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Heterogeneous Effect of Automated Alerts on Mortality.

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    Automated electronic alerts for acute kidney injury (AKI) show varied effects on patient mortality. Tailoring alerts to individual patient profiles may improve outcomes and reduce preventable deaths.

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    Area of Science:

    • Nephrology
    • Medical Informatics
    • Clinical Trials

    Background:

    • Acute kidney injury (AKI) is a common and serious condition in hospitalized patients.
    • Automated electronic alerts are used to prompt clinicians regarding potential AKI.
    • The effectiveness of these alerts can vary significantly among patients.

    Purpose of the Study:

    • To assess the heterogeneous effects of automated electronic alerts on 14-day mortality in hospitalized patients with AKI.
    • To model and predict individualized alert effects on patient outcomes.
    • To identify patient subgroups that benefit or are potentially harmed by alerts.

    Main Methods:

    • Analysis of data from 13,483 hospitalized patients with AKI across three randomized controlled trials.
    • Development and internal/external validation of a model predicting individualized alert effects.
    • Machine-learning based meta-analysis to identify factors influencing alert effectiveness.

    Main Results:

    • Patients predicted to benefit from alerts had significantly lower mortality compared to those predicted to be harmed (p-interaction<0.05).
    • In external cohorts, 43 deaths were potentially preventable by restricting alerts to likely beneficiaries.
    • Alerts reduced mortality in patients with higher blood pressure and lower predicted risk, but increased it in non-urban/non-teaching hospitals.

    Conclusions:

    • Automated electronic alerts for AKI have heterogeneous effects on mortality.
    • Tailoring alert strategies to patient phenotypes may improve clinical outcomes.
    • A prospective trial of individualized alert strategies is warranted to optimize AKI management.