Emergency departments are designed for the unexpected. But when the unexpected becomes routine, weather-triggered outbreaks and hours-long wait times, it’s no longer just a logistics challenge. It becomes a systems problem. In Connecticut, hospitals are exploring a new way forward: using artificial intelligence to predict when the pressure will hit and adjusting staffing before it does.
At Connecticut Children’s Hospital, a team of clinicians and data scientists built an AI model that uses weather forecasts, school calendars, and historical data to forecast emergency department volume. The tool was paired with simulation and optimization engines to recommend ideal staffing levels. In Hartford, this meant making real-time staffing decisions before bottlenecks began.
“There’s a whole host of things that AI can be used for to help better resource allocations and optimize the care we’re providing to our patients,” said Dr. Christine Finck, Chief of Pediatric Surgery at Connecticut Children’s.
The model earned third place at the inaugural Health AI Championship hosted by Yale New Haven Health, where teams competed to solve challenges like ED boarding and care delays. The greater achievement was demonstrating that hospitals can anticipate pressure points before they happen. The next step is ensuring they can act with equal speed.
ShiftRx steps up to transform predictions into action. When a surge is predicted, our platform makes it easy to respond in real time by posting shifts, deploying credentialed clinicians, and adjusting coverage based on live operational needs. Our mission is to fill last-minute gaps and stay one step ahead.
This model reflects a national turning point. A 2024 HIMSS-Medscape report found that while 86 percent of healthcare systems are already using AI, many still struggle to operationalize it. AI can detect patterns, but unless a staffing infrastructure is in place, those insights stall at the dashboard level.
We aim to close that loop. Our vision is to make proactive staffing the norm. If an algorithm predicts a 20% patient spike on Wednesday afternoon, ShiftRx ensures nurse managers are ready and already covered. The value of prediction isn’t in what we know, it’s in what we’re able to do next.
As Dr. Lee Schwamm, Chief Digital Health Officer at Yale New Haven Health, put it: “It is not AI replacing humans, this is AI augmenting humans... letting AI do what it’s good at, and letting humans then do what they’re good at.” This is the future we’re building toward, where staffing responds to real-world signals as fast as the systems that forecast them.
ER care will always carry uncertainty. But with the right tools, our response doesn’t have to. ShiftRx is helping hospitals bridge the gap between prediction and preparation, insight and impact.
Sources:
AI Adoption in Healthcare Report 2024
HIMSS: Driving the Future of Health with AI