Aridhia risk calculation app could save NHS hospitals millions

Sarah Spickernell
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Hospitals are penalised if a person is readmitted within 30 days (Source: Getty)
A new app designed by health informatics company Aridhia could save the NHS millions of pounds by cutting patient readmissions.
Called PARR30 Edition, it uses a risk calculation model to predict the likelihood of a patient being readmitted after discharge, allowing for extra precautions to be taken if this is deemed likely.
More specifically, it aims to prevent readmissions occurring within 30 days, since a policy introduced by former health secretary Andrew Lansley in 2011 means hospitals are paid for initial treatment but they are not paid again if a patient is brought back in with a related, avoidable problem within this time period.
The scheme was introduced to increase the responsibility of hospitals for looking after their patients, and also to counteract the negative effects of another initiative incentivising hospitals to cut lengths of stay, as this resulted in an increase in the number of emergency readmissions.
But since its introduction, Lansley's policy has led to an estimated £390m being withheld from English hospital budgets. The hope is that the app will increase understanding of readmission risk and therefore make more of this money available.
The predictive mathematical model is based on an anonymised sample of NHS England hospital admissions between April 2008 and 2009. It processes 17 pieces of information that can be obtained from hospital information systems or from the patient’s notes, such as date of birth, detail on recent admissions, and diagnosis of any major health conditions.
Aridhia is currently looking to partner up with NHS Trusts so it can take the app beyond the theoretical stage and put it use in a clinical setting.
David Sibbald, CEO of Aridhia, said: “PARR30 is a brilliant example of how anonymised data can be put to use in a practical way to improve the outcomes of patients across the NHS and is the first App launched in our data safe haven.”

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