Precision Diagnostics and Digital Twins: Transforming the Future of Healthcare
- hiranmaydash
- Sep 2, 2023
- 6 min read
Introduction
The post-COVID-19 has completely changed the healthcare landscape. The healthcare sector is about to enter into rapid change. The influx of new technologies and discoveries is propelling patient care through patient empowerment. This is fundamentally changing how we prevent, diagnose, and cure diseases. The focus of healthcare is changing from treating illness to caring about wellness.
Technology is already playing a major role in healthcare, and this trend is only likely to continue. We can see wide adoption of AI and other digital technology to improve healthcare both inside the hospital and outside the hospital.
For instance, the next frontier of healthcare delivery for the USA is patient-centric, virtual, home-based technology-driven as stated by Mckinsey. Out of which, the productivity from technology-driven care delivery could be $280- $550B by 2028.
Hospitals currently conduct a staggering 3.6 billion imaging procedures each year, resulting in a massive amount of data, approximately fifty petabytes annually. This data encompasses various elements such as clinical notes, lab tests, medical images, sensor readings, genomics, and operational data. Unfortunately, a significant portion of this data, around 97 percent, remains untapped and unused. However, with the advancement of digital platforms that can effectively aggregate and leverage this data, there is immense potential to revolutionize the quality of medical care by unlocking valuable insights and transforming healthcare systems on a larger scale [9].
The huge potential of digital technology is reflected in every aspect of healthcare. Some of these are
Prevention of diseases:
We are increasingly able to focus on preventing disease in the first place as our understanding of the human body and the cause of diseases grows. This will involve a combination of lifestyle changes, such as diet and exercise, and new medical treatments.
The personalization of care:
Healthcare is becoming increasingly personalized, as doctors can tailor treatments to each patient's individual needs. This will be made possible by advances in genetics, artificial intelligence, and other technologies.
The rise of patient empowerment:
Patients are becoming more curious about their own healthcare. They are demanding more information and control over their care. The host of digital and material technologies that are reshaping the healthcare domain is genomics, telemedicine, portable devices, 3D printing, AI in decision support, IoT, and robotics surgery. There are many examples where AI, medical devices, informatics, and IoT are used effectively. The precision diagnostic/ digital healthcare that connects data, devices, patient information, and digital twin are such examples.
Integrated diagnostic /integrated care/precision diagnostics /value-based care
The future of healthcare with precision diagnostics is expected to be transformative, offering significant advancements in disease prevention, early detection, personalized treatment, and improved patient outcomes. Precision diagnostics refers to the use of advanced technologies and techniques to identify diseases and conditions with a high level of accuracy and specificity.
The need for precision diagnosis is greater than ever. The world is facing a growing epidemic of chronic diseases, such as cancer, heart disease, and diabetes. These diseases are often difficult to diagnose and treat, and they can lead to serious health problems or even death.
In a hypothetical scenario where lung cancer is suspected, the diagnostic process involves several steps. Initially, the patient's medical history, symptoms, and risk factors are assessed. Then, high-resolution imaging techniques like CT scans or MRIs are used to examine the lungs and identify abnormalities. If suspicious findings are detected, a tissue biopsy may be performed through minimally invasive procedures or surgery to collect samples for analysis. Molecular analysis, including genetic testing and biomarker analysis, is conducted on the tissue sample to determine specific mutations and biomarkers associated with lung cancer. The collected data is integrated and analyzed to form a comprehensive diagnosis, guiding treatment decisions tailored to the patient's condition.
If you take the example of Philips, Philips is a company that is working to advance precision diagnosis. There are four frontiers that Philips is focusing on to advance precision diagnosis:
Getting diagnostic studies first-time right with smart diagnostic systems. This means using technology to make sure that diagnostic studies are accurate and that patients receive the right care the first time.
Harnessing the power of data to personalize care. This means using data from a variety of sources, such as imaging, pathology, and genomics, to create a comprehensive picture of a patient's health.
Making diagnostics more accessible and affordable. This means developing diagnostic technologies that are affordable for patients and healthcare providers in all parts of the world.
