Acute kidney injury identification for pharmacoepidemiologic studies: Use of laboratory electronic acute kidney injury alerts versus electronic health records in Hospital Episode Statistics.

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.