Clinical Implementation of an AI Early Warning System Algorithm: Lessons Learned.
- Resource Type
- Academic Journal
- Authors
- Meehan AM; Department of Medicine, Mayo Clinic, Rochester, MN, USA.; Core MA; Department of Information Technology, Mayo Clinic, Rochester, MN, USA.; Ross JM; Department of Information Technology, Mayo Clinic, Rochester, MN, USA.; Rahman PA; Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.; Borah BJ; Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.; Caraballo PJ; Department of Medicine, Mayo Clinic, Rochester, MN, USA.; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
- Source
- Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform
- Subject
- Language
- English
The Deterioration Index (DI) is an automatic early warning system that utilizes a machine learning algorithm integrated into the electronic health record and was implemented to improve risk stratification of inpatients. Our pilot implementation showed superior diagnostic accuracy than standard care. A score >60 had a specificity of 88.5% and a sensitivity of 59.8% (PPV 0.1758, NPP 0.9817). However, acceptance in the clinical workflow was divided; nurses preferred standard care, while providers found it helpful.