University of Bristol

ILD73

From 9th March 2015, NHS England required laboratories in England to run an algorithm to detect cases of acute kidney injury (AKI), generate alerts for clinical teams and submit data on all cases of AKI to the UK Renal Registry. How each laboratory has implemented this algorithm in its local laboratory information management system is unknown and to date no work has been undertaken to examine this. Since these alerts are being transmitted to clinicians caring for these patients, and being used to compare AKI rates between clinical commissioning groups, it is important to ensure the algorithm is working accurately and consistently. Acute kidney injury alerts are generated using changes in levels of creatinine. There is no consensus about how to identify the baseline creatinine level against which these changes are measured to create the alert. We will develop code to identify cases of AKI using routine laboratory data, and compare our results with the alerts generated by individual laboratories and transmitted to the UKRR. We will look at the reasons for any differences. We will use creatinine values from different time points prior to the identification of acute kidney injury to determine the baseline time point that is most strongly associated with the risk of developing chronic kidney disease and the risk of dying. Examining the implementation of the AKI algorithm in different laboratories will allow comparisons of AKI rates between different areas in the UK. Improving the algorithm and its implementation will benefit patients by better identifying AKI and improving how quickly and effectively care is provided.

15/09/2020