A digital twin is a virtual copy of a real system, object, or process. It updates in real-time to match what happens with the actual thing. In healthcare, digital twins can be models of medical devices, hospital tools, workflows, or even a patient’s health condition.
Digital twins are different from simple simulations or static 3D pictures because they change and interact with live data. They help hospital managers and IT staff watch, test, and improve daily operations. They use data from devices connected to the Internet of Things (IoT), sensors, and smart computer programs called artificial intelligence (AI).
For example, a hospital might create a digital twin of its emergency room processes. This includes data about how many patients arrive, staff work schedules, room use, and equipment condition. By testing ideas in this virtual model, they can find problems, see what will happen if changes are made, and better use resources without disrupting the real hospital.
In the U.S., where money can be tight and hospitals have many demands, digital twins offer real benefits. A 2025 survey by Hexagon found that 92% of groups using digital twins saw returns more than 10%, and over half had returns of 20% or more. This shows digital twins are being used more to save money and improve work.
Digital twins let hospitals plan and test process changes on computers before doing them in real life. This lowers the chance of expensive mistakes. For example, digital twins help predict when machines might break so hospitals can fix them early. This means less machine downtime and longer use of costly devices.
Studies using Simio’s Process Digital Twins showed hospitals could cut operational costs by up to 30% by using resources and schedules more wisely. Hospitals also reported 25% less unexpected downtime, which helps departments run smoothly without wasting time or money.
One big benefit is using resources better, such as staff, equipment, and space. Digital twins model hospital work in detail to find resources that are not used enough or that are overloaded. This helps managers fix workflows, set priorities, and stop waste.
Hospitals have seen a 20% boost in resource efficiency and a 15% cut in work-in-progress. This helps get patients care faster and lowers extra staff overtime. These improvements are especially important for hospitals in rural areas with fewer resources.
Because budgets often limit new building in U.S. hospitals, making current spaces work better is needed. Digital twins help with planning by showing detailed system-wide operation data. For example, Caboolture Hospital used digital twins in its design phase to lower building risks. They improved hospital operations without needing major renovations. Data helped use beds and rooms more efficiently.
Digital twins rely a lot on the Internet of Things (IoT). IoT means putting sensors on physical things to collect and send live data. In healthcare, IoT sensors watch patient vital signs, track medical equipment, and check the environment like temperature and air quality.
These sensors act like the “nervous system” of the digital twin. They give real-time data to keep the virtual model synced with the real environment. This constant data lets hospital managers change processes fast when things need attention.
For example, hospitals can check incubators in newborn units or refrigerators with medicines remotely. This helps keep conditions right and avoid costly equipment breakdowns. Staying synced in real time means care happens smoothly and resources are not wasted.
By 2025, 75% of industries, including healthcare, are expected to use digital twins with IoT to work better. U.S. hospitals want faster patient triage and better use of critical care resources.
Apart from running hospitals well, digital twins are also used in patient care. Doctors can make virtual copies of organs or body systems to test how diseases grow and try treatments in a safe, digital space.
For example, for patients with heart disease, digital twins can model their condition to help doctors adjust treatment before giving it for real. The models update with data from wearable devices that track heart rate, blood pressure, and oxygen levels. This helps care change quickly based on how patients might respond.
This method reduces guesswork and emergency visits. It also lowers costs from hospital readmissions and complications. It supports new healthcare payment models that pay for value rather than just services.
Artificial intelligence (AI) is important in making digital twins work well. AI looks at lots of data from twins and IoT devices and gives predictions to help managers make better choices.
AI helps predict when medical devices like MRI machines or building systems might fail. This lowers sudden repairs and keeps downtime low. It also reduces the work needed by maintenance teams and extends the life of equipment.
Digital twins with AI help make better staff schedules. Managers can try different shift plans, nurse-to-patient ratios, and staff assignments without real-world risks. AI finds the best plan to give good care without spending too much on overtime or extra staff.
As patient numbers change, AI-driven digital twins can quickly change patient routing or room assignments. This lowers crowding in busy areas like ERs or surgery rooms. It helps move patients faster, raises satisfaction, and cuts wait times.
Simio’s digital twin platform lets hospital leaders test new rules, layouts, or technology virtually. AI speeds this up by checking many “what-if” situations and picking the best plans. This saves up to 40% on innovation costs and cuts wait times for new steps by half. Hospitals can adjust quickly to rule changes or new demands.
Hospitals in the U.S. face special challenges. These include complex insurance, strict rules, and very different patient needs. Digital twins fit well here because they give detailed data and forecasts designed for each facility.
Using digital twins matches U.S. goals like lowering costs, paying for value, and better patient results. Hospitals and clinics can use twins to check safety rules and use resources well for Medicaid and Medicare patients.
Because labor costs are rising and staff shortages happen, especially in rural places, digital twins help hospitals do more with fewer people. Improving workflows and automating admin tasks help managers use their staff better.
Some big companies show how digital twins work well. Alcoa, a large manufacturer, used Simio’s system for over seven years to help with daily choices and long-term planning.
In healthcare, Bristol Myers Squibb uses similar models to spread digital twin use to teams in different locations. This helps sites improve using data without each needing expert staff.
The U.S. healthcare system is just starting to use digital twins widely, but the technology is growing fast. Combining digital twins with AI and IoT may help hospitals become stronger, save money, and give better care.
Healthcare leaders should work closely with IT and clinical staff to make sure digital twins meet their needs and handle risks well.
Digital twins offer a useful advance for U.S. healthcare. They help simulate and improve hospital operations, personalize treatments, and automate maintenance and staffing decisions. This supports care that is more cost-effective and sustainable. As technology advances and AI and IoT become part of it, hospitals that adopt digital twins may run better and care for patients more effectively.
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