Digital Twin

Healthcare delivery is massively complex. Digital Twins help leaders design and execute models of care which are revolutionary for patients, families, and caregivers.

What is a Digital Twin?

A Digital Twin virtualizes a hospital as a safe environment to test changes in system performance. In other words, to play “what if?” with system dynamics.

Common sense, spreadsheets, and statistics just don’t have the horsepower to inform strategic decisions. Digital Twin does.


Objectively determine what actions to take

By creating a Digital Twin of your hospital(s) (and related ambulatory services), we can test potential changes in operational strategy, capacities, staffing, and care delivery models to objectively determine which actions to take.

Industrial-grade discrete event simulation

An industrial-grade discrete event simulation model developed in collaboration with GE’s Global Research Center, the Hospital of the Future Simulation Suite was designed specifically for use in healthcare to focus on the problems and scenarios that differentiate this industry from others.

Properly modeling patient and staff behavior, variation in demand and supply, patient pathways necessitated a new and more powerful tool than otherwise available and thus “HoF” was born.

In addition to being purpose-built for healthcare applications, HoF has a few key attributes:

  1. Speed. Using HoF, GE HealthCare analytics consultants can model academic medical centers in about two months.
    This speed means hospital leaders can run more scenarios and develop better go-forward plans. This includes the time to gather data, review workflows, and build the model.
  2. Modular. HoF Digital Twins are built to be expanded. This means GE HealthCare can start by modelling an ED, then add the OR, then complete the hospital; and add the other hospitals in the system later.
    Or, GE HealthCare can start with hospital system macro-dynamics and work back to the unit- and department level micro-dynamics later.
  3. Durable. HoF models are built to last. Some of our simulation models are more than five years old and still used on a regular basis. For clients on the “scenario service”, GE HealthCare updates the data as needed and is available to test scenarios ad hoc.
  4. Dynamic. Traditional modeling approaches are static and rely on average behaviors. Hospitals and patients are variable, interdependent, and dynamic and rarely act as the average would indicate. HoF learns the statistical behaviors of patients, staff, and resources, and replays these in a more true-to-life fashion.

The inherent complexity of healthcare delivery means that making strategic capacity decisions can be a massive challenge.

Adding a few bays to an Emergency Department could result in congestion in Critical Care which could lead to backups in the OR which could result in a shortage of Anaesthetists.

Understanding the global impact of local changes is of critical importance, and doing so requires a toolkit whose sophistication matches the complexity of the healthcare space.

Digital Twins from GE HealthCare are built for this purpose and high-performing organizations around the world continue to return to this toolkit to support the strategic decisions that drive their capacity planning and flow improvement agendas.

How does a Digital Twin work?

Digital Twins enable massively collaborative, data-driven, and scenario-based decision making.


Without a Digital Twin, leaders rely on tribal knowledge and basic analysis to plan new facilities and next year’s budget for existing facilities. This is normal but it leaves much to be desired.

What's the Impact?

Real Time Information
Discharge planning with MDRs
Bed Re-Alignment
ED-to-Unit Handoff
OR Schedule Redesign


ED Boarding
Excess Bed Days
Pathway Non-Compliance

Digital Twins target process improvement efforts by putting each process improvement project into larger context. This enables us to charter projects with specific goals tied to both local and system performance.

What has Digital Twin simulation helped to solve?


Bed & Level of Care Configuration

Understanding the number of beds by level of care required to match capacity to the timing and profile of demand.


Surgical Block Schedule Optimization

Designing a surgical schedule that is optimized not only for theaters and surgical staff but also for downstream resources.


Health System Facility & Service Line Growth Strategy

Building a strategy to help a facility or enterprise achieve its growth strategy while maintaining an efficient and effective operation.


Facility Design for New & Existing Facilities

Matching facility design, staffing design and model of care to each other.


Optimization of Process Improvement Funnel

Evaluating the impact of process improvement ideas on organizational priorities and building an implementation roadmap from those that make the biggest difference.


Staffing Model Design

Developing departmental or enterprise-wide staffing plans that align to the dynamics of predicted demand.

Download the Executive Brief

Capacity Strategy Powered by a Digital Twin

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