Researchers have begun work analysing doctors’ notes in a huge project which could revolutionise healthcare and treatments.

GPs usually log details, such as symptoms, medical histories and other information, of each patient consultation using a series of codes.

But experts say a lot of vital information that could be used to benefit public health is hidden away in uncoded information written by doctors called “free text”, which has remained untapped in research.

Academics at the University of Sussex and Brighton and Sussex Medical School (BSMS) now aim to analyse thousands of anonymous computerised GPs' notes from the past 15 years.

It is hoped the software will be created to allow researchers to extract "big data" to reveal patterns of disease, diagnosis, treatment and prognosis across the UK.

Professor of computational linguistics John Carroll from the University of Sussex said: "Databases of electronic patient records are used extensively in biomedical research.

"But little attention is paid to the information contained in other text, such as notes or letters, often using shorthand terms and individualised language that is difficult to manage.

"Our research offers something unique, combining medical knowledge, linguistic processing and computer coding software to help us mine medical records and extract and correlate information on disease, health and social or geographic factors affecting public health."

Professor Jackie Cassell, of the BSMS, said the "big data" collected by the team from the records of rheumatoid arthritis patients could provide real benefit in the future.

She said: "When a new treatment becomes available, perhaps through a research trial, it is important that specialists can quickly find all the people who might benefit.

"However, at the moment there isn't a simple way of checking through GP records to see who could be invited to try the new medication.

"Some people with rheumatoid arthritis will be seeing their GP, but won't have a code that clearly identifies that they have rheumatoid arthritis.

"But a systematic survey of 'free text' could identify those patients by, for example, looking for the medications they are taking and noting that they complained of sore hands and feet, which might flag up that the patient has early rheumatoid arthritis.

"The information could then be used to alert GPs and patients that a new trial or medication is available."

The data sets being used come from the Clinical Practice Research Datalink, a £60 million service recently announced by the Medicines and Healthcare Products Regulatory Agency and the National Institute for Health Research.

The records are kept anonymous so that patients cannot be identified and the use of any resulting data will be strictly regulated.

Prof Cassell added: "At the end of the five years, we expect to have a better understanding of how we can use medical big data in the real world to provide alerts and information that will benefit patients, and to be able to feed this back to patients and their doctors and nurses."