Predictive services

AI-powered predictive services from GE HealthCare monitor equipment around the clock,¹ helping to fix problems before they occur and enabling systems to stay up and running.

Predictive services in healthcare are more important than ever

The demand for predictive maintenance is growing because it can play a huge role in keeping equipment up and running. In healthcare, where downtime is costly, predictive maintenance has the ability to help minimize equipment failures, lower maintenance costs and extend equipment lifetimes.

Key stats

$81B

Projected size of the medical equipment predictive maintenance market by 2030²

$740k

The cost of each equipment downtime occurrence in the U.S.²

≤40%

The cost of predictive maintenance compared to fixing a machine after it breaks³

20-40%

Longer lifespan for equipment with predictive maintenance⁴

Our solutions

Reduce disruptions. Enhance care delivery.

GE HealthCare Predictive Services use AI and 24/7 monitoring¹ to help predict potential failures in imaging systems—helping to enable proactive maintenance and part planning and reducing unplanned downtime.

OnWatch™ Predict uses AI and digital twin technology to estimate remaining component life before disruption, helping to enable planned downtime and part replacement to help reduce impact.

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Tube Watch helps to predict X-ray tube or generation chain failures before they happen, helping to prevent disruptions, ensure timely care delivery and protect revenue.

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OnWatch helps maintain uptime for imaging systems by proactively detecting issues early—helping to minimize cancellations, support efficiency, and avoid disruptions in patient care delivery.

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OnWatch™ Predict uses AI and digital twin technology to estimate remaining component life before disruption, helping to enable planned downtime and part replacement to help reduce impact.

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Modality-level support

Magnetic Resonance (MR)

Supported by OnWatch Predict and OnWatch offerings

Computed Tomography (CT)

Supported by OnWatch Predict, OnWatch and Tube Watch offerings

Image Guiding Systems (IGS)

Supported by OnWatch Predict, OnWatch and Tube Watch offerings

Molecular imaging (MI)

Supported by Tube Watch offerings

Mammography

Supported by OnWatch Predict and Tube Watch offerings

Radiography systems

Supported by the OnWatch offering

Monitor: Real-time system surveillance

Our real-time system surveillance combines IoT data collection, digital twin technology, AI and machine learning to create a system that can help anticipate and address equipment issues before they impact patient experience or workflow.

Predict: AI-powered failure forecasting

Just one day of unplanned downtime can result in canceled scans and lost potential revenue.⁵ Thanks to digital twin technology, we have the ability to assess the remaining life of a component in a system before it’s down or limited in use. Planning for maintenance ahead of a failure can help decrease downtime.

Repair: Proactive service scheduling

We offer proactive service scheduling through solutions like OnWatch and Tube Watch to help minimize unplanned downtime, reduce costs and optimize care delivery by helping to ensure equipment reliability and availability.

Restore: Fast return to full functionality

When an issue is identified through predictive maintenance, we can work to quickly assess the problem, develop a repair plan, and dispatch parts for timely on-site service. Some failure modes are able to help significantly reduce unplanned downtime through this process.

Measurable results

≤ 36

Hours of downtime saved^6,7

≤ 89%

Reduction of unplanned downtime for failure of the X-ray tube or X-ray chain with Tube Watch⁸

≤ $20k

Reduction of unplanned downtime for failure of the X-ray tube or X-ray chain with Tube Watch⁹

References

Availability of 24/7 remote monitoring and predictive analytics is subject to customer connectivity and applicable service plan. GE HealthCare disclaims liability for service interruptions due to connectivity issues or plan limitations.
MarketsandMarkets, “Predictive Maintenance Market Share, Global Industry Size Forecast,” MarketsandMarkets, n.d., March 2024, https://www.marketsandmarkets.com/Market-Reports/operational-predictive-maintenance-market-8656856.html.
Simbo Ai and Simbo Ai, “Cost Benefits of Predictive Maintenance: How Healthcare Facilities Can Save Resources and Optimize Operations - Simbo AI - Blogs,” Simbo AI - Blogs - (blog), June 22, 2025, https://www.simbo.ai/blog/cost-benefits-of-predictive-maintenance-how-healthcare-facilities-can-save-resources-and-optimize-operations-3101482/.
Ai, Simbo, and Simbo Ai. “The Role of Predictive Maintenance in Healthcare Facilities: How AI Is Transforming Equipment Management and Reducing Downtime - Simbo AI - Blogs.” Simbo AI - Blogs - (blog), June 28, 2025. https://www.simbo.ai/blog/the-role-of-predictive-maintenance-in-healthcare-facilities-how-ai-is-transforming-equipment-management-and-reducing-downtime-2321345/
Zavatarelli, Mike. "Beyond Downtime: Redefining Predictive Medical Equipment Maintenance." GE HealthCare, Oct. 9, 2024. https://www.gehealthcare.com/insights/article/beyond-downtime-redefining-predictive-medical-equipment-maintenance.
Results are estimates based on AI model recall performance.
Estimated yearly downtime savings are based on the same population of ~2,000 CT systems, comparing systems with OnWatch Predict activated versus those without for a one-year period.
Calculation is based on the average downtime caused by tube or X-ray generation chain failures single event versus the average planned labor time. Source: One Model Explorer, using data from over 1,300 systems in USCAN and EMEA (2021). Results may vary and are not guaranteed for all customers.
GE HealthCare calculations are based on data from Decision Resources Group and CMS.gov (2017), API Healthcare (2015), and Global Hospital Executives Insights – ITG Market Research (2015).

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Predictive services