The emergence of next-generation technologies, including artificial intelligence (AI), augmented reality and internet of things (IoT), has significantly transformed the functioning of the healthcare sector in the past three years. The implementation of these solutions in the healthcare sector, often labelled as “healthtech”, is visible across divisions ranging from hospital administrative processes to cancer research, drug development and surgery. The primary aim is to boost efficiency, increase collaboration across systems, automate processes and improve patient experience.
In addition to private enterprises and healthcare start-ups that accelerated their digital transformation during and post the pandemic, the government too extended policy support through initiatives such as the National Digital Health Mission and a focus on digitising health records.
A look at the key technologies transforming the healthcare industry and the way forward….
AI, ML and NLP
AI is rapidly becoming an integral component of modern healthcare. The most common applications of the technology in a healthcare set-up are machine learning (ML) models and natural language processing (NLP). Organisations in this sector have accumulated vast amounts of data in the form of health records and images, population data, claims data and clinical trial data, which is practically impossible to analyse without AI technologies. ML algorithms and deep learning models are best suited to uncover useful patterns and insights from these complex data sets to support better business and clinical decision-making and improve operational workflows. Another use case of AI is precision medicine, which predicts the treatment procedure that would likely be the most successful, based on the patient’s medical records and treatment framework.
AI in healthcare that uses deep learning is also used for speech recognition in the form of NLP. For healthcare players, NLP capabilities can take the form of a virtual agent, using conversational AI to help connect health plan members with personalised answers at scale.
Some examples of AI implementation in the industry include IBM’s Watson for Health, which is enabling healthcare organisations to apply cognitive technology to access huge amounts of health data and power diagnosis. Watson can review and store far more medical information – every medical journal, symptom and case study of treatment and response around the world – exponentially faster than any human brain. Another application is DeepMind Health by Google, which is working in partnership with clinicians, researchers and patients to solve real-world healthcare problems. It combines ML and systems neuroscience to build powerful general-purpose learning algorithms into neural networks that mimic the human brain.
Robots are not new to the medical field, although their complexity and use cases have increased over time. They range from simple laboratory robots used for repetitive tasks, physical therapy and in the service of patients with chronic conditions, to more complex surgical robots that aid human surgeons. Motion control technologies have evolved and led to higher precision in surgical assistance by these robots. Some surgical robots may even be able to carry out certain surgeries themselves, while surgeons oversee procedures from a console. Meanwhile, robots with AI-enabled medicine identifier software also help in identifying, matching and distributing medicine to patients. With further advancements, robots will function more autonomously and eventually execute certain tasks entirely on their own. This will enable healthcare practitioners and workers to focus on providing direct patient care.
The internet of medical things (IoMT) is a sub-set of IoT technologies. It is a connected infrastructure of internetworked healthcare devices and applications. Akin to IoT, IoMT uses automation, sensors and machine-based intelligence to minimise human intervention in healthcare procedures. The technology connects patients, doctors and medical devices including hospital equipment, diagnostic gear and wearables. It can reduce unnecessary hospital visits and the burden on healthcare workers by transmitting information over a secure network. Furthermore, IoMT offers centralised control to the workforce over their facilities, thus providing more visibility into their environment.
Juniper Research forecasts that 7.4 million connected IoMT devices will be deployed globally by 2026, a total growth of 231 per cent over those in 2021, when 3.2 million devices were deployed. However, the real-time nature of the technology requires low latency and high bandwidth to ensure that transmission health data is not distorted or interrupted. This is where 5G and edge computing can play a critical role in enabling the wider deployment of IoMT.
Two well-known applications of the technology are ingestible and wearable sensors.
Ingestibles and wearables
Ingestible sensors, or simply ingestibles, are broadband-enabled devices that integrate a wireless sensor system into a non-invasive capsule and can be used for various tasks such as endoscopy, drug delivery applications and patient monitoring of the body’s pH, digestive processes and internal reaction to medications. These smart pills help physicians to find optimum dosage levels and thus truly personalise treatment. Capsule endoscopy through ingestible video cameras is also set to replace traditional endoscopies or colonoscopies.
In contrast, wearables are medical and healthcare devices or supportive accessories that can be worn by patients. Medical wearables use sensors, actuators, software and electronic patches attached to the body to monitor patients’ heart rates and other vital signs, identify anomalies and even treat health conditions. A recent advancement in this domain is a “tattoo-like” sensor that can be peeled off after use or may be absorbed by the body. These sensors collect data through skin contact and transmit information wirelessly to smartphones and remote diagnostic facilities.
Using smartphones, wearables and head-mounted displays, augmented reality (AR) and virtual reality (VR) technologies are driving new interactions between the real and virtual realms, to redefine the way healthcare services are delivered. Key innovative use cases are in the areas of surgical simulation as surgeons can study patients’ anatomy before going into surgery, high resolution imaging diagnostics to obtain 3D data visualisation, rehabilitation, and medical equipment maintenance. In addition, medical institutions are beginning to implement AR in their curriculum to simulate patients and surgical encounters for students during their practical training.
For example, healthcare practitioners at the Imperial College and St Mary’s Hospital in London have already begun using Microsoft’s HoloLens AR glasses for reconstructive surgery on patients with severe injuries. In terms of market growth, Goldman Sachs predicts that the use of AR and VR in the healthcare industry will reach $5.1 billion by 2025. In fact, market reports even suggest that healthcare tech is the second biggest marketplace for AR/ VR technologies after gaming.
Blockchain technology in the healthcare sector offers a user-centred way for patient data to be securely collected, verified and shared. The technology provides complete transparency and interoperability across diverse and highly fragmented healthcare systems. While it is transparent, it also anonymises and safeguards the sensitivity of medical records with complex and secure codes. One of the most popular applications of blockchain in healthcare is centred on electronic health record (EHR) interoperability and healthcare big data exchange.
Additionally, blockchain can ensure the authenticity of medical goods by tracing them at every stage of the supply chain. It can also enable companies to apply AI to predict demand better and optimise the supply of goods and medicines accordingly.
In the healthcare industry, cloud computing involves implementing remotely accessible servers to store, manage and process large volumes of data in a secured environment. Since the introduction of EHRs, cloud-based healthcare solutions are emerging as a means of storing and protecting patient records. The technology streamlines the process of patient care and makes it easier for healthcare professionals to collaboratively view or share a patient’s medical records. Cloud storage also enables significant cost savings in contrast to on-site storage, which requires huge upfront investments in hardware and IT infrastructure. With cloud computing, all the data that was previously inaccessible in filing cabinets can be accessed and analysed using available complex computer algorithms. This allows healthcare providers to detect and respond to public health threats at an early stage.
The way forward
The disruption caused by the Covid-19 pandemic left a permanent mark on the healthcare industry and highlighted the need for a medical revolution. Further, challenges of affordability, interoperability and regulations still remain in the healthcare sector. The industry has been, and still is, a major target of data breaches and cybersecurity threats. However, organisations in the sector must prioritise the implementation of innovative solutions to address the low doctor-patient ratio in India and ensure affordable quality healthcare for all. Latest technologies such as 5G, IoT and nano-sensors will open new opportunities in the field. Going forward, the next few years will see a digitally transformed healthcare ecosystem.