A national algorithm, standardising the definition of AKI has now been agreed. This provides the ability to ensure that a timely and consistent approach to the detection and diagnosis of patients with AKI is taken across the NHS.
This algorithm has been endorsed by NHS England and it is recommended that the algorithm is implemented across the NHS. When integrated into a Laboratory Information Management System (LIMS) the algorithm will identify potential cases of AKI from laboratory data in real time and produce a test result. The laboratory system will then send the test result, using existing IT connections to patient management systems.
- AKI algorithm
- AKI algorithm FAQs
- AKI patient safety alert
- Transmitting AKI warning stage data to the UK Renal Registry
Presentations and posters from the AKI Scientific Day – 19th June 2014
The following presentations were delivered at the AKI Programme Detection Stream’s “Scientific Day” on 19th June. Dr Andy Lewington describes the clinical context of AKI and the potential impact of preventing AKI. AKI is seen as one of several medical conditions where harm to patients can be avoided by relatively simple measures. This presentation also provides the background to the patient safety alert (NHS/PSA/D/2014/010) issued by NHS England on 9th June 2014. Dr Robert Hill describes the AKI programme and how the consensus algorithm for detecting AKI was agreed and how this has become a core part of the AKI programme. He introduces the purpose of the day by pointing out the many advantages of having the same method for detecting AKI in all NHS Trusts across the UK.
The following posters were invited from Trusts invited to showcase their approach they have taken with automated live e-alerting systems for AKI. The clear message from this day was that the NHS must harmonise its AKI detection systems to a system based on a single NHS England detection algorithm and a single universal messaging system using test results generated in the Laboratory Information Management System. However the AKI programme is keen not to stifle innovation and to learn from the good practice already in place in the NHS. The content of the posters will contribute to future versions of the algorithm which will change when evidence supports it to do so.