Letters from the Field Phase is an opportunity for the 2015-17 Sauvé Fellows to share their takeaways from the residential phase of the Jeanne Sauvé Public Leadership Program and showcase their applicability in the field.

Here is Charles Onu’s story:

At the end of the residential phase of the Jeanne Sauvé Public Leadership Program, I took up a position at St. Mary’s Hospital Research Centre as a Health Informatics Researcher. Based in one of the most ethnically diverse neighbourhoods of Montreal, St Mary’s serves over 53,000 persons annually in its outpatient clinic alone. Needless to say, I was excited about working in this prestigious hospital and about getting back to work in a healthcare setting.

The project I was going to work on was also quite interesting. It involves applying artificial intelligence (AI) to improve the experiences of women newly diagnosed with breast cancer. In Canada, breast cancer is the most common type of cancer among women and is the second leading cause of death from cancer (Canadian Cancer Society, 2016). This was a part of a larger project known as Health Experiences Canada. This project aims to use the power of storytelling to provide psychological and social support to persons undergoing diagnosis or treatment for chronic conditions. 

In the case of breast cancer, women who have undergone the diagnosis-treatment-recovery cycle are invited to tell their stories (in video or audio format), providing valuable perspectives on questions that doctors are either unable to answer or do not have the time to address. These stories explore individual challenges (bodily changes that may result from chemotherapy, feelings of inadequacy that result from mastectomy); family challenges (how to inform one’s children, the impact on relationships with partners), information needs, and longer-term concerns about recovery or recurrence. 

So how does AI fit into such a project? As women were offered this huge resource with hundreds of video clips of other women sharing  their stories, another problem arose: How do they find content that is relevant to them? The story of a person who did not receive chemotherapy may not be useful to one who is going to receive it. The story of how a 40-year woman who has 3 children navigated family issues, may not be useful to a 26-year old who is not married and is without children. It is important to ensure that women who use our resource are able to quickly find content that is useful and relevant to their experience, especially at such a mentally and physically demanding time in their lives. This is where AI comes in. My colleagues and I are applying machine learning techniques to build a recommender system into a tablet-based application. This system would be able to harness knowledge about a user (both demographic and illness-related information) to match them to content that would be most relevant to them.

It has been 6 months and I cannot overemphasise how valuable the Sauvé experience has been in helping me make the best of this experience. I found place at St. Mary’s for the practical tools we engaged with, as Fellows, for working within multidisciplinary teams. Also, Sauvé programming on the concept of systems thinking has helped me in appreciating the scope of the system I work within, the roles of the actors (oncologists, clinical researchers, system engineers, media specialists, patients, etc), and the interaction of these elements to manage conflict and increase value.

Other valuable takeaways from the Sauvé Program are cross-cultural communication and non-violent communication (NVC) skills. Every two months at St. Mary’s, we have focus group sessions in which breast cancer survivors are invited to help us review our progress with the app, to see if it would have met their needs and to offer recommendations on how it can be most useful for women undergoing the process. These sessions have been as enlightening as they have been heartbreaking. Quite often, the women find themselves explaining some of the hardest parts of dealing with breast cancer, and we (the team) realise that it is not just about the app we are building. These sessions are also therapeutic for them – opportunities to process locked up feelings – and we let them do it. We try our best to stay with them as they recount their journey, but also to guide them back towards  the feedback we hope to get.

Quite frankly, I had nearly forgotten one of the most grounding aspects of working in the healthcare setting. It is emotionally challenging being constantly reminded of the inherent vulnerability of our bodies. It is easy to forget; easy to take for granted our ability to sleep and wake everyday, to go to work, school, etc. In this respect, the health experiences project is particularly challenging. In other ongoing health projects that I’m involved with (such as Ubenwa), ‘data’ are generally mute. Whether it is heart variability, cry, or respiratory signals of babies, the data do not explicitly express any opinions or feelings. In HealthEx, ‘data’ are powerful, sometimes disheartening, sometimes laced with humour, but mostly, profound and touching stories of women who have come face to face with the fragility of our existence.

Working in a hospital is also motivating, with many opportunities to help, whether it is through the work I do, or simply holding a door for a woman who is completely worn out from chemo treatment, or walking an elderly man to the bus stop. Here, I am constantly reminded that my skills, talent and effort are being applied in the right way, and in an important place. I strongly believe in the potential for AI to bring positive transformation into how we deliver healthcare. Whether it is in increased precision in disease diagnosis, discovery of effective treatment pathways for chronic conditions, or in realising low-cost medical solutions, the possibilities are remarkable for the human race. 

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