Since the Senate healthcare reform bill was released late last week, there's been tons of conversation around what's in the darn thing. Among the rotten provisions in the current iteration of Trumpcare -- and there are many -- arguably the least discussed are those affecting individuals with mental illness. Mental illness is an extraordinarily broad category, by the way; it includes everything from anxiety, depression, bipolar disorder, eating disorders, ADHD, schizophrenia and more. To escape the bill's clinical, impersonal language and get to the point: Folks living with mental illness are about to get completely screwed. One in five Americans suffers from mental illness, and Medicaid is the single largest payer of their mental health services.
Oct. 10 marks World Mental Health day. According to the World Health Organization, the objective of observing the day is to raise awareness about mental health issues and mobilize efforts in helping people suffering from these problems. An estimated one in five people in the U.S., or 43.8 million people, have mental health problems in a given year. The stigma surrounding mental illness still prevails and these negative stereotypes can create a lot of misconceptions and isolate people who have serious mental health problems. Research indicates these stereotypes can pose a "significant barrier to care for many individuals with mental illness."
Mental health disorders are expected to cost the global economy £12 trillion ($16 trillion) a year by 2030, experts have said. Conditions such as depression and anxiety are rising in every country on the planet, according to the authors of a new report. They add the'collective failure to respond to this global health crisis' will'result in monumental loss of human capabilities and avoidable suffering'. Speaking on World Mental Health Day, the report's joint lead editor Professor Vikram Patel, from Harvard Medical School, said: 'Mental health is the foundation of human capability that makes each life worthwhile and meaningful. 'It is for this reason that there can be no sustainable development without attention to mental health.'
A ten-year plan for the future of the UK's National Health Service aims to improve mental health services and maternity care, and use digital technologies to make access to healthcare easier. The plan, launched by NHS England today, also outlines proposals for expanding the use of genetic testing and whole-genome sequencing. But critics have warned that funding and staffing shortfalls could obstruct the plan. According to the UK government, maternity safety in the UK will be improved, and more mental health support offered to new parents. Mental health services will also be extended to an additional 350,000 children and young people, and at least an extra 380,000 adults, over the next five years.
Rosenfeld, Ariel, Benrimoh, David, Armstrong, Caitrin, Mirchi, Nykan, Langlois-Therrien, Timothe, Rollins, Colleen, Tanguay-Sela, Myriam, Mehltretter, Joseph, Fratila, Robert, Israel, Sonia, Snook, Emily, Perlman, Kelly, Kleinerman, Akiva, Saab, Bechara, Thoburn, Mark, Gabbay, Cheryl, Yaniv-Rosenfeld, Amit
Mental health conditions cause a great deal of distress or impairment; depression alone will affect 11% of the world's population. The application of Artificial Intelligence (AI) and big-data technologies to mental health has great potential for personalizing treatment selection, prognosticating, monitoring for relapse, detecting and helping to prevent mental health conditions before they reach clinical-level symptomatology, and even delivering some treatments. However, unlike similar applications in other fields of medicine, there are several unique challenges in mental health applications which currently pose barriers towards the implementation of these technologies. Specifically, there are very few widely used or validated biomarkers in mental health, leading to a heavy reliance on patient and clinician derived questionnaire data as well as interpretation of new signals such as digital phenotyping. In addition, diagnosis also lacks the same objective 'gold standard' as in other conditions such as oncology, where clinicians and researchers can often rely on pathological analysis for confirmation of diagnosis. In this chapter we discuss the major opportunities, limitations and techniques used for improving mental healthcare through AI and big-data. We explore both the computational, clinical and ethical considerations and best practices as well as lay out the major researcher directions for the near future.