Why a Hospital CEO Views Burnout as a 'Complex' Problem, Not Rocket Science

Alejandro Quiroga of Children's Mercy Kansas City says healthcare keeps treating workforce burnout like an engineering problem when it requires hypothesis-driven leadership instead.

When hospital leaders try to fix workforce burnout, they often respond by reaching for the same tools to quantify solutions.

Pro formas and ROI models can be useful for alleviating strain, but Dr. Alejandro Quiroga, president and CEO of Children's Mercy Kansas City, believes that approach misses the point.

"A complicated problem has a solution that you can know the answer ahead," Quiroga tells HealthLeaders. "Sending a rocket to the moon is a complicated, not a complex problem. Why? People have done it."

Burnout, he argues, is not that kind of problem because it's complex, and "a complex problem doesn't have a solvable answer."

The distinction of complex versus complicated has become foundational to how Quiroga approaches workforce challenges. In his view, healthcare leaders often apply engineering-style thinking to problems that are human and adaptive at their core.

"We have a framework issue in healthcare," he says.

Building a hospital tower is complicated, but Quiroga notes that its variables can be modeled. Burnout and staffing shortages don't work that way. There's no formula to plug into a calculator.

"The way you deal with a complex problem is you have to have a hypothesis," Quiroga says. "Healthcare is often very uncomfortable with hypothesis-driven work."

Instead of certainty, leaders must accept iteration. That means forming a testable hypothesis, allocating appropriate resources to try to prove or disprove it, and adjusting based on what frontline teams learn.

It also requires rethinking where solutions originate.

"In my experience over my career, over and over, the answers do not exist at the top of the organization," Quiroga says. "The answers exist closer to the problem."

For executives, that shifts the role of leadership. "The top has to bring that clarity," he says. "The top has to bring the direction, the resources, and then don't get into the how. Allow [your teams] to figure out the how and they often do."

Pictured: Alejandro Quiroga, president and CEO, Children's Mercy Kansas City.

Trust before measurement

Quiroga posits that healthcare's culture has made burnout harder to solve by eroding trust around measurement and productivity.

"When you're trying to get data on how a hospital is being run in the U.S., you are going to find a very interesting black box," he says.

Over time, he believes frontline staff have learned that when leadership gains visibility into workflow, the outcome often isn't relief, but new constraints. That dynamic fuels skepticism around new tracking or productivity initiatives and makes nurses wary of being "measured" yet again.

"If I were to tell all the nurses in the U.S. we're going to be measuring everything that you're doing, they would be very stressed out," Quiroga says.

For that reason, he contends workforce redesign must begin with tangible support, with leaders focusing first on making the job more doable and sustainable.

"You make the job possible and you save money with things that are hard to measure in the industry," he says.

Improvements in retention, throughput, and quality ultimately produce financial returns, even if they don't slot neatly into traditional ROI frameworks. The returns are real, but Quiroga acknowledges that healthcare often looks for them in the wrong places.

Iteration in practice

That hypothesis-driven approach is visible in Children's Mercy's recent rollout of Helen, an AI-enabled, concierge-backed platform designed to offload non-clinical tasks from nurses.

The first hypothesis was wrong, Quiroga admitted. Initially, the plan was to have an Alexa in the room. However, he quickly realized that technical issues and lack of adaptability were limiting factors, and the idea didn't resonate with either nurses or patients.

The team pivoted to a mobile app and moved into co-creation with frontline staff. "We iterated, that's how we learned," Quiroga says.

Assumptions continued to evolve. What was initially conceived as a way to bypass nurses for routine requests became a tool nurses actively used themselves, with 75% of commands coming directly from nursing staff, Quiroga highlights.

The rollout strategy followed the same iterative logic. Rather than treating financial projections as the primary proof point, leadership looked for behavioral validation.

"Our first KPI was if you deploy the app and all the nursing staff says, ‘If you take this away, we will be very upset,' then you won," Quiroga said. "We got to that very fast."

The system is now seeing measurable time savings at roughly an hour per nurse per shift, according to Quiroga. He emphasizes though that the larger impact is a cultural one that reduces burden so nurses can focus on delivering the best clinical care possible.

"In any other industry, this would be widely celebrated," he says. "In this industry, it's faced with a lot of skepticism for a myriad of reasons that I understand, but it goes back to the complicated, complex framework."

For Quiroga, the lesson extends beyond any single strategy.

"Everybody's talking about differentiating themselves, but when you benchmark yourself against the 50% of everybody else and do the same, you do not create a differentiation," he says.

In a tight labor market, he insists that approach is unsustainable. Organizations that want to recruit and retain talent must redesign the experience in ways that are meaningfully distinct.

To achieve that, Quiroga's process offers a blueprint: trust the people closest to the work, form a hypothesis, test it, and accept that complex problems rarely yield linear solutions.