Digital twins in future healthcare

FEATURE - Industry Innovation Article – Beca

The use of computers to digitally model the characteristics and simulate the operation of physical systems and processes is not new. Since the advent of the digital computer, the opportunities to use such technology to enhance our understanding of the operation of real-world systems have been widely recognised across many domains; including engineering, logistics, transportation, and climatology. 

In recent years, as the power of computer processing has continued to grow exponentially and with the evolution of techniques such as artificial intelligence and machine learning (AI/ML), we have seen the possibilities to extend digital modelling and simulation into some of the most complex areas of our lives, including biological systems. 

Digital Twin
The use of the term “Digital Twin” has crept into much commentary around modern technology trends, and in our experience is often an overhyped concept with inconsistent or confusing definitions.

In our view, a digital twin is simply a computerised tool established to enable insights to be derived, these insights then lead to enhanced decision making. 

We define a digital twin as a digitised representation (or “digital replica”) of a physical (natural and human-made) system or process, whereby the digital replica looks and behaves like the real-world system or process, and responds to real-world inputs. We therefore see that a digital twin typically comprises of a visual model, a logical model, and a simulation engine, with inputs from external sources (such as sensors).

Digital twins offer great promise in the healthcare segment, far beyond the potential to optimise the operation of physical assets and processes. 

Through the power of low-cost sensors, mobile computing, terrestrial wireless communications, computer vision, and AI the possibility to accurately simulate systems within the human body is an emerging reality. 

Furthermore, the concept can be extended to a community of citizens where the opportunity to leverage the power of contemporary digital technologies to significantly improve community healthcare outcomes is a plausible scenario over the next 10 years.

For hospitals of the future, we can envisage an integrated ecosystem of three Digital Twins:
● Personal Digital Twin
● Hospital Digital Twin
● Community Digital Twin

(Click to view enlarged image)

Personal Digital Twin

Conceptually, a human digital twin would comprise; sensors, analytics and visualisation.

Sensors are used to collect data about the operation of the various human systems. Such sensors can range from medical devices widely used in healthcare environments (such as blood pressure monitors and oximeters) to personal wearable devices (such as smart watches and wireless patient monitoring devices). 

AI based analytics tools will be used to process patient data to derive insights about current medical conditions as well as being able to make predictions about emerging conditions. This then leads to the possibility of targeted interventions at an early stage (the notion that prevention is better than cure). It will also be possible to factor in wider aspects of health, such as diet and exercise.

Currently, visualisation typically involves textual or graphic information presented on computer displays. We expect to see the adoption of 3D technologies (such as holographic displays) to enhance the understanding of medical conditions, particularly where there is a need to convey complex information. 

Furthermore, it will be possible to visually simulate the potential outcomes of a particular medical condition over time.

Hospital Digital Twin & Command Centre
A Hospital Digital Twin has the same component categories as the Personal Digital Twin (Sensors, Analytics, and Visualisation).

Sensors are used to collect data about the operation of the hospital, from the perspectives of the physical infrastructure as well as clinical and administrative operations within the hospital. Data will be collected from a wide range of sources; including building systems (i.e. those systems that provided fundamental building services such as power, conditioned air, vertical transportation, medical gases, etc), environmental sensors (measuring temperature, humidity, air quality), visual sensors (such as CCTV cameras), and object tracking sensors (such as asset tracking and human occupancy sensors).

AI based analytics tools will be used to process building and operations data to derive insights about:
● The performance of the building and the systems that deliver the required services
● Achievement of sustainability and wellness goals
● The performance of key operational processes (such as management of patient flows)
● Asset optimisation (e.g. bed allocation)
● Emergency responses and scenario planning
● Hospital financial performance

An integrated “Command Centre” will provide the appropriate focal point for accessing data and insights from the Digital Twin. The Command Centre (relatively new for Healthcare, but well established in other sectors like defence, energy and aviation) should be both physical and virtual, and provide the following functions:
● Management of hospital operations (hospital capacity, bed management, patient flows, etc)
● Management of building operations (energy management, environmental management)
● Security management
● Incident response management
● Emergency scenario planning

The Command Centre will be a focal point for decision making in a hospital, as well as a hub for continuous improvement. The Command Centre should enable a real-time wholistic overview of the operations of the hospital.

Community Digital Twin
The concept of a Community Digital Twin considers the potential to monitor the health of an entire community, using a wide range of data sources and sensors. Such data could be used predict outcomes, particularly the impacts of epidemics and emerging health threats. This leads to longer term benefits for health response planning and capacity management.

The Digital Twin Ecosystem
By 2030, we envisage the notion of “healthy city digital twin” will be a feasible outcome, whereby all components within the ecosystem of a healthy community are able to be digitally modelled; including the physical infrastructure, clinical systems and processes, human physiological systems, and the overall health of a human population. 

With a healthy city digital twin; planners, administrators and healthcare professionals have the chance to gain valuable insights into a wide range factors that influence community health outcomes; including:
● Infrastructure requirements (current and future)
● Clinical space, workflow and resource planning
● Predicting the impact of emergencies
● Predicting the impact of community health and wellbeing improvement initiatives
● Target early interventions for at risk individuals
● Improvements to the accuracy of treatments and interventions
● Accelerate the development and deployment of innovative healthcare practices
● Delivery of “data-driven” personalised medicine

Our vision is for a healthy city digital twin as a key enabler for the delivery of high-quality care to the community. We believe the digital twin of the future will be a transformative approach to the use of a sophisticated computing architecture to connect different parts of a whole system, whether an individual patient and the systems their body, or the systems of care within the healthcare ecosystem. 

The goal is to mine actionable insights that enable better decision making and ultimately deliver improved patient and community outcomes.

To learn more about how a digital twin is being deployed in the New Zealand health sector, watch the free eHealth TV webinar on Digital Hospitals: Merging sustainability and technology.

Author: Bruce Neville, Senior Director – Technology Consulting, Beca

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