My own journey started after I had been in clinical practice for over a decade. I had qualified in England and worked in the NHS for a few years before moving to Singapore where I had worked in public hospitals and private clinics. I moved into administration, cutting my teeth with not just the operational aspects of running clinics at scale, but also on financial eyeballing and strategy. Thereafter as a solopreneur in providing healthcare and consultancy services to large organisations, I deepened these skills through contract and partnership negotiations.
Babylon Rising
This set me up nicely to jump on opportunities when Babylon Health was recruiting researchers in Singapore. It was a great learning experience, exercising domain knowledge within development in technology. It demonstrated to me that to move into tech, deep coding or AI knowledge was not absolutely necessary. The table stakes were clinical expertise & experience and expertise in translating those into useable data/information for other teams- such as the developers or the product managers.
The translation skill is one that is easily learnt, but not easily executed and required an open collaborative mindset with a willingness to learn. Additional skills and knowledge, common to many tech firms came easily through working in the environment. Importantly, much of this was not taught formally. Skills such as agile development, knowledge such as the difference between front-end and back-end.
Additionally, key leadership positions were filled with clinicians focused on different problem areas from risk estimation to symptom checking to telemedicine. This really accelerated the collaboration between the technical and the clinical teams.
gaining a working knowledge of AI, models, statistics, development philosophies (such as Scrum) in a slow, drip-fed manner was indispensable
Through Babylon, gaining a working knowledge of AI, models, statistics, and development philosophies (such as Scrum) in a slow, drip-fed manner was indispensable. This was really only possible as the role was part-time, facilitating gradual learning. I credit this process as enabling me to ease into a tech role. I recommend this route heartily, but more on that later.
Furthermore, much like any other skills, the practical day-to-day application of foundational knowledge, tech cultural skills and methodologies helped to cement this knowledge onto the clinical scaffolding of medical school and a jobbing physician.
A good indication of the value of skills imparted by, or learnt at Babylon are the Babylon Alumni. Many of whom are active in the tech space now- for example, Dr Keith Grimes (Curista), Dr Sim Hui Xin (Qmed Asia), Dr Annabelle Painter (Visiba UK), Dr Alex Szolnoki (Medtronic).
A reflection of my time at Babylon
When I was at Babylon, we started out with a large number of clinicians, all working mostly on data and data translation. From there, the playing field was whittled down and we progressed to work on the clinical testing/ validation. Eventually, I was left with two other physicians, and we were brought over to the Sloan Square HQ in London to work on some aspects of their model.
In retrospect, this was the point at which I realised this could be a viable career path. In particular, a viable one for me. You see, I have fairly bad imposter syndrome. Usually, I use this to power my urge to upskill, learn new things and generally improve myself. In this instance, it was validation that I had valuable skills and, I could utilise them and leave a positive impact through technology.
If there was anything I would have done differently, it would have been to take greater advantage of the networking opportunities when I was at their Sloane Square office. As it is I managed to connect with the majority of the clinical teams and clinical research teams but in hindsight, a more senior innovation lead connections would have been even more valuable.
Stay tuned for the next post on my experience surfing the second wave of Physician Defectors with Ubie and AWS!
Bonus content!
The fall of Babylon.
I was involved at Babylon for 2 years, leaving before their US expansion, IPO and subsequent collapse. I’ve been asked by numerous folks why the company failed- so here are my 2 cents- based on public information.
#1. Lack of differentiation on reimbursement- the majority of contracts appear to be capitation, which means, they have to differentiate thusly either on cost of customer acquisition or on operating model.
#2. Lack of differentiation on operating model. The AI symptom checker should have been a cost-savings for Babylon, but this was hampered by (i) regulatory requirements (or the avoidance of regulations) (ii) lack of trust due to high profile push back against the performance of their model, and, (iii) non-compliance with privacy regulations in Canada.
This was great, id love for more ‘raw’ behind the scenes of early Babylon days