Building a culture of collaboration. This means working with other healthcare organizations, researchers, and patients to advance precision diagnosis.
Challenges to implementing the precision diagnosis
However, it's important to note that the full realization of precision diagnostics in healthcare requires overcoming various challenges.
These challenges include
The complexity of data integration and interpretation
Ensuring equitable access to advanced diagnostics
Addressing ethical and privacy concerns related to genetic information
Need for robust regulatory frameworks to ensure safety and efficacy
Way forward
Precision diagnosis has the potential to revolutionize healthcare by improving patient outcomes and reducing costs. It also holds tremendous promise for transforming healthcare delivery, improving patient outcomes, and shaping a future where medicine is more precise, personalized, and effective.
Digital twin for healthcare
A digital twin refers to a virtual replica of a physical product, process, or system. It is a digital representation that closely mimics the characteristics and behavior of its physical counterpart. In the healthcare field, digital twins have found applications ranging from monitoring devices and predictive maintenance to complex models of human organs.
Importance of digital twin in healthcare
Digital twins offer numerous benefits in the healthcare sector. They facilitate cost optimization, improve operational efficiency, reduce downtime, and even forecast future demands. By leveraging digital twins, healthcare organizations can enhance home healthcare, enable remote diagnostics, accelerate precision medicine, expedite clinical trials, and provide superior patient care.
There are many potential benefits to using digital twin technology in healthcare. For example, digital twins can be used to:
• Improve diagnosis and treatment: By creating a virtual model of a patient's body, doctors can get a better understanding of their condition and make more informed decisions about treatment.
• Personalize medicine: Digital twins can be used to create personalized treatment plans that are tailored to each patient's individual needs.
• Reduce costs: Digital twins can be used to identify potential problems early on, preventing them from developing into costly complications.
• Improve patient outcomes: By providing doctors with a better understanding of their patient's conditions and by personalizing treatment plans, digital twins can help to improve patient outcomes.
Different types of digital twins for the healthcare system
Product twin: This type of digital twin replicates a physical product, such as medical imaging device. It enables predictive maintenance, minimizes system failures, and ensures the availability of critical equipment when needed. It also helps in accelerating the new product launch by minimizing the design iteration and improving the 1st time right.
A digital twin of a device consists of four components: a digital representation of the device, data from that device, AI, and data analytics to identify relevant patterns, and an interface for human interaction. This can help predict when a device needs maintenance and prevent system failures (Philips Healthcare).
Process twin: Process digital twins simulate and evaluate clinical procedures and healthcare systems. They help optimize healthcare delivery, identify areas for improvement, and enhance overall system performance. For instance, virtual twins of hospitals can be created to optimize operational strategies, staffing, and care models.
Siemens is using digital twins to improve the efficiency of its hospitals. The company has created digital twins of its hospitals in Dublin, Ireland. These digital twins are used to track the performance of the hospitals, identify potential problems, and improve the efficiency of care delivery.
Clinical twin: A digital twin of a patient integrates various measurements and data over time to create a virtual model of a body part or an entire physiological system. These personalized models can aid in diagnosis, treatment planning, and targeted therapy delivery.
Philips is using digital twins to improve the care of heart patients. The company has created a digital twin of the heart that can be used to simulate different scenarios and predict the risk of heart attacks.
The emergence of digital twin technology has opened new possibilities for revolutionizing healthcare. From optimizing patient care and streamlining processes to improving precision medicine and clinical outcomes, digital twins have the potential to reshape the healthcare landscape. By leveraging AI, ML, and advanced analytics.
The confluence of digital twin and integrated care
In the future, healthcare will see exciting outcomes through the use of digital twins and integrated care. Digital twins create virtual copies of patients, devices, and processes, helping doctors personalize treatments, improve diagnoses, and efficiency and save costs. Integrated care uses advanced techniques to accurately identify diseases, leading to better prevention, early detection, and personalized treatments. By combining digital twins and precision diagnosis, we can revolutionize healthcare, making it more precise, personalized, and effective. These technologies will bring positive changes, improving people's health and well-being in the years to come.
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