The technology of digital twins in the healthcare of the future
A digital twin is the representation of a product or process created through the use of a computer program that uses real-world data to forecast efficiency.
One way manufacturers can improve their production is to embrace the Internet of Things, artificial intelligence, and software analytics.
Digital twin technology is widely used in industries such as healthcare, manufacturing, science and technology.
What is digital twin technology in healthcare?
A digital twin is a virtual copy of a physical entity or process, such as a patient, an anatomical structure, or a hospital environment. Along with extensive detail and moment-to-moment feedback on a patient’s status and health.
It relies on data sources including electronic health records (EHRs), disease registries, wearable sensors, and more.
In the near future, digital twins could be used to anticipate the onset of disease and assist in treatment and patient care.
Is digital twin health the future of healthcare?
Digital twin technology is becoming more and more common.
- The global digital twin market size was valued at USD 3.1 billion in 2020 and is projected to reach USD 48.2 billion by 2026.
- It is expected to grow at a CAGR of 58.0% during the forecast period. Increased demand for digital twins in the pharmaceutical and healthcare industries due to the outbreak of the COVID-19 pandemic.
- The changing face of maintenance and the increasing adoption of digital twin solutions to cope with the COVID-19 pandemic are the key factors driving the growth of the digital twin market.
Ways Medical Digital Twins Will Transform Healthcare
Digital Twin encompasses four technologies for creating visual representations, capturing, storing, analyzing data, and providing insights. These technologies are IoT, Extended Reality (XR), Cloud and Artificial Intelligence (AI).
Personalized health information
The pandemic has helped fuel the growth of digital health services that help people assess and treat simple illnesses using AI.
Through this digital twin solution, the efficacy and interactions of drugs in a patient’s body are monitored based on their personal characteristics, such as age, gender and kidney status.
Various apps are available to track and store health-related information, such as daily physical activity log, calorie intake calculation, and medication planning and appointment reminders.
An example of a digital twin includes therapy decision support for cancer treatment.
Digital Twin with patient imaging data, genetic data, and laboratory results helps the physician decide on the optimal treatment of surgery, radiation therapy, or hormone therapy.
To address chronic diseases in a significant population, Digital Twin helps detect them by analyzing physiological and behavioral data.
Advanced Surgical Planning:
Performing preoperative and postoperative tests and obtaining results on a digital replica of human body parts eliminates the risk of harming human health.
The National Institute of Health (NIH) develops digital twin models of athletes throughout their careers to accurately predict concussion-related brain injury trauma.
Remote patient monitoring technologies include apps or mobile devices that can measure patient health information, such as blood pressure or blood sugar, sleep patterns, and transmit it to the healthcare team.
The market for wearable devices is expected to be worth $51.60 billion by 2022 , it is critical to consider the benefits of integrating them with telemedicine software .
Drug testing and medical education.
Artificial intelligence algorithms are used to speed up drug trials.
In particular, digital twin technology is used to monitor and predict the impact of experimental drugs on patients in real-world settings.
In the future, it may also help clinicians improve the performance of patient-specific treatment plans.
Digital twins, combined with virtual/enhanced reality, are rapidly gaining momentum to meet the training and education needs of healthcare professionals.
Improve the caregiver experience
Digital twins can also help caregivers capture and find shared information between doctors and multiple specialists.
For example, if a person sees their regular primary care physician, they will have a basic understanding of the patient, their medical history, and their medications. If the same patient sees a specialist, many repetitive questions may be asked.
Using technologies like natural language processing, a digital twin can model the patient and use all the data to help understand what is happening to them.
This saves time and improves the accuracy of capturing and presenting information such as specific medications, health conditions that providers need to know in context to make clinical decisions.
Current trends and challenges
- Digital twins in healthcare revolutionize clinical processes and hospital management by improving medical care with digital monitoring and advancing human body modeling.
- Such tools are of great help to researchers in the study of diseases, new drugs and medical devices.
- Digital twin technologies enable simulations to find out how different people would react to different treatments.
- Medical digital twin technology can also be used to represent a person’s genome, physiological characteristics and lifestyle to fully personalize medicine.
- Increased health costs.
- Inefficient processes.
- Poor access to health care.
- Inadequate quality of care.
- And the lack of a specific treatment for the patient.
- With the promise of personalized health information, remote patient monitoring, advanced surgical planning, and many other digital twins, the demand in the medical field has increased significantly.
- Additionally, with the Digital Twin model, care environments, operational strategies and staffing help hospitals and medical practices optimize costs and improve patient care.
- Now in Healthcare, together with IoT data, Digital Twin Application in Healthcare will play an important role in improving the medical and healthcare sector.