Heterogeneous Effect of Automated Alerts on Mortality

We analyzed data from 13,483 hospitalized patients with acute kidney injury (AKI) from three randomized controlled trials to assess the heterogeneous effects of automated electronic alerts on 14-day mortality. We modeled and predicted individualized alert effects on a subset of the ELAIA-1 patients and validated it internally on ELAIA-1 holdout patients and externally on ELAIA-2 and UPenn trial patients. 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 may have been preventable if alerts were restricted to likely beneficiaries. Machine-learning based meta-analysis identified reduced mortality with alerts among patients with higher blood pressures and lower predicted risk, but increased mortality in non-urban and non-teaching hospitals. Provider responses to alerts varied across subgroups. These findings suggest that tailoring alerts to patient phenotypes may improve outcomes and support the need for a prospective trial of individualized alert strategies.

https://clinicaltrials.gov/ct2/show/NCT02753751 and https://clinicaltrials.gov/ct2/show/NCT02771977.