The new technologies transforming psychiatric practice and patient outcomes

Data-driven approaches to psychiatric diagnosis and practice fueled by the abundance of information provided by smart devices and sensors together with massive supercomputing power enabling the development of previously unimaginable artificial intelligence (AI) and machine learning tools and techniques are revolutionizing patient outcomes. Psychiatric practice is undergoing a technological transformation, stated Dr Arshya Vahabzadeh, from Massachusetts General Hospital Psychiatry Academy, to the large audience attending the welcome session at Psych Congress 2019.

Many technologies are contributing to improved psychiatric practice and outcomes, and are maturing at different stages, explained Dr Vahabzadeh:

  • smartphone apps, telemedicine, digital therapies and wearable sensors are already used in practice
  • social media tools, virtual reality, electronic health record data, artificial intelligence (AI) techniques and natural language processing will contribute to practice over the next 5 years
  • augmented reality, genotyping, and neuroimaging will become more mainstream within the next 10 years

Data will drive future practice and improve diagnosis

The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides 227 different symptom combinations for diagnosing major depressive disorder (MDD), said Dr Vahabzadeh.

A data driven framework for MDD will refine the diagnosis and enable identification of different subgroups

Any two people with MDD can have completely different manifestations and symptoms, and apparently very different forms of MDD. In addition, MDD is often comorbid with anxiety and personality disorders and alcohol use disorders, which do not currently contribute to the diagnostic assessment.

A data driven framework for brain function is now possible; because never before have we been so connected with smart devices or had so much computing power, said Dr Vahabzadeh.

Furthermore, a data driven framework for brain function is more reproducible than an expert driven framework for brain function and an expert driven framework for mental illness (i.e., the DSM).1

Chatbots and telepsychiatry are increasing access to psychiatric interventions

Nearly one in five people in the United States was living with a mental illness in 2017, and less than 50% of these people receive mental health care, said Dr Vahabzadeh.2

Increasing access to psychiatric interventions for the many people not receiving mental health care

Telepsychiatry, also referred to as a digital therapist, is now addressing this gap and is an effective, efficient alternative for direct psychiatric consultations. Not only does telepsychiatry improve access to psychiatric interventions, but it also makes better use of psychiatrist time and reduces travel times and costs for both patients and clinicians, explained Dr Vahabzadeh

Chatbots are also increasing patient access to psychiatric intervention. Preliminary evidence is demonstrating that these AI-powered nonhuman conversational partners with human-like dialogues and behaviors are a feasible, engaging, and effective way for delivering cognitive behavioral therapy (CBT) to populations with or at high risk of MDD, anxiety, schizophrenia, bipolar disorder, and substance abuse disorders.3,4

However, when chatbots are compared with human intervention and the patients know which is what, patients prefer the human intervention.5

An emotionally aware chatbot that analyses facial expressions to become more empathic has now been developed, although this is not yet in clinical use.

Digital hot topics

Psychiatric practice is undergoing a technological transformation

Digital hot topics that Dr Vahabzadeh believes will play an increasing role in improving psychiatric practice and patient outcomes over the next few years, include:

  • AI speech analysis to diagnose MDD
  • machine learning techniques to predict conversion to schizophrenia6
  • prescription digital therapeutics, which provide patients with CBT tools to use in their own time, for instance CBT for insomnia (CBT-I)7
  • sensor-enhanced medication8 and AI machine vision9 to improve adherence
  • digital phenotyping,10,11 which involves collecting sensor, keyboard, voice and speech data from smartphones to measure behavior, cognition, and mood — such techniques have led to the development of smartphone-based mental health exams and digitally subtyping of suicidal thoughts12
  • augmented reality techniques to help patients improve their social skills and address specific behavioral problems such as delusions and fears13

Our correspondent’s highlights from the symposium are meant as a fair representation of the scientific content presented. The views and opinions expressed on this page do not necessarily reflect those of Lundbeck.

References
  1. Beam E, et al. BioRxiv 2019. In press.
  2. National Institute for Mental Health. https://www.nimh.nih.gov/health/statistics/mental-illness.shtml. Accessed 4 October 2019.
  3. Vaidyam A, et al. Can J Psych. 2019;64:456–64.
  4. Fitzpatrick K, et al. JMIR Ment Health. 2017;4:e19.
  5. Morris R, et al. J Med Internet Res. 2018;20:e10148.
  6. Rezaii N, et al. npj Schizophrenia. 2019;5:9.
  7. Zachariae R, et al. Sleep Med Rev. 2016;30:1–10.
  8. Knights J, et al. npj Digital Med. 2019;2:20.
  9. Bain E, et al. JMIR Mhealth Uhealth 2017;5:e18.
  10. Baker JT. Neuropsychopharm. 2018;43:2504–5.
  11. Insel T. JAMA. 2017; 318:1215–6.
  12. Kleiman E, et al. Depress Anx 2018;35:601–8.
  13. Vahabzadeh A, et al. Behav Sci. 2018;8:85.
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