Connecting and Predicting Psychiatric Patients in Mental Health System to Criminal Offenders in Criminal Justice System

Author: C. Charles Lin

Abstract Concept: (1) To learn the behaviors and healthcare of at-risk psychiatric patients, utilizing mobile technology and new sensors safeguard with heightened security, and use analytics tools to  insight, predict,  and coordinate psychiatric healthcare. (2)To identify at-risk psychiatric patients using artificial intelligence tools, and to connect with existing criminal offending records to provide objective data-driven results for criminal justice system.

Background: As the startup Velera Health demonstrated, psychiatric patients’ co-morbid medical and/or behavioral health could be monitored with patients’ smart phones. Mobile technology could collect active and passive data and analytics can analyze and predict behavioral change. A digital case management platform could enable preventive rather reactive behavioral healthcare. Law Professor Ann Milgram of NYU, former Attorney General of New Jersey, urged criminal justice system practitioners to use analytic tools, and urged the researches on connecting offenders in criminal justice system to their behavioral/psychiatric healthcare system as patients. Methods: Obtain the at-risk psychiatric patients’ informed consent under HIPPA regulations. They are required to carry smart phones, or connected wearable devices with sensors. Active and passive data (including drug-taking history, and online search history, etc) are collected and use analytics to capture measurements. Machine learning of data from the criminal justice centers, to break the silos of criminal justice system. Under HIPPA regulations, use AI tools, including machine learning, to connect psychiatric patients with data from criminal justice, and gain insights of patients’ backgrounds and behaviors in holistic views.