Impact of electronic alerts for acute kidney injury on patient outcomes: interrupted time-series analysis of population cohort data.

Background: Automated acute kidney injury (AKI) electronic alerts (e-alerts) are rule-based warnings triggered by changes in creatinine and are intended to facilitate earlier detection in AKI. We assessed the impact of the introduction in the Tayside region of UK in April 2015 of automated AKI e-alerts with an accompanying education programme.

Methods: Interrupted time-series analysis using segmented regression was performed involving all adults with AKI aged ≥18 years who had a serum creatinine measured between 1 April 2013 and 31 March 2017. Analysis evaluated associations of AKI e-alert introduction on rate and severity (Stages 2-3) of AKI as well as mortality and occupied hospital bed days per patient per month in the population with AKI.

Results: There were 32 320 episodes of AKI during the observation period. Implementation of e-alerts had no effect on the rate of any AKI [incidence rate ratio (IRR) 0.996, 95% confidence interval (CI) 0.991 to 1.001, P = 0.086] or on the rate of severe AKI (IRR 0.995, 95% CI 0.990 to 1.000, P = 0.061). Subgroup analysis found no impact on the rate or severity of AKI in hospital or in the community. Thirty-day mortality following AKI did not improve (IRR 0.998, 95% CI 0.987 to 1.009, P = 0.688). There was a slight reduction in occupied bed days (β-coefficient -0.059, 95% CI -0.094 to -0.025, P = 0.002).

Conclusions: Introduction of automated AKI e-alerts was not associated with a change in the rate, severity or mortality associated with AKI, but there was a small reduction in occupied hospital bed days.