AI In Telemedicine: Reimagining Indian Healthcare Future
With the onset of the Covid-19 pandemic, the adoption of digital technologies in the healthcare sector has spiked with many providers pivoting to virtual care. Accenture reports that while only 7 per cent of people used virtual consultations in 2020, the number increased to 32 per cent in 2021. As technological advancements continue on a rapid basis, perhaps it comes as no surprise that healthcare providers are moving towards more digital care options to enhance treatment and patient experience.
AI (artificial intelligence) in telemedicine is augmenting healthcare delivery by allowing doctors to make real-time, data-rich decisions creating better health outcomes and a better patient journey. According to research by MIT, 75 per cent of healthcare facilities that utilise AI, claimed that it enhanced their capacity to treat diseases, and 4 in 5 said it assisted them to avoid job burnout. With the rising burden of non-communicable diseases and the ongoing pandemic, the increasing use of telemedicine services along with AI-powered capabilities is expected to open the doors to further evolution in healthcare.
AI transforming the telemedicine landscape
As per the e-health market opportunity report of 2021, telemedicine will be the biggest contributor to the e-health market of India and is expected to reach $5.4 billion by 2025. The latest telehealth innovations along with AI applications can be used to support, supplement and develop new digital healthcare models that can lead to the evolution of overall healthcare. Here’s how AI’s implementation in telemedicine can bring a new paradigm to healthcare as well as address existing challenges:
Enhance clinical efficiency
Gathering data passively through AI tools and remote patient monitoring (RPM) sensors allow clinicians to concentrate on diagnosing, treating and educating patients that can enhance the efficiency and productivity of care provided. As responsibilities shift from manual processes to AI-powered technology and automation, it can bring good end results for both providers and patients alike. AI-powered RPM can allow patients to stick to their care plans all the while returning necessary information to providers. This allows medical staff to customise the care plan of a patient as per their needs.
Support care through robotics
AI-enabled robots in healthcare can be a big boon for RPM as they can navigate to hospital or exam rooms, allowing doctors to interact with patients from a different location. Nowadays, robots are also being built to accompany doctors while they make rounds. The robot can share live feeds and information with remote specialists who can contribute to on-screen consultation. This can be especially useful in rural healthcare facilities where specialists and physicians can check in from a distant location.
Telesurgery/remote surgery
Remote surgery or telesurgery happens to be an emerging tool that makes use of both wireless networking and robotic technology to connect surgeons and patients at different locations. The first telesurgery also known as the Lindbergh operation was carried out in 2001 where surgeons remotely removed the gallbladder of a patient by using a remote-controlled robotic system. Since then, further advancements has been made to enhance remote surgical procedures with higher efficiency. Robotic-technology assisted surgery can not only expedite treatment but even ensure proper care to remote areas or underserved populations. The tele-robotic model is capable of increasing the volume of patients a doctor can treat, allowing patients to stay near to their homes while undergoing treatment, and also reducing mortality and morbidity by giving fast access to care for chronic acute conditions.
Give structure to unstructured data
Studies have revealed that almost 80 per cent of the data gathered by healthcare organisations is conversational or unstructured which includes physician’s notes, radiology images or social media posts as well. AI has the capability to manage the huge volumes of unstructured data and provide it to intelligent systems to improve the reliability and accuracy of their learnings. By turning unstructured data into structured data, AI can transform it to actionable information or insights for healthcare providers to utilise the same at the point of care. It can also lay the foundation to a continuous process of learning.
Virtual nursing assistants
AI-enabled virtual assistants provide customised experience to patients. Through this, patients can get to know their illness depending on the symptoms, keep track of their health status, make doctor appointments, etc. Also, the virtual assistant is available round the clock to the patients which indicates that patients can ask questions and get answers in real-time. This method can be a boon for patients as it increases patient engagement and improves the self-management skill of patients to prevent chronic diseases from getting worse.
Aid in diagnosis
The application of AI in telemedicine is making it easier for doctors to screen, analyse and diagnose various conditions remotely. For instance, instead of a doctor relying on 2 or 3 pieces of a patient’s medical information, AI can search through thousands of datasets for different patients with similar illness profiles to produce algorithmic patterns that can suggest the next possible steps for treatment to the doctor. The doctor can then leverage this info to effectively treat illnesses. The application of artificial intelligence in remote care can save a considerable amount of time and resources for both doctors and patients. Predictive analytics using AI can also enable patients to discover specialists quicker. For example, AI can direct inquiries to a specialist depending on the patient’s symptoms, instead of sending them right away to the first doctor available.
Help in elderly care
Telemedicine applications are usually developed with the objective of helping patients in managing their medical issues, fitness goals, insurance claims and physician’s visits more efficiently. Apart from these, AI-based assistive robots in telemedicine are quickly becoming a reality, helping individuals, especially the elderly with activities such as walking and moving around in the home, timely delivery of medicines, and notifying healthcare authorities in the case of an emergency. Such robots can perform the duties assigned to them and can comprehend the surroundings, the house interior settings and the patient’s movement and behavioural patterns, thanks to AI capabilities. Thus, it may learn to better help the patient and act as his/her caregiver.
Convenience in remote patient monitoring
RPM or remote patient monitoring is becoming one of the most useful tools for the management of chronic diseases. RPM is the collection and delivery of a patient's health data to healthcare providers through connected devices outside a conventional care setting. When combined with AI, RPM can enable proactive care as well as anticipate adverse events without the need for consistent visits. For instance, an elderly patient with COPD may have faced disruptions in regular, in-person appointments due to the pandemic. This may result in a reluctance to frequently connect with the primary care physician remotely. Thus, the patient’s self-management practices may get affected adversely during this period. However, with the combination of RPM and AI, it would be easy for a care team to identify the patient’s increase in risk and precisely anticipate potential complications. With proper insight and specific evidence supported by AI, providers can get an idea of a patient’s condition and initiate preventive measures. This can also enhance patient engagement, significantly reduce costs for the patient and improve long-term health.
There is no doubt that AI in telemedicine promises a lot to offer, replacing existing paradigms. However, its success depends on how fast the healthcare industry adopts a comprehensive digital platform of various service offerings to produce a circle of security and trust with patients, doctors, nurses, vendors and the other participants in the ecosystem. It will not only help in reducing expenses, providing better healthcare and improving the work environment with fewer wait times but make healthcare accessible to all 24 hours a day, 7 days a week.
