Cale Queen

[Cale Queen @cale_queen]

You have the opportunity to reduce the avoidable work around them, but if the goal becomes replacing human judgment rather than improving conditions, we are not solving the staffing problem. We are just creating a new operational problem with better software around it.

[Cale Queen @cale_queen]

AI conversations circle around replacement, and healthcare is no exception. Staffing is one of the largest cost centers in any care setting. In many cases, people-related costs make up roughly 60% of the total. That makes leaders ask where automation can reduce pressure.

[Cale Queen @cale_queen]

We should push back on that inclination. The human touch in healthcare is part of the operation. Moving a patient, calming a family member, noticing when something feels off, helping someone understand what comes next. These are care delivery and should not be substituted.

[Cale Queen @cale_queen]

You might think that once people see the data, a change will naturally follow. But organizations do not really change from awareness. They change when decision makers follow through. Otherwise, the dashboard just becomes a very expensive weather report.

[Cale Queen @cale_queen]

A dashboard can tell a leadership team that patient wait times are increasing, but if there is no agreed-upon threshold for intervention, then the organization absorbs the information without changing its behavior. The report becomes awareness, not action.

[Cale Queen @cale_queen]

Healthcare organizations are incredibly inertia-heavy systems. The people working within them are already operating at capacity. Everyone may agree that a problem exists, yet still default to the current process because changing workflows can introduce short-term disruptions.

[Cale Queen @cale_queen]

That is where healthcare organizations have an opportunity to move the conversation beyond analysis and toward operating systems that reduce surprise.

🔗https://t.co/lWtlD2bG6X

[Cale Queen @cale_queen]

The recent JAMA study on nonprofit hospitals and management consultants raises an important question for healthcare leaders. Why does so much analysis fail to become measurable operational improvement?

[Cale Queen @cale_queen]

The real value comes from building a system that can recognize meaningful signals and act before the issue becomes harder to correct. More visibility only matters if it changes the decision in time.

[Cale Queen @cale_queen]

This is the kind of pressure healthcare operators need to see earlier.
Small changes become much harder to manage once they are already embedded in the margin.

[Cale Queen @cale_queen]

Cost of goods is one of those clinic pressures that can be easy to overlook because it does not always show up as a single major event. It shows up in smaller ways. Supplies, shipping, equipment, and parts cost a bit more because of it, but it all adds up qucikly.

[Cale Queen @cale_queen]

That creates a margin issue, seemingly out of nowhere. The clinic may be delivering the same care, seeing the same volume, and doing the same work, but the economics underneath that work have changed.

[Cale Queen @cale_queen]

Before a clinic can make better decisions, it must understand its operating environment. From there, the work becomes more specific. The point is to understand which signals are connected to decisions the organization actually needs to make.

[Cale Queen @cale_queen]

Eligibility questions that were not resolved earlier turn into calls. Prescription refill processes that rely on manual follow-up turn into calls. Unclear scheduling rules turn into calls.

Phones are where the root problem becomes impossible to ignore.

[Cale Queen @cale_queen]

When phones are backed up, it looks like a staffing issue. More calls are coming in than the team can handle, so the natural question is whether there are enough people to answer them.

But a busy phone line is often where other operational issues finally become visible.

[Cale Queen @cale_queen]

But data innovation can lose its value when meaning is separated from its application. We should keep pushing what data can do, but not lose focus on the decisions it is supposed to improve and the outcomes that actually matter.

#DataInnovationDay

[Cale Queen @cale_queen]

I love data, and I love seeing how people continue to innovate with it. There is a lot of important work happening right now, and much of it is doing real good. Better signals, faster visibility, stronger decisions, earlier intervention. That progress matters.

[Cale Queen @cale_queen]

That requires a different kind of visibility, and that's where business intelligence becomes more important. Healthcare organizations need to understand not just what happened, but what is changing inside the system before the result is already set.

[Cale Queen @cale_queen]

A fee-for-service model is built around documenting activity. A visit happens, a procedure is completed, a test is ordered, and the organization needs to capture and code that work correctly.

Value-based care shifts the focus toward outcomes, cost, quality, and coordination.