GE HealthCare Announces CareIntellect for Operations, Helping Health Systems Optimize Resources and Expand Access to Care

• Two leading academic medical centers will be the first health systems to implement CareIntellect for Operations
• Solution provides a 72-hour view of emerging operational bottlenecks and delivers actionable guidance tied to discharge, imaging, transfer, and other capacity needs
• Combines GE HealthCare’s proprietary AI models and more than two decades of hospital operations expertise

CHICAGO--(BUSINESS WIRE)--GE HealthCare (Nasdaq: GEHC) today announced CareIntellect™ for Operations, a new AI-enabled Software-as-a-Service (SaaS) application designed to help health systems forecast capacity constraints up to 72 hours in advance, providing comprehensive unit-, department-, and enterprise-level views of emerging bottlenecks. By analyzing hundreds of patient- and operational-level data points—including bed availability, patient delays, staffing, wait times, and ancillary services—CareIntellect for Operations predicts constraints and helps operational leaders decide what to do next by recommending prescriptive actions to optimize areas including capacity and throughput. The Queen’s Health Systems and Duke Health will be the first health systems to implement the application.

Health systems are facing rising demand, staffing shortages, and increasing costs. In 2025, inpatient volumes increased 5.3%, requiring health systems to care for more patients while operating at or near capacity.^{1, 2} In this environment, operational visibility and predictive insights are more important than ever. Yet leaders currently spend up to several hours each day gathering and analyzing data to answer basic operational questions, including pulling and reconciling data from multiple systems with little or no predictive foresight into oncoming bottlenecks. In some cases, teams still rely on manual processes to track operational updates and escalate issues. Even after leaders create a picture of the current state, they must then spend additional time determining how to mitigate emerging issues before they cascade into system-wide disruptions. These operational inefficiencies can create added churn for care teams, constrain patient access, and impact speed and quality of care delivery.

CareIntellect for Operations is designed to help health systems shift from reacting to operational pressure to anticipating and proactively managing resource constraints and bottlenecks. The application uses two proprietary GE HealthCare AI models. The Pressure Forecast model analyzes historical hospital operations data alongside real-time insights from the EMR and other resource management systems to predict potential resource constraints across hospitals, departments, and units up to 72 hours in advance, including census, staffing, boarding and wait times across the emergency department, therapies, procedural recovery, and inbound transfers. The Estimated Day of Discharge model analyzes longitudinal patient data to predict when individual patients are likely to be discharged, with estimates updated hourly as new information becomes available. It then surfaces recommended actions and dynamically prioritizes operational workflows to help teams address system strain and mitigate impacts to access, quality of care delivery, or capacity.

The Queen’s Health Systems and Duke Health will be the first clinical evaluation sites to implement CareIntellect for Operations, providing frontline clinical and operational feedback that GE HealthCare is using to inform future enhancements and capabilities. The application is also informed by more than two decades of healthcare operations expertise. This includes insights from its Command Center software, which is used by nearly 500 hospitals and medical facilities globally. Command Center customers have reported measurable operational outcomes, including up to $20 million in first-year cost savings,³ more than a one-day decrease in length of stay,⁴ and increased capacity to serve 19,000 additional patients annually.^{5, 6}

“At Queen’s, improving access for the communities we serve is one of our top priorities, and optimizing our operations is critical to helping us achieve that,” said Alex Wroe, Chief Operating Officer at The Queen’s Medical Center. “We’ve seen firsthand how this type of advanced operational software can help us free up more capacity and better use our resources. We look forward to taking this work to the next level, helping us move beyond reacting to capacity challenges and toward proactively ensuring that our beds, teams, and resources are available for the patients who need them most.”

"Managing demand and capacity across our system in a coordinated, predictable way is essential to delivering exceptional care,” said Katie Flanagan, Associate Vice President Patient Flow and Care Coordination at Duke Health. "CareIntellect for Operations builds on three years of partnership with GE HealthCare, giving our teams a three-day view of what's coming so they can move faster from analysis to action, for the benefit of our patients.”

CareIntellect for Operations is part of GE HealthCare’s CareIntellect™ family of clinical and operational applications which share a common, cloud-first infrastructure designed to allow customers to quickly and securely onboard new CareIntellect applications without having to take a costly and time-consuming product-by-product integration approach. CareIntellect for Operations runs on Amazon Web Services (AWS) and is available for purchase directly from GE HealthCare as well as through the AWS Marketplace.

“Health systems need to know where pressure is building and what to do next. CareIntellect for Operations brings together patient and operational signals to give teams a 72-hour view of emerging constraints and help them act earlier,” said Dr. Taha Kass-Hout, Global Chief Science and Technology Officer at GE HealthCare. “AI in hospital operations has to give teams predictions they can understand, workflow-connected recommendations they can use, and a system they can trust at the point of decision—and that is the bar we designed this solution to meet.”

CareIntellect for Operations supports GE HealthCare’s strategy to deliver a new wave of innovation and further differentiate its portfolio of AI-enabled SaaS offerings that help health systems expand access, manage capacity, and keep care moving. Since 2023, GE HealthCare has invested more than $5.1 billion in innovation to elevate care, support clinicians, and streamline operations.

For more information on CareIntellect for Operations, visit: https://www.gehealthcare.com/en-us/products/software/careintellect/careintellect-for-operations?utm_source=newswire&utm_campaign=USC-USC-STO-CIO-AO-AWR-BL-26-09&utm_medium=article&utm_content=nw-press-release&utm_term=organic

^1 American Hospital Association, “Costs of Caring: Challenges Facing America’s Hospitals as They Care for Patients in 2026,” March 2026, https://www.aha.org/costsofcaring.

^2 UCLA Clinical and Translational Science Institute, “The U.S. Could Experience a Critical Hospital Bed Shortage by 2032, New Research Warns,” April 30, 2025, https://ctsi.ucla.edu/the-us-could-experience-a-critical-hospital-bed.

^3 GE HealthCare, “Command Center Helps Improve Patient Flow, Saving $20M in First Year: Case Study: The Queen’s Health Systems,” 2025, https://www.gehealthcare.com/content/dam/gehc/sitecore-migrated-assets/gehc/us/images/products/software/commandcenter/case-study-the-queens-health-systems-may-2025.pdf.

^4 GE HealthCare, “Command Center Helps Improve Patient Flow, Saving $20M in First Year: Case Study: The Queen’s Health Systems,” 2025, https://www.gehealthcare.com/content/dam/gehc/sitecore-migrated-assets/gehc/us/images/products/software/commandcenter/case-study-the-queens-health-systems-may-2025.pdf.

^5 GE HealthCare, “Regional Command Center Helps Create Capacity for 19,000 Additional Patients Annually: Case Study: Providence Swedish – Puget Sound Region,” 2025, https://www.gehealthcare.com/content/dam/gehc/sitecore-migrated-assets/gehc/us/images/products/software/commandcenter/providence-1-page-case-study-090525-rgb-v2.pdf.

^6 The results are not prescriptive and could vary depending on user, electronic patient medical records software used, and level of adoption.