorithm for the treatment of meningococcal disease (produced by specialists at St Mary's Hospital, Paddington) would be available instantly to an A&E unit in a much smaller hospital which may not otherwise have access to specialist experience. The doctors there could then benefit from the experience of the specialists in meningococcal disease at St Mary's, possibly making the difference between life and death.
c)
THE NEED TO INCREASE THE USE OF INFORMATION
TECHNOLOGY WITHIN THE NHS
The
Health Service, although a highly knowledge-intensive sector, has traditionally been very slow and fragmented in its use of technology.
To date, the main use the NHS has made of clinical decision support has been through NHS Direct (the telephone and web-based medical advisory service which advises patients on the most suitable course of action). NHS Direct is currently developing a face-to-face version to be used in the Accident and Emergency setting, called CAS (Clinical Assessment System), and is interested in integrating Isabel into this system.
However, in the future the NHS faces an increasing shortage of skilled personnel as demands on its service become greater and regulations, such as the Working Time Directive, reduce the amount of hours that doctors are able to work. It is likely that the NHS will make increasing use of less highly trained staff to carry out the work currently performed by doctors. In this situation clinical decision support tools like Isabel will play a vital role in enabling, for example, nurse practitioners to carry out some of the tasks traditionally carried out by doctors.
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