SmartAlert: Integrating Machine Learning and Alert Triggers into Live Electronic Medical Record Systems, Targeting Low-Yield Inpatient Lab Tests

Abstract This study explores integrating machine learning into electronic medical record systems to predict stability of inpatient lab tests. A ‘smart alerts’ system was developed and tested at Stanford Hospital. The system identifies stable lab results, advising clinicians on test ordering. Live deployment showed desired precision at good recall in predicting test result stability, with suggestions for system optimization identified. This approach may significantly decrease low-yield testing and enhance personalized clinical decision-making.