Health systems nationwide are rapidly adopting AI in healthcare, with behavioral health seeing results such as reducing clinician burnout and creating tools for caregiver emotional support.
Arjun Nagendran, PhD, and Scott Compton, PhD, researchers at Chicago-based Ann & Robert H. Lurie Children’s Hospital, have implemented four AI models aimed at closing gaps in mental healthcare by improving access, safety and personalization. All models were developed in clinical settings and require governance approval prior to rollout, according to a Jan. 28 news release.
Here are the four AI models to know:
- The Neuropsychology Outcome Reporting Assistant reduces clinician report generation from three to six hours to just three minutes. It uses multi-source patient data and flags low-confidence areas for manual review.
- Medication Information for Neuropsychological Disorders delivers context-specific medication guidance to patients and families. The tool targets about 30% of clinician time spent answering repetitive medication queries and has undergone 12 months of experimentation and study.
- The Suicide Assessment Fidelity Evaluator provides real-time quality assessments of suicide safety plans. It can reduce review time by 70% and may help predict a patient’s return to the emergency department.
- The Suicide Prevention AI Role-play Kit uses dual AI models to simulate patient scenerios and offer feedback to clinicians during suicide prevention training. It is still in development.
