What are the benefits and how are edge and AI driving better outcomes?
The COVID-19 pandemic has exposed the healthcare industry across the Asia-Pacific region, which is continuing to stretch to breaking point across the board. The expected growth trajectory will reach a spend of $22.5 billion by 2025. Drivers of this anticipated growth include edge computing and Artificial Intelligence (AI).
These technologies have tremendous use cases and value. They have the potential to make the delivery of services more physically accessible and overall, more efficient for all. Edge computing directs data, analytics and processing power where it is most critical – clinics, hospitals, laboratories, operating rooms suppliers and into patients/peoples homes. Edge computing and machine learning tools can fact-check data and produce relevant analytics in real time, transforming the way the healthcare industry operates at a macro-level.
By processing data locally on the edge, healthcare organisations can minimise the constraints of traditional on-premises infrastructure. Such devices are already being utilised to deliver care to remote areas where connectivity may be sparse, creating more seamless delivery of care, increase accuracy and speed of diagnosis and manage the supply chain. It’s all about greater delivery of healthcare services to drive faster patient outcomes.
Increased adoption of smartphones, wearables and electronic medical records have seen healthcare organisations in this region as the most “pro-cloud” of any vertical industry, tipped to be the fastest-growing regional market for digitisation between now and 2028. Here’s why edge computing is the future for the region.
A solution to network latency
The ability to process data locally on the edge addresses roadblocks such as limited data transmission through on-premises infrastructure, slow speeds, low bandwidth and cloud storage. While this may help reduce costs, and improve speed of delivery, storing this information locally offers additional benefits in the form of privacy and security.
For example, through AI and edge computing technology, wearable health monitors and fitness trackers collect and locally analyse data such as pulse rate, blood-oxygen levels and sleep patterns. Doctors can then use this data to evaluate patients on the spot. It also allows for historical data to also be analysed for underlying health trends or issues in a particular patient.
Using edge devices that are detached from large healthcare networks makes it much more problematic for cyber criminals to access personal data. Through edge computing – especially when employed via a hybrid and multi-cloud model – healthcare providers can ensure they are giving the right services, to the right people, at the right time, without having to utilise offshore data centres – all while minimising downtime.
Innovation through data-driven healthcare
Healthcare data volumes are growing at an exponential rate as providers seek advanced centralised technology-based systems that provide a 360-degree view. AI allows healthcare professionals to analyse a patient’s data and respond in real time and this process is being increasingly performed by machines at the edge. AI has now become so intrinsic across the healthcare lifecycle that use cases of edge computing solutions can be seen in nearly every scenario of the medical lifecycle.
With the rise of the Internet of Healthcare Things (IoHT), AI is being used not only for remote services, but in ambulances, hospitals and even our homes. Emergency service professionals within vehicles can now communicate with doctors in real time. Within hospitals, edge computing and AI are enabling faster, more accurate diagnoses and automating the delivery of medicine with individuals having healthcare treatments delivered to their home in minutes or online, significantly increasing the availability of care.
Telehealth has become much more popular during the pandemic, generating enormous volumes of data, consuming copious amounts of bandwidth and cloud storage. Employing edge technologies allows this data to be stored and processed locally to minimise chances of not only network latency, but also attempted cyberattacks to access a clients’ personal information.
Avoid threats by devaluing the data
Devaluing data is the end game. With a multi-layered approach that includes the digitisation of data, the overall cost of this information can be minimised, making it redundant should it fall in the hands of bad actors, organised crime and other cyber-threats.
Whilst it is vital that organisations protect their external perimeter from threats, securing Protected Health Information (PHI), patients’ Personally Identifiable Information (PII) and payment data is of equal importance. Research has found each cyberattack can cost organisations up to A$31.3 million in estimated economic losses, and over 50% are ransom-focused. An essential component of protecting against these attacks is devaluing the data that is transmitted, making it of limited or no use to hackers.
Healthcare providers should take advantage of the shift toward the edge and be proactive in making the investment in software, such as point-to-point encryption, that will help protect against ransomware and other threats.
Pushing the boundaries through edge computing
With the Asia-Pacific market for IoT medical devices expected to reach $95 billion by 2026, the healthcare industry is experiencing a paradigm shift in the way it structures, interacts, and manages the personal data of patients.
Looking forward, organisations must learn to adapt to shifting security environments that are increasingly at risk of exploitation. Security at the edge is now mission-critical to ensure that healthcare providers can continue to employ edge computing to better their ability to support the growth of the broader Asia-Pacific economy and cater to the ever-present need for better care, fast decision making and enhanced patient outcomes.