The MONARCA system for Bipolar Disorder is the foundation of the Monsenso mHealth solution for mental health. MHealth solutions are now broadly used to manage a wide range of health-related conditions. These monitoring systems help users monitor and visualise their behaviour. For example, it states users’ physical state, it reminds them to perform specific tasks, it provides feedback on their behaviours, and it recommends healthier actions.

Until very recently, mHealth solutions have primarily targeted somatic diseases, even though, they have the potential to assist the management of mental illnesses such as depression, bipolar disorder, and schizophrenia. It is possible that this has been the case due to the complexity of mental illness, since symptoms vary from patient to patient, it may be unclear what data should be monitored. Besides, there isn’t a set treatment and standard medications that will work for all patients; therefore, treatment should be as individualised as the illness itself. Additionally, it could also be difficult for patients to reflect on their own mood and behaviour, and they may only recognise their symptoms if they understand the illness and know what to look for.

This article portrays the origins of the Monsenso mHealth solution, founded in October 2013 by Jakob E. Bardram, Ph.D. and Mads Frost, Ph.D. as a spin-off from the IT University of Copenhagen. The company was based MONARCA research prototype, funded by the European Commission under the 7th Framework Program.

The MONARCA Project (2009 to 2013) aimed to develop and validate solutions for multi-parametric, long-term monitoring of behavioural and physiological information relevant to bipolar disorder. It included the development of an appropriate platform and a set of services into an innovative system for management, treatment, and self-treatment of the illness.

The MONARCA system was designed to comply with relevant security, privacy and medical regulations. It also paid close attention to interoperability with existing medical information systems. The system was integrated into appropriate medical workflows, and evaluated in clinical trials. The project involved 13 European academic, clinical, and commercial partners.

As part of the MONARCA project, a close collaboration was established between the researchers in the PIT Lab and the Department of Psychiatry at the University Hospital of Copenhagen (Rigshospitalet) represented by Professor Lars Vedel Kessing, MD & Ph.D. This Copenhagen-based alliance formed the basis for developing a unique sensing and treatment platform utilizing semi-automatic data collection from smartphones used by patients.

During the project, the MONARCA system was designed and developed in close collaboration between the researchers, psychiatrists, and patients suffering from bipolar disorder. The system was subject to intensive clinical trials and ultimately went into a randomised clinical trial (RCT). The aim was to establish clinical evidence for the efficacy of using the MONARCA system in the treatment of bipolar disorder. More than 100 patients were enrolled in the clinical trials and used the system.

The MONARCA system

The Monsenso platform and the MONARCA research prototype consist of two parts:

• A smartphone app for patients that allows them to enter self-assessment data, collects sensor-based data from the phone, helps the patients track their medicine and provides feedback on the data collected.
• A web portal that provides detailed historical overviews of a patient’s data, and it can be accessed by patients and clinicians.

The patient web portal can be fully customisable to accommodate the needs of each individual, such as their own Early Warning Signs and Triggers.

The clinician web portal provides them with a quick overview of all their patients enabling them to focus on the patients in need of immediate attention.

An mHealth solution for Bipolar disorder

The bipolar disorder is characterised by recurring episodes of depression and mania, and its treatment aims to reduce symptoms and prevent episodes through a combination of:

• Pharmacotherapy – Symptoms are controlled and mood is stabilised with a customised combination of antidepressants, anti-psychotics, mood stabilisers, and other drugs such as sleeping pills.
• Psycho-education – Patients are taught about the complexities of their disorder, the causes of recurrence of episodes, and how to manage their illness.
• Psychotherapy – Patients are coached to deal with their symptoms and find practical ways to prevent episodes through actionable behavioural and life-style choices, such as routine, sleep, and social activity.

A good approach to treatment is predicting and preventing episodes by training patients to recognise their Early Warning Signs (EWS), which symptoms that indicate of an oncoming episode [2]. This type of training is resource-intensive and its success varies highly from patient to patient.

In particular, it was discovered that these three parameters are crucial in keeping a bipolar patient stable:

• Adherence to prescribed medication: Taking all medications on a daily basis, exactly as prescribed.
• Stable sleep patterns: Sleeping eight hours every night and maintaining a consistent routine of going to bed, waking up.
• Staying active both physically and socially: Getting out of the house every day, going to work, and engaging in social interaction.

Although at first glance this list seems simple, numerous studies have shown that each of these items are very difficult to achieve for many patients, and achieving all three at the same time every day is inherently challenging in combination with a mental illness. Hence, the core challenge is to create technology that would help – or persuade – the patient to do these three things daily. [1]

Therefore, the MONARCA system was developed to include five core features that support a patient’s self-management:

• Self-assessments – Reminded by an alarm, patients enter subjective data directly into the system through their smartphones. This data includes mood, sleep, level of activity, and medication. Some items can be customized to accommodate a patient’s specific needs, while others are consistent to provide statistical analysis.
• Activity monitoring – Through a GPS and accelerometer, objective data is collected to monitor a patient’s level of engagement in daily activities. The system can also measure the amount of social activity based on phone calls and text messages.
• Historical overview of data – On the web portal, patients and clinicians can obtain a two-week snapshot of a patient’s basic data for immediate feedback. The portal also gives them access to a detailed historical overview of the data, enabling them to explore it in depth by going back in time, and focusing on specific variables.
• Coaching and self-treatment – The MONARCA systems supported psychotherapy in two ways. Firstly, through customisable triggers that notify the patient and clinician when the data potentially indicates a warning sign. Second, since the patients have access to their own Early Warning Signs, it empowers them to learn more about them.
• Data sharing – To strengthen the relationship between patients and clinicians, important information and treatment decisions are shared.

In general, patients and clinicians found the system quite useful and easy to use. The preliminary user feedback revealed all research participants agreed it was easier to use the smartphone-based self-assessments than the paper-based ones.All participants believed that entering data on the self-assessment is easy and that the system provides them allows them to adjust to their personal needs.

A user explained that “It is much easier to use the phone that the piece of paper. I have the phone with me at all times, and I don’t have to worry about the paper getting lost in the piles. I is very convenient that you can just enter data when you remember or experience instead of having to recall it all when you have the paper in your hands.” [1]

References:

[1] The MONARCA Self-assessment System: A Persuasive Personal Monitoring System for Bipolar Patients. Bardram, Jakob E., Frost, Mads, Szanto, Karoly and Marcu, Gabriela. In Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, pages 21-30, New York, NY, USA, 2012.

[2] Long-term mental health resource utilization and cost of care following group psychoeducation or unstructured group support for bipolar disorders: a cost-benefit analysis. J. Scott, F. Colom, E. Popova, A. Benabarre, N. Cruz, M. Valenti, J. M. Goikolea, J. Snchez-Moreno, M. A. Asenjo, and E. Vieta. J. Clin. Psychiatry, 10, Mar 2009.