Current AI healthcare trends aim to improve patient outcomes, align the interests of healthcare industry investors and reduce the costs of medical services for patients. Socially assistive robots are already being used all across the world to improve consumers' everyday lives. There are support robots, robots that diagnose and treat people in-home, workplace AIs, clinical AIs and even robots that administer cognitive behavioral therapy. While there is quite a bit of variance in the products currently on the market, there are four trends shaping the future of AI in healthcare.
The Patient-Centered Approach
Upon receiving their license to practice, physicians promise under oath to put patients first, among other tenets. Yet, with an increasing need for medical services, rising costs and limited medical resources, patient-centric care has taken a back seat. Additionally, the medical environment is changing. As more and more patients suffer from chronic conditions and illnesses, many physicians are concerned that they are ill-equipped to properly care for these patients.
This is why researchers are developing AI that aids in the patient-centered approach.
The democratization of access to electronic health records (EHR) and smartphone apps for at-home health solutions are changing the landscape of healthcare. From apps that assess your risk for skin cancer to new technology for accessing health records at home, patient-centric AIs are making it easier for people to receive high-quality care. The public is more willing than ever to participate in the healthcare cycle, and artificial intelligence is driving that trend forward.
Data-Driven Medicine
Modern medicine is driven by science, and science is driven by data. Medical care is likely to improve if a patient can readily access their own medical records. According to research compiled by Datavant, over 4 trillion gigabytes of healthcare data is generated annually, and this is projected to double every two years. Experts say this data is also completely unstructured, making it difficult to navigate and keep current. Enter artificial intelligence for healthcare data mining.
Using electronic health records from patients across the country, new AI technology helps to compile data for clinical research and reviews. There are programs for identifying efficacious treatments based on patient evidence. Data is just as essential for a highly responsive AI as it is for well-informed medical decisions. That's just one of the reasons these two industries pair so well together.
Medical Imaging
The ability to take images of the human anatomy has transformed the healthcare industry. Not only can doctors screen patients for cancer, but they can also use imaging technology to make new discoveries about the human brain. But these scans are expensive: An MRI or fMRI can cost a patient up to $4,000, and without insurance, an X-ray can cost upward of $1,000.
It's no wonder, then, that a lot of focus has been put on developing cheaper AI imaging. For example Google DeepMind’s medical image-assistive AI can identify 50 sight-threatening eye diseases. Other AIs can identify markers of potential strokes, spot lung and liver lesions, and screen children for autism with an iOS app — and there is even an AI that can detect tuberculosis. I believe there are no limits to the power of AI medical imaging, especially when you can use a simple and low-cost app on your phone to do it.
Improving Healthcare Communication
According to a study by Johns Hopkins almost a quarter million Americans die every year because of preventable medical errors. Medical errors are the third leading cause of death in Americans, following heart disease and cancer, and 80% of these cases occur because of miscommunication during patient care transfer. Yet communication among healthcare staff isn't the only problem: The patient-doctor relationship is growing strained these days, and doctors are looking to improve it.
AI research and development is answering the call for better communication in healthcare.
Already on the market, there are apps that allow patients to chat with doctors and schedule appointments from home. New technology helps physicians compare their prescribing behaviors to peers who are treating the same condition. Improving patient-physician and physician-physician interactions is vital for the continued growth and success of the medical industry. That's why big names like Google are scrambling to get in on healthcare AI.
The Future Of AI In Healthcare
Despite so much growth of artificial intelligence in healthcare, I believe there are some challenges AI proponents will need to address in the coming years. Finding good technical and marketing teams to handle the development of healthcare AI will be integral to this evolution. These teams will need to obtain large quantities of data for AIs to learn from and also make it a point to optimize the imaging and processing systems to ensure the validity of these AIs. With this change, there will not only be the need for uniform standards for the use of AI in healthcare, but also a steady supply with this increased demand. Data from Accenture (registration required) estimates AI in healthcare will be a $6.6 billion market by 2021. AI startups have raised $4.3 billion across 576 deals in the last six years, and healthcare providers are projected to save almost $150 billion by 2026 with the help of AIs that can prevent medication dosing errors. The future of AI healthcare technologies is looking bright.
