Current best practice in assessing psychiatric clinical states relies on frequent clinical interviews with trained professionals. However, there are not enough clinicians to monitor patients as often as necessary, and relapse or suicide can follow even a few days after a clinician-patient meeting, highlighting the limits of intermittent clinical evaluation. Emerging technologies can automatically track and transmit key patient data, including information about affect, activation level, and suicidal ideati on, and generate alerts to initiate human intervention. Data capture can be inobtrusive (e.g., wristband monitors and smartphones). Body movement and non-verbal aspects of speech can form robust indicators of psychomotor activation and affect, while autom atic content analysis of speech can detect morbid ideation and changes in symptoms of depression and schizophrenia. We propose to assemble a remote monitoring system from currently available state-of-the-art technical elements, configure them to capture a nd transmit both passive-continuous and elicited-episodic data streams from outpatients. The goal is to implement a system that tracks the psychological state of psychiatric outpatients and when appropriate generates alerts that indicate that clinical sta ff should initiate communication with that patient. The potential to predict relapse risk before it occurs can avoid many medical crises and suicide-attempts/suicides. The research program is designed to answer three questions about the feasibility of rem ote monitoring of such patients: (i) Can available technology be configured to support such monitoring with sufficient accuracy to be useful? (ii) Will some portion of the outpatient psychiatric population tolerate such monitoring and comply with its beha vioral requirements? (ii) Can such monitoring be implemented effectively that better serves the outpatient population, while reducing overall costs?
Project leader: Brita Elvevåg
Category: Helse Nord RHF
Institution: UNIVERSITETSSYKEHUSET NORD-NORGE HF