AI In Healthcare: From Sci-Fi To Reality
John McCarthy, the father of artificial intelligence (AI), described AI as the science and engineering of making intelligent machines, especially intelligent computer programs. AI is continuously improving accuracy in medical image analysis with help from digital image processing, pattern recognition, and machine learning platforms. Wearable health technology has already taken a new leap with the fourth-generation iWatch announcing the capability to produce medical grade ECG and alert EMS if it senses medical emergencies.
By 2020, chronic conditions like diabetes and maybe even certain cancers are expected to be diagnosed in minutes using cognitive systems that will provide and analyze real-time 3D images capable of identifying typical pathological characteristics in the scans. When it comes to individual or mass healthcare, the idea is to amalgamate accumulated medical knowledge with advanced computer technology, hoping for a kind of clinical intelligence being demonstrated by machines and software that mimics human brain like analytical capability.
For this to happen, AI systems are essentially needed to be fed clinically relevant, quality information sourced from data stored in electronic health records including images, histopathology, and microbiology. This medical knowledge then would be thoroughly analyzed and memorized by these systems. AI can then offer improved patient outcomes by assisting healthcare practitioners by quickly going through the database and providing real-time, accurate referral points, or probable clinical answers.
Global trends
According to an Accenture report published in December 2017, key clinical healthcare AI apps can create USD 150 billion in annual savings for the US healthcare economy by 2026. Growth in the AI health market is expected to reach USD 6.6 billion by 2021 – that is a compound annual growth rate of 40 percent – says the report. Forbes recently reported that by 2025, AI systems are expected to be implemented in 90 percent of the US and 60 percent of the global hospitals and insurance companies. Technological innovation is proving to be beneficial in diagnosis procedure, monitoring of chronic conditions, assisting in robotic surgery, and drug discovery. Early this year, the US Food and Drug Administration (FDA) had approved clinical decision support software that uses AI algorithms to help neurovascular specialists gauge brain deterioration.
They recently gave a green signal to market IDx-DR, a medical device to detect diabetic retinopathy. Beta Bionics, iLet device, an infusion pump that mimics functions of pancreas, can deliver the required quantity of insulin with AI to calculate and decide the dose delivery, based on the body weight and data with the help of a glucose monitor is being tested in the United States of America. The product is expected to reach markets by 2020. Leading drug makers in the world like Pfizer, GSK, and Novartis have projects, in partnership with AI specialized companies and related drug discovery start-ups, to develop new drugs.
The curious case of Indian healthcare
According to the Indian Journal of Public Health (2017 edition), India had 4.8 practicing doctors per 10,000 population. The minimum doctor to patient ratio recommended by the World Health Organization (WHO) is 1:1000. We have only 10,000 radiologists and 130 crore people to scan. The country faces a dual burden of lifestyle as well as risk of chronic and infectious diseases. It is becoming the diabetic capital of the world with about 6 percent of the population diagnosed with the condition. A quarter of the population has high blood pressure or hypertension. Not just this, many people especially those in the age group of 25–40 are also being diagnosed with cardiovascular diseases.
Only 30 percent of healthcare resources are directed at the 70 percent nonurban population of India. AI applications like algorithms that analyze chest X-rays and other radiology images, read ECGs and spot abnormal patterns, automatically scan pathology slides, and even assess fundus images for signs of retinopathy can help decentralize medical care and also can be more effective in monitoring progression of disease apart from screening and diagnosis.
In a country with more than 1 billion people, many families are now equipped with smartphones. Applications for medication adherence monitoring (tuberculosis – one of India’s most significant public health issues), low-cost vital parameter monitors for use in the primary healthcare setting which should be integrated into electronic records, and telemedicine programs that provide clinical expertise to areas without doctors, have the potential to percolate healthcare delivery to the doorsteps of every villager.
Certain states in India particularly in association with certain branches of medicine have shown ways of innovation and adaptation. Ophthalmology is a clear leader on these counts, with a relatively broad range of new age technologies such as high-quality imaging of both retina and cornea (using smartphone-coupled devices), AI for the screening of diabetic retinopathy, being developed and tested, and then brought into clinical use. This has largely been due to private-sector efforts namely by a set of well-organized large eye care centers from South India, which invested in data collection and piloted the new technologies.
The government aims to increase the healthcare spending to 2.5 percent of the gross domestic product (GDP) by the end of its 12th five-year plan, and to 3 percent by 2022. The healthcare market in the country is poised to grow from USD 100 billion in 2016 to USD 280 billion in 2020. According to a report by CIS India published earlier this year, AI could help add USD 957 billion to the Indian economy by 2035. Of the USD 5.5 billion that was raised by global digital healthcare companies in the July–September 2017 quarter, at least 16 Indian healthcare IT companies received funding, the report said.
This is going to give a unique opportunity to digital innovation. The Microsoft Intelligent Network for Eyecare (MINE) is a project where the company is working with the government of Telangana for its Rashtriya Bal Swasthya Karyakram. The state government has adopted the MINE, an AI platform to reduce avoidable blindness. Microsoft also has a partnership with Apollo Hospitals to use AI for early detection of cardiac diseases. Healthi is a four-year-old Bengaluru-based digital health and wellness startup. The company uses predictive analytics, personalization algorithms, and machine learning to deliver personalized health suggestions. Another daily life example is the new online appointment-booking system at one of the country’s largest public hospitals in New Delhi. It will spare patients long waits and will help in monitoring patient flow and revisits. The data generated can potentially be used to identify the diseases that are encountered more frequently, their varied presentation, and areas of shortfall.
Challenges
For AI to be used at any scale, digitalization is a pre-requisite. In most Indian health centers, medical records are in paper form and radiology still uses films. Digitalizing of this content is going to be a herculean effort.
Technology that is intended for mass usage, definitely needs to be cost-effective. The other common spanner is – scalability to meet India’s health challenges. In India, a significant percentage of healthcare services are provided by the private sector and thus paid for out-of-pocket by the suffering population. This means that to be broadly adopted, technology needs to be either subsidized or incentivized by the government.
Government spending on healthcare in most scenarios is never enough, leading to public health programs getting funded from outside the country. A concerning trend for AI is India being seen as a data source for radiology and ophthalmology images. Today we live in a scenario of Lax privacy and opaque data protection and ownership laws. The data sharing itself is an obvious concern but lack of transparency and regulation around it are likely to create challenging issues. India needs regulation which does not stifle innovation while addressing concerns regarding sharing of data without infringing on privacy matters.
Conclusion
Till recently most technological innovations were aimed at the urban, spending consumer. Digitalization and AI in healthcare have gained traction, mostly in the form of online health service, telemedicine, home delivery of pharmaceuticals, and bundles of health/fitness apps.
The urgent need for technology to bridge resource gaps in India, and the potential of AI to offer affordable solutions at a scale unimaginable till now, means that India is poised to realize the benefits of these technologies on health outcomes. AI has potential to leapfrog other technologies not because of it being innovative but just because of the fact that smart phones have already brought digitalization to so many otherwise empty palms in India.
