A digital twin facilitates data-driven and scenario-based decision-making that encourages all stakeholders to work together to find solutions for common problems. Frost & Sullivan has identified several familiar corporations that continue to make strides in these areas.
Advances in artificial intelligence (AI) and the related deep learning, predictive analytics and digital twin concepts continue to disrupt the continuum of care. Frost & Sullivan has built an entire business unit devoted to monitoring the exciting pace of change: analysts and consultants on the company’s aptly named global transformative health research team investigate the implications of each new development on patients, providers and ancillary industries.
Deep learning, in which machines are trained to “think” like the human brain, can reduce turnaround time during the drug discovery process through predictive modeling; improve medical imaging and diagnosis; and support better clinical decisions through electronic health record (EHR) interoperability and analytics.
Predictive analytics leverages historical health care data, machine learning and AI to support a diagnosis, design a personalized care regimen, manage chronic diseases, or reinforce large-scale population health initiatives. Patients benefit from medication adherence and behavior modification techniques that improve outcomes, and hospitals realize reductions in adverse events, readmissions, infections and mortality rates.
A digital twin is a virtual environment that leverages the Internet of Things, big data and machine learning. In health care, it facilitates data-driven and scenario-based decision-making that encourages all stakeholders to work together to find solutions for common problems. Hospitals can use a digital twin to improve inventory management and safety, reduce wait times and average length of stay, and minimize billed hours.
Frost & Sullivan has identified several familiar corporations that continue to make strides in these areas.
IBM (Armonk, N.Y.)
With its AI platform Watson, IBM enables the integration of AI into drug discovery, social program management, genomics and personalized care delivery using individualized care plans and automated workflows. The company has several partnerships in this regard with leading pharmaceutical companies, research institutions, universities, and hospitals.
IBM’s partnership with Pfizer for developing a cloud-based cognitive tool using machine learning, natural language processing and cognitive reasoning technologies is making great strides in immune-oncology and neurological disease research. Watson helps Pfizer stratify patients to develop new drug targets and combination therapies for personalized care delivery. Project BlueSky, a result of this partnership, uses sensors and analytics to continuously monitor and collect clinical data from patients with Parkinson’s disease. The data will provide a real-time estimate of a patient’s motor function and is much more efficient than the traditional episodic assessment that requires patients to visit a hospital during clinical trials. Overall, an AI-enabled drug discovery process will speed up the clinical trial process because phase 3 trials easily can be scaled up to several hundred patients. IBM’s expertise will help to identify genetic reasons for diseases and use that information to design pathways for personalized therapy.
IBM Watson Health continues to develop capabilities in cloud-based health care intelligence, medical imaging, population health and genomics. IBM has made several acquisitions, including Truven Analytics, Phytel, Explorys and Merge Healthcare, to strengthen its value-based care portfolio.
Alphabet and its Google, DeepMind and Verily Life Sciences subsidiaries (Mountain View, Calif.)
Alphabet has a high-level goal of democratizing medical information, which is currently the biggest challenge in health care, by actively investing in the development of technology for actionable use of health care data and expanding its capabilities in medical imaging. The focus is on predictive software that uses medical record data (e.g., patient demographics, previous diagnoses and procedures, lab results and vital signs) to predict outcomes including patient mortality. A most promising development is AI software developed by Verily and Google that can predict the risk of cardiovascular disease. It analyzes retinal fundus images to identify risk factors such as smoking, blood pressure and age and assess the likelihood of a heart attack or other cardiac event. The predictive algorithm that generates attention maps is less invasive and more cost-effective than current tests, such as the coronary calcium CT scan, pushing new frontiers in preventative care.
While much of the company’s work in this area today is explorative research, it has a clear, strategic roadmap for bringing AI into patient care. By developing capabilities to extend AI into disease detection, data infrastructure, and potentially insurance, Frost & Sullivan believes that Alphabet and its subsidiaries are poised to disrupt the entire health care industry.
GE Healthcare (Little Chalfont, United Kingdom)
GE Healthcare is honing its capabilities in applied intelligence using a predictive analytics platform for transforming large, disparate patient data into actionable and intuitive intelligence. The aim is to help customers manage, coordinate and benchmark patient care at a population level.
GE is a front-runner in digital twin technology, with which it models virtual hospital settings using its health care-specific simulation platform. GE is collaborating with Johns Hopkins Medicine for an advanced Capacity Command Center that applies simulation and analytics for better decision-making in The Johns Hopkins Hospital in Baltimore. By building digital twins of patient pathways, the hospital is able to predict patient activity and plan capacity according to demand. The hospital has been able to demonstrate significant improvements in patient safety, experience and volume, and in the movement of patients in and out of the hospital—including their access to emergency and life-saving treatments.
GE Healthcare also is augmenting its capabilities in imaging through its portfolio of high-end radiology ultrasound systems that integrate AI technology, cloud connectivity and advanced algorithms, and through partnerships with Intel and Nvidia for developing its deep learning platform to apply AI to medical imaging.
The Road Ahead: AI in an Era of Personalized Care
Frost & Sullivan has determined that the market for AI and associated technologies will become more mainstream with the move toward personalized care, and estimates that it will be worth $6.6 billion by 2021. AI has the potential to reduce health care costs by 50% and improve patient outcomes by more than 50% by automating processes, improving workflows and increasing accuracy. Imaging and diagnostics will be the major market segments disrupted by AI: radiologists can expect a 10 to 15% gain in productivity by leveraging AI platforms with deep learning capabilities.
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