The Indian health-tech market is expected to grow at 39% CAGR to reach $50 billion by 2033 from $2 billion now, according to an RBSA Advisor report.
Telemedicine has seen huge growth since the pandemic breakout. Startups such as myUpchar, Practo, Tattvan, Lybrate and mFine have cashed in on the demand and hospitals such as Akash, Apollo Hospitals, Narayana Hrudayalaya started teleconsultations to avoid crowding at hospitals.
According to a McKinsey Digital India 2019 report, telemedicine in India can reduce in-person outpatient consultation load by half and cost about 30% less for patients. In the US, artificial intelligence applications are expected to save $150 billion in healthcare costs annually by 2026.
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Futuristic telemedicine technology
The objective of telemedicine is to improve healthcare access, reduce delays and save logistics costs. Of late, telemedicine has turned to artificial intelligence to achieve these objectives.
Patient monitoring through video consultations is one of the first and most common applications of telemedicine. This has allowed faster and safer ways of consultations in both urban and rural India.
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Interestingly, rural India had teleconsultations (hub and spoke model) even before the pandemic. Hospitals set up mobile clinics in villages and connect doctors through video or audio. However, telemedicIne today is not just about video consultations. For instance, ultrasound is done with a probe attached to a smartphone in the US.
Telepresence robots
Telepresence robots can be remote-controlled using a software interface, allowing doctors to examine and interact with patients from anywhere. The concept combines AI and computer vision for navigation and obstacle detection.
DrRho, a medical telepresence robot developed by Vyas Labs, provides a robotic base with human-environment manoeuvrability, robotic manipulators, an electronic stethoscope, blood pressure machine and thermometer, ECG and pulse oximeters. It also provides an intuitive vision system to the doctors, meaning the robot’s eyes turn as the doctor moves his head. The robot also carries a projector in cases of surgery or collaborative examination.
Recently, researchers of the Integrated Systems Engineering Group of the University of Malaga (UMA) in Spain have developed a telepresence robot to enable quarantined persons to get on video calls.
Two students from VR Siddartha Engineering College in India built a virtual telepresence robot:
- Developed a robot with an onboard camera and Wi-Fi capabilities that capture videos and allows users to monitor the situation on their smartphones, internet browsers, or Virtual Reality headsets
- Used accelerometers and gyroscopes, i.e., sensors that determine an object’s position and orientation to ensure the robot’s onboard camera moves according to the user’s head movements
- Data collected in the user’s smartphone is used to track head movements
- Data transferred to a Rasberry Pi device and used to control the movements of the robot’s camera
- Used Arduino for the robot’s back and forth, left and right movements.
- Later substituted Rasberry Pi and Arduino with MyRIO, a more expensive device with higher processing capability. The portable device combines the capabilities of Rasberry Pi and Arduino and serves both as a data processor and a controller.
Electronic health records
Electronic Health Records (EHR) systems created using big data analytics and neural networks have pushed telemedicine in India.
A study by the American College of Physicians showed doctors spend 50 percent of their time on patient records. Today, Electronic Health Records (EHR) software is integrated with machine learning capabilities. This has enabled faster sending of prescriptions and other information directly to the patient. Hospitals and clinics use proprietary machine learning algorithms on top of the data to systematically categorise health data.
Many B2B health tech platforms offer EMR that can be integrated across a network of hospitals or clinics. This way, the patient can walk into any hospital and access records.
Cloud computing
Many medical professionals use cloud computing to store, process and transmit health data. Cloud computing has also been successful in merging traditional healthcare infrastructure systems with new technologies like IoT & wearables. For example, Microsoft Band 2, equipped with BP sensors, can accelerate data retrieval and transactional processing capacity.
Today, there is an increased demand for startups offering cloud solutions. For instance, Bengaluru-based Alkenist uses AI solutions to detect lung issues in COVID positive patients, where the cloud-based software analyses chest X-ray and CT-scan images. This helps doctors quickly decide on the next course of treatment. Mumbai based Qure.ai has built an AI-powered solution on AWS to identify abnormalities in chest X-rays.
Cloud technology provides scalability and can be deployed anywhere effortlessly.
