Statistics show that today we are battling a global shortage of doctors. According to the World Health Organization, there is a global shortfall of over 4.3 million doctors and nursing staff across the world. This shortage of doctors might not be impacting the U.S that much but the country is plagued by increasing healthcare costs that limit the time that a patient can spend with a doctor. In countries such as India that has a huge rural population and some parts of Africa for example, there is a shortage of doctors and access to good medical services. Doctors too are feeling the brunt of these rising pressures and are now looking at avenues to improve their efficiencies to improve patient outcomes and have been open to technology adoption to facilitate the same.
One technology that is gaining prominence in the healthcare sector is Machine Learning and Artificial Intelligence. A study by Frost & Sullivan highlights that the AI market in healthcare is expected to grow to $6.6 billion by 2021 from USD 7,988.8 million in 2016. According to Accenture, the use of AI in healthcare can save the industry over $150 billion over the next decade. So what is it that makes AI and Machine Learning, computing systems that can complete designed tasks independently of human intervention using algorithms that can self-learn, so beneficial to the healthcare sector?
Machine Learning is not just beating up board game experts but is being used extensively to recognize disease symptoms in patients. Machine Learning and AI applications can scan through thousands of documents much faster than humans can. These applications are therefore perfect for running diagnostics for medical cases that demand record and diagnostic comparisons. Analysis of tests, X-Rays, CT scans, etc. can be done faster and more efficiently by AI and machine learning systems. For example, IBM’s supercomputer Watson established its credibility as Dr. Watson when it diagnosed the exact condition that was plaguing a leukemia patient by cross-referencing patient information with over 20 million oncology records. Watson not only came up with the right diagnosis but also did the same in a matter of minutes using the power of the computing system.
Doctors across the globe are leaning in heavily towards preventive medicine. AI and machine learning systems have been of great help in this area as the computing power of these systems can help assess which patients will need medical intervention when a patient or patients are likely to fall sick, common denominators causing recurring ailments in patients etc. Using these diagnostics, doctors can take a more preventive approach to medicine for better patient health and reduce hospital readmissions.
Good pre and post-operative care are essential to reduce the rate of readmissions in hospitals. But how can doctors ensure that their patients are taking the necessary precautions to ensure the same? AI systems come of great help here. AI applications can help in providing timely alerts pre and post operation regarding the care the patient should take. They can help in optimizing the doctor’s time and schedule by ensuring that the most pressing and urgent messages reach them first. Along with this, AI and machine learning applications also have the capability to assess the mental state of the patient and hence can be immensely helpful in mental health cases. Using this information, doctors can assess who will need medical intervention and also determine the timeframe for the same.
Robots in the OT
No, the robots are not replacing the doctors in the operating room but are being of immense assistance there. Repetitive and time-consuming tasks of the operating room such as making sutures can now be done with the help of robotic automation that helps in reducing surgery time. Along with this, you have the cognitive robots who are taking pre-operative medical information and integrating it with real-time operating metrics to increase the surgeon’s instrument precision. This also helps in improving patient safety as the more tedious and routine parts of the surgery are replaced with robots running on the power of AI and Machine Learning.
Telemedicine, Online Consultations and Virtual Nurses
Voice-powered AI applications are here to answer patients queries regarding their health. These applications help in better health management, chronic disease management, and long-term maintenance, and also assess patients for potential health risks. These AI applications called virtual nursing assistants are expected to become an industry staple and help the healthcare industry save more than $20 billion. These intelligent AI applications help in reducing the time taken during physician interactions as they provide answers to most of the patient queries. The time spent with the doctor thus becomes more productive and can be leveraged more effectively.
Machine learning and AI are also helping doctors in making telemedicine more efficient by aiding better diagnosis, enabling remote monitoring using machine learning, detecting rare genetic diseases, and solving logistical challenges by using predictive analytics.
AI and machine learning are here to act as the efficient doctor’s assistants. The aim of AI and machine learning, unlike what is written, is not to replace the doctors but to help them increase their efficiencies and replace the burden of mundane tasks from their shoulders so that they can focus on the human elements of patient care.