Ieso Leads the Way in Innovative Mental Healthcare

Ieso Leads the Way in Innovative Mental Healthcare

Ieso’s US clinical lead speaks about AI in mental healthcare.

I had the honor of being a panelist presenter for the World Medical Innovation Forum(WMIF) organized by Partners Healthcare in Boston, Massachusetts. WMIF brings together Ph.D. researchers, engineers and practitioners from around the world who are interested in the theory and applications of healthcare-related Artificial Intelligence and machine learning. With high prevalence rates, poor access to care, minimal outcome data, high cost, high dropout, and low engagement rates, mental healthcare is ripe for AI and machine learning interventions.

The biggest takeaway from this meeting is that Ieso is ahead of the curve with the implementation of AI and machine learning in its therapy platform in the UK. Industry leaders opined about the need for Clinical Decision Support tools and spoke about them theoretically in the future in the field of mental health. Here at Ieso in the UK, we have diagnosis prediction, severity prediction and the likelihood of dropout from treatment. Each of these tools serves to enhance the therapy provided and addresses very real problems that occur in therapy today. With our Therapy Insights Management(TIM) tool we can see what is occurring in the therapy both in real time and in summary afterward. Using Natural Language Processing and the data we have analyzed from a few hundred thousand cases, we are now able to tag therapeutic interactions in different categories such as change mechanism, agenda, homework, etc. In WMIF attendance were leaders and innovators from around the world and there was not a single presenter or participant at the conference who is able to have a pulse on the actual occurrences and utterances in therapy and then tie these back to outcomes.

Another interesting theme at the conference was the need to redefine the clinical phenotypes beyond clinician observation and patient report. Through AI and machine learning the new phenotype should broaden to include breath, voice, facial pattern, activity level, eye gaze, and pupil dilation, movement characteristics, sleep, galvanic skin response, and many pieces of data generated by AI from the patient. Can you believe that Poppy Crumb, Ph.D. out of Dolby Laboratories has developed a way to detect mood from breath?

Finally, the title of the panel I participated in was “Mental Health, Smartphone Apps and the Promise of AI”. The discussion centered around AI-enabled technologies, including smartphone-based tools, that may help close this treatment gap for patients worldwide. This session focused on efforts to develop smartphone apps and other tools, including those designed to help predict patients’ moods and provide cognitive behavioral therapy. If you’d like to view the panel discussion it can be found here: https://www.youtube.com/watch?v=9ItY6uV6iVI&t=506s.

Important themes in this discussion were the need for AI to help us solve some of the challenges in the delivery of mental health care and the importance of evidence-based care driving the apps. As well, the level of human interaction needed to have successful patient engagement and participation in the care delivered via app or other digital interventions was addressed.

Again, Ieso possesses most if not all of the characteristics desired for a successful digital mental health intervention.

The WMIF reinforced that Ieso Digital Health is poised to be a great contributor to the field of mental health. Not only through the provision of written CBT delivered via telehealth care but rather perhaps more importantly through the AI and machine learning insights fed to the therapists and their supervisors which results in a superhuman therapist of sorts. Patients struggling with mental health conditions deserve to have the highest quality mental health care which can only occur in the context of accurate diagnosis, outcomes measurement framework, and best possible strategies to promote engagement and finally it needs to be scalable to help us solve the access problem here in the United States which may happen through AI augmentation.

Written by Jennifer Gentile - Senior Vice President, US Clinical Operations
Published May 15 2019
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