Acute kidney injury (AKI) identification for pharmacoepidemiologic studies: use of laboratory electronic AKI alerts versus electronic health records in Hospital Episode Statistics (HES)

PURPOSE A laboratory-based acute kidney injury (AKI) electronic-alert (e-alert) system, with e-alerts sent to the UK Renal Registry (UKRR) and collated in a master patient index (MPI), has recently been implemented in England. The aim of this study was to determine the degree of correspondence between the UKRR-MPI and AKI International Classification Disease-10 (ICD-10) N17 coding in Hospital Episode Statistics (HES) and whether hospital N17 coding correlated with 30-day mortality and emergency re-admission after AKI. METHODS AKI e-alerts in people aged ≥18 years, collated in the UKRR-MPI during 2017, were linked to HES data to identify a hospitalised AKI population. Multivariable logistic regression was used to analyse associations between absence/presence of N17 codes and clinicodemographic features. Correlation of the percentage coded with N17 and 30-day mortality and emergency re-admission after AKI were calculated at hospital level. RESULTS In 2017, there were 301 540 adult episodes of hospitalised AKI in England. AKI severity was positively associated with coding in HES, with a high degree of inter-hospital variability-AKI stage 1 mean of 48.2% [SD 14.0], versus AKI stage 3 mean of 83.3% [SD 7.3]. N17 coding in HES depended on demographic features, especially age (18-29 years vs. ≥85 years OR 0.22, 95% CI 0.21-0.23), as well as sex and ethnicity. There was no evidence of association between the proportion of episodes coded for AKI with short-term AKI outcomes. CONCLUSION Coding of AKI in HES is influenced by many factors that result in an underestimation of AKI. Using e-alerts to triangulate the true incidence of AKI could provide a better understanding of the factors that affect hospital coding, potentially leading to improved coding, patient care and pharmacoepidemiologic research.