Digital Twin Revolution in the Healthcare Industry 2021

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Digital Twins concept is no more science fiction; it has many real-life applications too. Digital Twin in healthcare is making headway. This technology allows creating a virtual representation of a physical object or system. Dassault’s Living Heart project was the first realistic virtual model of a human organ. The options have expanded during recent years to include large items ranging across industries. 

Digital Twin Explained

A digital twin is a virtual replica of a physical asset or process, used to analyze the physical counterpart’s performance. In healthcare, a digital twin can be defined as a full-life data of any patient combined with AI-powered techniques that perform data analysis to answer a range of clinical queries. 

A digital twin can be used for predicting procedure outcomes. It can be useful in finding out the right treatment option for a specific patient. 

Why & How To Design Digital Twin?

Advantages of digital twin technology across industries are widely known be it improving the performance of asset or process or reducing unnecessary costs.

Digital Twin in Healthcare Examples

In order to design a digital twin, firstly, select the enabling technology that will be integrated with the physical asset within its digital twin for real-time data flow from the IoT devices. Secondly. Understand the information type required across the asset life-cycle, where that information is stored, and how it can be accessed and analyzed.

Digital Twin Use Cases

Some of the important and widely accepted use cases of Digital Twin are listed below: 

  • R&D

In healthcare, digital twin simulations are used to build models that can create data that helps in research and development. Even doctors refer to it to observe and re-define care delivery models, capacities, staffing, etc.

  • Diagnosis

In the healthcare context, a digital twin can monitor and analyze a patient’s data using a biophysical model. A doctor can provide the most current treatment in managing a patient’s healthcare through remote by analyzing the patient’s historical and current data. In fact, digital twins work on Machine Learning (ML) techniques to revolutionize healthcare practices and enhance the patient experience. 

  • Surgery

Digital twins simulate healthcare procedures to predict the outcome before the therapy is selected. Additionally, a virtual replica of a patient’s organs enables surgery in a simulated environment rather than on a real patient.

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This can also be extended to medical colleges where aspiring surgeons can develop theoretical expertise before assisting a surgeon in real-time. 

  • Medical Equipments

Digital Twin technology in medicine helps to analyze a patient’s health records and also medical equipment’s performance used under different circumstances. The performance and criticality of the equipments for various medical processes is critical to every treatment. 

  • Monitoring

A digital twin can assist in analyzing complete data with reference to a hospital – available bed count, healthcare professional’s schedules, etc. Easy availability of this information will help optimize not only cost but also enhance the patient experience. This is very important in healthcare as it helps in enabling strategic decision-making in an otherwise complex and sensitive environment.

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With predictive analysis through simulation, models can be built that detect symptoms at early stages. As we know, in medical terms, prevention is better than cure!

Digital Transformation in Healthcare

The benefits of digital transformation in healthcare are many. Digital transformation is rapidly transforming the healthcare industry. Patients have transitioned from passive recipients of health care to active value-seeking consumers. With the advancement of technology and smartphone penetration, patients and their families have access to medical information more than ever before.

digital twin in healthcare industry

As a result of this transition and new government regulations, health care providers have to improve patient care and experience by adopting a variety of custom applications, which rely on trouble-free, real-time access to information in their IT environment. This adoption is driving the health care industry’s critical need for the best service to all the stakeholders.

Digital Twin in Healthcare Examples

To develop a customer-centric framework, the healthcare industry has realized that digital must be focused on. While investments in social, cloud and analytics are progressing and adding value, the healthcare industry leaders should look towards more sophisticated ways to deliver a best-in-class customer experience. Strategizing today for the post-digital world is essential as healthcare organizations continue to embark upon their digital transformation journeys.

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Treatment options vary depending on the patient’s condition, treatment history, etc. It could be something simpler like an oral dosage solution or something complex like a surgery. A digital twin encompassing a patient’s historical records, laboratory results, and genetic data, combined with a model of the clinical pathway is a boon to doctors and surgeons. It helps to ensure optimal decision-making with reference to the treatment of the patient. 

Conclusion

There are many examples of companies using digital twins. The concept of Digital twin hospital is seeing the light of the day. There are a lot of healthcare digital transformation trends that must be considered before embarking on the digital transformation journey.

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Building a digital twin of a human body requires an understanding of advanced and complex processes and a lot of understanding of human anatomy. Scientists and Technologists world over have been able to overcome these challenges and the future of Digital Twin has picked up the pace than ever before.

FAQ's

It is important to understand how an organization can move from traditional modeling and monitoring of assets to digital twins. This requires a clear-cut understanding of the existing business operations and the requirements. Digital Twin implementation examples also help understand the same. Implementation cost can be then figured out specific o the business use case. 

 

Some advantages of digital twin are predictive maintenance (thus lowering maintenance cost), better performance, and enhanced productivity. 

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