How Providers Can Use Digital Twins in Healthcare

COVID-19 underscored the healthcare sector’s need for holistic design planning capabilities to foresee the upstream and downstream impacts of a complex system that interacts with the entire community. From being able to predict a health system’s infrastructure, staffing, and equipment needs in an emergency, to more structured processes, and designing superior health facilities with the right resources, it is essential for healthcare organizations to use data to visualize the systemic impacts of emergency scenarios.

As the industry grapples with volatility and uncertainty in the form of complex capacity, demand, and workforce challenges, digital twins are introducing new ways to manage and innovate operations, move away from manual processes, and embrace the powers of AI and machine learning to catapult healthcare into a new era.

The Era of Digital Twins in Healthcare

The future of healthcare will be focused on managing industry complexities—and it is here that digital twins can advance operations from good to great. Digital twins are highly complex models that use AI alongside large amounts of data to accurately mimic a real-world object. For example, they can gather data from wearable devices, patient records, pharmaceutical companies, device manufacturers, and other healthcare departments. That data can then be manipulated to allow clinicians and healthcare providers to easily test potential interventions in real-life situations.

Growing investments in digital twin technologies are introducing intelligent opportunities to benefit clinicians, healthcare organizations, and patients. The future is not simply one digital twin per organization, but rather a massive network of digital twins connecting to create virtual models of facilities, supply chains, medical products, and even body parts and organs. Providers will be able to create digital twins at different levels of sophistication to match their use cases.

Soon digital twin technologies will be critical to every healthcare enterprise’s clinical and operational strategy. By transforming existing data into interactive digital twin models that test costly interventions or plans in digital environments, healthcare providers can deploy the most efficient and cost-effective strategies at scale in the real world. Industry leaders are preparing for this by identifying use cases and building the infrastructure needed to successfully develop and deploy them—and gain a return on their investment.

Digital Twin Use Cases in Hospitals

Superior Management of Hospital Resources and Operations

What if you didn’t have to guess how a scenario would affect your hospital’s bed capacity? In a post-pandemic era, hospitals across the nation are reeling with extremely challenging bed-capacity issues and lengths of stays that are exceeding payer expectations, compounded by staffing shortages and razor-thin financial margins. The topic of “patient throughput management” is almost nightmarish for administrators, executives, and caregivers alike. Virtually every hospital in the country has a priority initiative to manage throughput, including by implementing hospital-at-home strategies.

However, a hospital is a complex and dynamic environment. A lot can change from day-to-day and hour-to-hour. The patient population can swing, staffing availability could change, there could be a sudden influx of patients in the emergency department (ED), or a breakdown in the internal infrastructure could hold up vital testing and critical procedures. Imagine then, having a “digital twin” of the hospital. Before any of these issues occur, imagine the possibilities if hospitals could simulate the “what-if” situations that enable good decisions if a scenario were to play out. This might include predicting the success of potential interventions to address challenges like increasing bed capacity, an influx of a certain type of patient population (mass casualty, local disease, etc.), managing emergencies during shutdowns, offering virtual and home care, or initiating “code purple” protocols.

With the use of digital twins, healthcare organizations can also forecast what they will need in any scenario, including staffing, resources, and infrastructure. This will allow hospitals to place patients more effectively in the right settings, create new opportunities for optimizing patient flow, and eventually automate their operational processes. A future possibility could include adding machine-learning algorithms to analyze the data collected and make predictions for better business decisions.

Improving Utilization in Operating Rooms and Surgery Centers

The operating room (OR) department is at the intersection of several value streams. When synchronized, it functions like a “well-oiled machine,” with its peak utilization exceeding 80% of the available capacity. However, it is incredibly difficult to achieve this level of synchronization without advanced process capabilities, monitoring, and a constant study of optimization.

OR departments with 10, 20, or even 30-plus rooms are complex ecosystems. They are cleaned and prepped within 30 minutes between surgical cases; and patient care for various services, including cardiology, orthopedics, etc., can require complex systems and equipment that aren’t always available for every room. Then there is the supply chain in the form of “carts” that bring in specifically sourced supplies and other equipment customized for the surgeon, the patient, and the type of procedure. All these things happen in rooms and behind closed doors with limited visibility.

If a digital twin monitored these complexities to continuously identify areas of breakdown or opportunities for optimization it would act like a virtual “air traffic controller” assisting OR leadership. After decades of managing the OR with manual processes, this could be the solution to achieving 80% utilization.

Twinning the Emergency Department

The ED can be described as the most vital organ for any hospital, where most hospitals see 80% or more of their admissions. A typical hospital-based ED sees more than 100 patients daily and is staffed with skilled clinicians, equipment, resources, and protocols to handle any and every possible scenario.

Today, many intra-city EDs are constantly at overflow capacity, occasionally on divert (sending the non-critical patient population to another ED), boarding (admitted) patients who are “stuck,” and facing significant staffing issues.

Imagine the possibilities a digital twin presents, in identifying blockages to patient flow, running “what-if” scenarios of where patient care could be transferred or temporarily lodged to alleviate the situation. The digital twin would allow testing of various scenarios before moving critically ill patients.

Healthcare Leaders are Getting Ready

These three digital twins use cases are the most common operational scenarios in a hospital. However, the applications are endless. There are plenty of individual functions and departments that could benefit from having an active digital twin, including outpatient functions, such as lab work, imaging, and interventional services and clinics.

In another frontier yet to be crossed, digital twins could also be applied to studying what-if scenarios in care and clinical pathways to optimize a patient’s care while benefitting the bottom line. By combining views of patient data scattered across various medical applications, physicians and specialists could build digital twins to predict the outcomes of their care decisions. For example, providers could create a real-time medical dashboard providing patient-specific information to predict and improve clinical decision-making at the point of care. Providers could also test changes to operational activities on patient outcomes, such as care delivery programs, staffing allocation, appointment scheduling, bed facilities, and other decisions that affect a healthcare organization’s top and bottom lines.

The benefits of digital twins for healthcare providers can be summarized as:

1. Enhanced decision-making and operations capabilities
2. Testing interventions before costly infrastructural implementations
3. Minimized risk associated with changing a complex system
4. Identifying flow and blockages
5. Preparing for unusual catastrophic events

Successfully leveraging digital twin technology often requires an experienced partner who understands the important role it can play in the future of healthcare. Through Discover, Guidehouse’s Innovation platform, we can experiment with digital twins and demonstrate the technology’s most creative potential for almost any sector or use case.

By Shashank Khandekar