Weathering Healthcare’s Perfect Storm

Hospitals live with a problem most industries would find intolerable: They rarely know what is coming through the door. On any given morning, a department might see a steady run of routine cases. Or they could see a sudden wave of patients whose conditions are complicated, severe and resource-intense.

How should administrators staff a unit when both the number of patients and the complexity of their needs can swing without warning? When clinicians are unsure what they are dealing with, do they order more tests to compensate? When a department is overwhelmed, who gets seen, and how fast? And what, if anything, can hospital leaders actually do to absorb these shocks without driving up costs or compromising care? 

Sarv Devaraj has spent his career studying how data and operational design can improve the business of delivering care. In previous research, Devaraj, the Fred V. Duda Professor of IT, Analytics, and Operations at the University of Notre Dame’s Mendoza College of Business, applied the Theory of Swift and Even Flow to healthcare. The theory suggests that productivity improves when work moves quickly and consistently through a process with minimal disruptions. Devarag and his research colleagues demonstrated across 567 U.S. hospitals that when the rhythm of care turned erratic and unpredictable, patients suffered measurably higher rates of complications and mortality. Now, alongside co-authors Sriram Thirumalai and Tyson R. Browning, both at Texas Christian University, he is asking more pointed questions: Where does that unevenness come from, and what can hospitals do about it?

In “Uncertainty in Healthcare Operations: How Hospitals Weather the Perfect Storm,” published in the Journal of Operations Management, Devaraj and his co-authors examine what happens when two very different kinds of uncertainty converge on a hospital at the same time.

“Healthcare is the single largest sector of the U.S. economy. We're talking about $4.5 trillion a year, or roughly 17 cents of every dollar Americans spend,” said Devaraj. “And yet, for all that investment, we still know remarkably little about one of its most fundamental challenges: uncertainty.

“Decades ago, healthcare researcher Jack Wennberg made the striking observation that uncertainty is the single most important factor shaping how physicians behave. That's a bold claim, but our research lends support.”

Devaraj said that one way to understand uncertainty is to think of a hospital department like a restaurant kitchen. What he called “volume uncertainty” refers to how many diners show up, as some nights the place might be packed, while it’s half empty on other nights. On the flip side, “mix uncertainty” is about what those diners order. Sometimes, everyone wants a simple burger;  other nights, half of the room is ordering elaborate, multi-course meals with complicated dietary restrictions.

According to Devaraj, both create challenges in the kitchen for completely different reasons. In healthcare, there is a crucial difference between mix uncertainty and volume uncertainty, and  they require completely different solutions.

“Volume swings are a staffing and scheduling problem,” he said. “Mix swings are a knowledge and coordination problem. We found the same is true in hospitals. When a cardiology unit sees wildly different numbers of patients month to month, that's a volume problem. When the complexity of those patients swings dramatically — some weeks mostly routine cases, other weeks patients with six overlapping chronic conditions — that's a mix problem.

“We had to separate them because, as we discovered, they actually push doctors to behave in opposite ways. If you lump them together, you miss that entirely and you design solutions that fix one problem while making the other worse.”

According to Devaraj’s data, mixed uncertainty leads to more procedures, but volume uncertainty leads to fewer. So, what explains that opposite reaction? It comes down to the kind of pressure doctors face in each situation. When a department faces mix uncertainty, they're less sure exactly what they're dealing with. This means that they run more tests and order more procedures to gather information and close that knowledge gap.

“It's a bit like a detective collecting more evidence when the case is murky,” he said. “More procedures are the doctor's way of saying, 'I need more data before I can be confident in my diagnosis and treatment plan.’”

Comparatively, volume uncertainty triggers a quite different instinct. When patient numbers surge, the system gets overwhelmed. In these cases, doctors feel the pressure to move faster, cutting non-essential steps, streamlining and focusing only on what seems most critical.

“It's the classic 'triage mentality,’” Devaraj said. “Paradoxically, this means fewer procedures per patient, but patients end up waiting longer overall because the whole system is congested and bottlenecked.”

The opposite directions of the two uncertainties caught the researchers off guard at first. Initially, they expected both types of uncertainty to push things in the same direction, meaning that more uncertainty equals worse outcomes across the board. Yet they found that when it comes to procedures, mix uncertainty and volume uncertainty pull in opposite directions.

“Hospitals can't treat ‘uncertainty’ as one big monolithic problem.”

Instead, hospital administrators have to diagnose which kind they're facing before they can prescribe the right fix. The research offers a blueprint for a different way to approach an ever-present obstacle.

The first practical step Devaraj recommends to any administrator is to measure the variation in their patient mix from week to week and month to month. Most hospitals track volume and average complexity, but are not systematically tracking the swings.

“You can't manage what you don't measure,” he said. “Our study provides a straightforward framework: Look at how much the complexity of your patients is fluctuating within each department over time, and look at how much your patient volumes are fluctuating. Those two numbers tell you very different stories and point to very different solutions. Once you've done that diagnostic, the next question is where your biggest exposure is.”

These findings could translate into better patient care. Devaraj expects this research can help patients go home sooner, with fewer unnecessary tests and procedures behind them. When a hospital department is constantly faced with unpredictable complexity, then the default response becomes defensive medicine. This means more tests and procedures, as well as more days in the hospital as a precautionary measure.

Yet when hospitals build the right kind of expertise and give departments a little breathing room, the defensive impulse decreases. This makes doctors more confident, better informed and better able to arrive at a clear diagnosis and treatment plan without running the patient through a gauntlet of extra procedures.

“Ultimately, the 'perfect storm' in our title refers to the combination of both types of uncertainty hitting at once,” said Devaraj. “When complexity is unpredictable and patient volumes are erratic simultaneously, the system is under maximum stress. Understanding that dynamic — and having concrete tools to address it — is what we hope hospital leaders take away from this work.”