Description
Integrating care for mental health illnesses into primary care has been proven to improve quality and decrease utilization. Primary care providers (PCP) at Intermountain Healthcare currently use a 9-page questionnaire to evaluate the complexity level for mental health patients. They are challenged with a large amount of patient-reported information and a paper-based scoring guideline that is not integrated in the clinical workflow. This study experimented with Machine Learning techniques to automatically suggest complexity levels and its contributing components using both patient-reported data and EHR data to guide optimal treatment plan and care team allocation.
Learning Objective: identify Machine Learning technologies that will help physicians treating mental health patients with different needs
Authors:
Shan He (Presenter)
Intermountain Healthcare
Peter Haug, Intermountain Healthcare
Kathryn Kuttler, Intermountain Healthcare
Brenda Reiss-Brennan, Intermountain Healthcare
Presentation Materials: