The Emergency Department is a fast-paced, tightly run ecosystem with many spaces for specific functions, and multiple events happening at any one time. Together with Vouse and FARM, Changi General Hospital (CGH) saw an opportunity to innovate through the development of a smart hospital digital twin for its Emergency Department to provide more holistic perspectives for decision-making to support patient care.

By combining knowledge and experience in user design, spatial experiences and visual technology, the digital twin enabled the team to consider all aspects of the emergency department ecosystem, including space, people, activities, workflow and time to address complex challenges. Through this project, we hope to enhance the approach to healthcare design and planning, as well as to improve experiences for patients, family members and healthcare workers.

This project is produced by hyperfield, an experimental aggregation of FARM and Vouse that aims to multiply ideas and accelerate transformation of organizations who want to become better versions of themselves. Hyperfield and CGH worked together to develop this digital twin, a first for an emergency department in Singapore.

With this digital simulation, hyperfield and CGH are able to experiment on new models of care on different dimensions against multiple scenarios in a safe environment, to find the sweet spot between people, space, workflow and activities. The insights gained from the Digital Twin will be applied to the design of CGH’s future A&E remodeling plans. Our methodology consists of 4 mains steps:

1. Workshops and Interviews

A series of workshops, interviews and surveys are conducted with key stakeholders and on-the-ground personnel (doctors, nurses and patients) to identify key roles and responsibilities in the hospital ecosystem as well as to quantify the scope for simulation. Coupled with research on existing academia and alternative methodologies, the basic parameters for the simulation are established at this stage.

2. Establishing Scenarios

Using the extensive information gathered in the workshops and interviews, various scenarios were set up for the different key actors in the simulation. At this point, historical data is input into the system as a reference point, as well as to identify extreme cases in the simulation. The upper and lower limits of the simulation are established, so as to ensure that realistic results can be achieved.

3. Prototyping and Simulation

A complex simulation was created with Unreal Engine, to run the tests. The existing hospital layout is created in 3D, to simulate the effects of space and wayfinding and how it affects the efficiency of the A&E department. Different scenarios were input into the system, in the form of tasks and events to be completed by the different actors (doctors, nurses and patients). Each actor makes their own decision in real-time, depending on the evolving scenario and the situation at hand. As the simulation runs, the user may observe staff movement and A&E task completion via the 3D simulation, as well as real-time dashboard.

4. Results Analysis and Recommendations

The user may tweak the starting conditions and staffing ratios to quickly simulate various manpower structures and workload. At the end of the simulation, a summary of simulation results is generated. At a quick glance, users may view immediate choke points and task failure rates, to quickly determine points of critical failure. By tweaking the initial staffing settings, users can then discover ways to mitigate these critical failures.

A detailed result dissection and report was created to identify further insights and recommendations for the CGH A&E team to review. The next stage of the project would consist of adding in different spatial configurations to simulate and find out the optimal spatial layout for future construction of the new A&E department.

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