SmartAlert - Implementing Machine Learning-Driven Clinical Decision Support for Inpatient Laboratory Utilization Reduction.

April S Liang¹, Fatemeh Amrollahi², Yixing Jiang², Conor K Corbin³, Grace Y E Kim⁴, David Mui⁵, Trevor Crowell⁶, Aakash Acharya⁷, Sreedevi Mony⁷, Soumya Punnathanam⁷, Jack McKeown⁷, Margaret Smith^6,8, Steven Lin^6,8, Arnold Milstein^8,9, Kevin Schulman^1,9, Jason Hom¹, Michael A Pfeffer^1,7, Tho D Pham¹⁰, David Svec^1,11, Weihan Chu^1,11, Lisa Shieh¹, Christopher Sharp⁸, Stephen P Ma¹, Jonathan H Chen^1,2,9,12

¹Division of Hospital Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA.

²Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA.

³SmarterDx, New York, NY, USA.

⁴The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

⁵Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA.

⁶Stanford Healthcare AI Applied Research Team, Stanford University School of Medicine, Palo Alto, CA, USA.

⁷Technology and Digital Solutions, Stanford Health Care, Palo Alto, CA.

⁸Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA.

⁹Clinical Excellence Research Center, Stanford University, Palo Alto, CA, USA.

¹⁰Department of Pathology, Stanford University School of Medicine, Palo Alto, CA, USA.

¹¹Stanford Health Care Tri-Valley, Pleasanton, CA, USA.

¹²Stanford Division of Computational Medicine, Stanford University, Palo Alto, CA, USA.

PubMed PMC DOI PDF

Abstract

Repetitive laboratory testing that is unlikely to yield clinically useful information is a common practice that burdens patients and increases health care costs. Education and feedback interventions have limited success, while general test ordering restrictions and electronic alerts impede appropriate clinical care. We introduce and evaluate SmartAlert, a machine learning-driven clinical decision…

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