Availability Bias: The Silence of the Unseen

What if we are optimizing for the patients who aren’t showing up?

Availability Bias: The Silence of the Unseen

What if we are optimizing for the patients who aren’t showing up?

Medical technology has a unique kind of digital Survivorship Bias. It’s the ultimate manifestation of Availability Bias: the human tendency to over-value the information right in front of us while ignoring the critical context that is missing.

If we do our job well, our dashboards are incredibly persuasive. We could see the 10,000 active patient portal users, the 5,000 completed telehealth visits, and the high-performing diabetic control cohort. We celebrate that available, visible “data” and use it to double down on our existing strategy.

But what about the “data that isn’t”?

We often fail to optimize for the patients who missed the appointments, who have unreliable broadband, or who simply don’t fit into our preconceived dropdown boxes. If a patient cannot find their identity or their experience in our structured fields, they effectively cease to exist in our analytics.

Their voices aren’t in our satisfaction surveys because they couldn’t log in, or they had no way to identify themselves within our rigid data architecture. Their silence is a data point, but it remains “unavailable” without deliberate, inclusive effort.

When we follow data blindly, we are only serving patients who are already following us. We aren’t closing gaps. We are automating them.

When we follow data blindly, we are only serving patients who are already following us. We aren’t closing gaps. We are automating them. We are helping leaders follow a data delusion.