Finding a niche in coding can help you get your foot in the professional door, however, there are some risks. If your skill set is too narrow you can force yourself out of the competition. If you risk it and jump in a trending part of tech that doesn’t catch on you’ve also forced yourself out of the market. To some clinicians, this risk is too intimidating. Yes, you can still not pass exams etc but your clinical career progression is spelt out for you. I’ve known a nurse for many years who cripples himself with this. He has interests but every possible venture is avoided because it’s too risky. There’s always plenty of reasons why not to do something. The result, a very smart individual thinker who reads a lot has drifted into middle management. A field that he expresses little interest for.
Being alone is hard enough. Being alone with the risk resulting in failure is sometimes too much for people to handle. Peter Thiel’s quote still rings in my head:
“Brilliant thinking is rare, but courage is in even shorter supply than genius.”
Compared to the spelt out training schemes that the NHS offers investing time in coding can seem like a vast landscape with hidden baron deserts. Which platform should you code for? Which language should you learn? What type of tech is booming? Are you going to waste your time coding in an area that is on the way out or not widely accepted?
Your choice is not as complex as you think it is. You already have a niche, your clinical experience. Coding is a tool that speeds up and automates processes. When thinking of tools, I’ve never met a guy who’s brought a hammer because they wanted a hammer, they wanted to hammer something. You want to solve clinical problems, analyse clinical data and streamline processes. Pick an easy high-level language. You’ll be able to develop prototype code quickly and apply it to your clinical problem. Once your problem is solved you can go to professional developers to package your solution. For instance, Spotify labs use the high-level language Python for data analysis. This means that they “can quickly prototype complex data jobs”. If you’re wondering what good prototyping languages to learn I’d tell you to learn Python. However, others have already asked this question here. If you want to take the leap do!