Patient health data is the single biggest bottleneck for advancing healthcare

Healthcare is going through a tremendous phase of innovation. Healthcare data is finally coming online due to the government mandate to adopt Electronic Medical Records (EMR). AI and machine learning is advancing at an exponential rate. Soon, precision medicine will finally become reality. Doctors will be able to better diagnose my condition based on data from millions of research papers that no single human can possibly read in his lifetime. They will prescribe me the best treatment available not because it’s “what generally works”,  but because millions of other patients who are similar to me in age, sex, and genetic makeup saw a positive impact from the treatment.

While I have no doubt that is the future, I think one fundamental thing that is often not talked about is that these advancements all require a fundamental ingredient, holistic patient health data at scale. In my opinion, it’s not the lack of algorithms, but the lack of access to useful health data that is the single biggest bottleneck for advancing healthcare treatment. Any researcher will tell you that a simple algorithm with lots of data  will generally hold more predictive power than an complicated algorithm with little data. As far as I know, this type of data just simply doesn’t exist today for research. This is because sharing healthcare data is very hard. There are a number of reasons for this:

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It’s hard for outsiders to tell the difference between conviction and stubbornness.

Both have strong belief systems, but their mindset is vastly different.

I was going to write a long blog post about it, but realized I can distill it down to the following:

Someone with strong conviction is receptive to new information. He has strong opinions but is ready to be convinced otherwise.

Someone who’s stubborn is on his own island. He closes his mind to all other possibilities because he can’t possibly be wrong.

Conviction = opinionated
Stubbornness = bigoted

Don’t be a bigot.

 

 

On writing requirements

How do you write good requirements? What’s your process for writing them? These are often the first question people new to PM ask. And rightly so! A PM’s primary job is to figure out what to build and then write a set of clear instructions for the engineering team to actually build it.

The ability to write complete and clear requirement cannot be overstated. It gives you more credibility with the engineers, reduces preventable rework due to missed requirement, and most importantly, frees up your time to focus on future product releases.

There are lots of instructions on how to write a typical user stories in the Agile environment. However, I found that they either stay super high level, or give examples that are overly simplistic and doesn’t take into account the complexities of real world development.

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