Don’t Automate a Broken Process—Fix It First

We all want leverage. We’re all looking for the next tool, the next integration, the next AI plugin that’s finally going to unlock scale. 

But here’s the truth that founders in healthcare need to hear (and probably don’t want to): You can’t automate your way out of dysfunction. 

Let Me Explain 

I've seen founders spend thousands—sometimes tens of thousands—on building or buying tech tools that promise efficiency. NLP-based coding tools. Pre-visit planning platforms. Real-time dashboards. You name it. 

And yet, what happens? 

• A home visit provider documents "dementia"... but the AI doesn’t realize it was referring to the patient’s cat. 

• A platform flags a diagnosis... based on a note that’s seven years old and irrelevant. 

• A health plan pays 2x over market rate for risk adjustment services… and still doesn’t see accurate, compliant documentation. 

These aren't theoretical problems. They’re real examples from the field. 

What all of them have in common is this: The system being automated was broken to begin with. No amount of tech, automation, or AI can save a bad workflow. Garbage in, garbage out. 

The Temptation to Skip Steps 

It’s understandable. We’re all busy. We’re wearing too many hats. We want speed. 

But skipping process design to jump straight to automation is like building a conveyor belt before you’ve figured out what you’re shipping. It’s a fast path to nowhere. 

And in healthcare? That means compliance risk, wasted spend, and abrasion between teams. Fast becomes expensive.

Fix the Root, Not the Output 

Here’s where we need to shift our thinking: 

Don’t use tech to automate the way things are. Use it to reinforce how things should work. 

Start by mapping your process without technology. Where are the pain points? Where are the handoffs breaking? What steps depend entirely on one person’s institutional knowledge? 

Only after you’ve cleaned up the process do you even think about layering in tools. 

Take the example of provider documentation. If physicians aren’t trained to link diagnoses to chronic conditions, no NLP tool is going to invent that connection for them. That’s not a tech problem—it’s a training problem. The real fix is provider education, not another widget. 

Ask Yourself: 

• Are we scaling something that actually works? 

• Does this workflow reflect what we wish was happening, or what is happening? 

• Have we validated this process manually before trying to automate it? 

If not? Pause. Fix first. Then scale. 

Final Thought 

There’s nothing more dangerous to your business than a shiny solution that hides a messy foundation. So before you spend money on automation, spend time on the basics. 

You might find the real unlock isn’t AI at all. It’s process clarity, and a little bit of courage to stop doing what no longer works.