Mike Denis, CEO of Akrivia Health, discusses real world data and how this can help us understand more about mental health disorders, enabling targeted precision medicine.
The picture of mental health diagnosis today:
Mental health problems account for 13% of the total global burden of diseases, with nearly 1 billion people living with a mental disorder and a further 50 million with dementia. However, only 6% of UK health research spending goes on mental health.
Currently, there is no single test to identify and diagnose mental health disorders and types of dementia. It is harder to determine the exact type of mental health disorder or dementia due to symptoms and overlapping changes in the brain. In addition to this, due to the lack of subcategories within certain conditions, such as schizophrenia and bipolar, clinicians often prefer not to diagnose and label too early. For some types of dementia, such as early-onset dementia, the symptoms are misdiagnosed and often attributed to stress, anxiety, depression, or menopause, similar to bipolar- a complex disorder for doctors to identify due to the wide variety of symptoms.
Despite the growing understanding of the brain and psychology, treatment and diagnosis for mental health and neurological conditions are lagging. Whilst diagnosis rates across the UK are improving, there are still so many people living in limbo with symptoms they don’t fully understand. At present, diagnosis of early-onset dementia can take up to 4.4 years after meeting with two to five different consultants.
Whilst we know that there are over 200 types of dementias, an appropriate diagnosis is unlikely. Many individuals are often placed under the umbrella term “dementia”, and only if the individual is formally diagnosed- in England (2018), the estimated dementia diagnosis rate for those under 65s was 41% and 68% for people over 65[i]. A similar experience to individuals diagnosed with bipolar. The average length of time between a person’s first episode and getting the right diagnosis for bipolar is 8 years[ii]. As with dementia, umbrella terms are used frequently to avoid misdiagnosis.
However, there is increasingly robust evidence that a range of innovative and preventative approaches can improve patient outcomes, increase quality of care and productivity, as well as reducing costs. Early identification and intervention are key to this.
Real world data
Real-world data with clinical depth and nuance are critically needed to understand disease progression, patient characteristics, condition subtypes, and variations- as well as clinical outcomes. The analysis of real-world data in clinical research is rising, but its use to study mental health and dementia subtypes has hardly been addressed until today.
Understanding which open questions can be answered by combining existing data sources- and what questions will require new data types and/or sources- will help us to most effectively and efficiently mobilise resources to address the pressing needs in mental health and dementia research. Extracting and reading unstructured real-world data collected from a variety of sources, such as electronic health records, can be particularly helpful in the diagnosis of psychiatric conditions.
Precision Medicine – The right patient, at the right time, with the right treatment
In order to meet projected demand, future treatment and care provision need to be more effective and efficient. This can only be achieved by combining improved technologies, more efficient clinical trials, and new drug applications for the development of precision psychiatry models.
Predictive models that can identify patients who will subsequently develop dementia may create the opportunity for such persons to be evaluated for potential contributors to cognitive impairment (e.g., high-risk medications, depression, medical illnesses).
Decision-making, based upon precision psychiatry models, will be dependent upon complex patient-level datasets that combine remote and continuous clinical data, genetic data, and brain images. These models will need to be continuously assessed and improved with updates of real-world data.
Harnessing real-world data will contribute to the early identification of mental health disorders. Correctly identifying and forming sub-categories will help scientists to discover new treatments to manage these conditions, offering patients and their families improved and potentially transformational health outcomes.
The potential of real-world data to transform current approaches to the diagnosis and thus the treatment of mental health disorders is considerable. Akrivia Health is working to enable a new generation of precision neuroscience, alleviating the burden in one of the world’s most pressing medical needs.
[ii] https://www.nbcnews.com/health/mental-health/why-does-it-take-so-long-diagnose-bipolar-disorder-n865171 Kay Redfield Jamison, professor of psychiatry at the Johns Hopkins School of Medicine and author of “Touched with fire: Manic-Depressive Illness and the Artistic Temperament.”