The Covid pandemic triggered a major digital transformation in the Indian healthcare industry over the past two years. Not only did it bring the inadequacies of the country’s healthcare system to the fore but also opened new possibilities for the digital intervention in healthcare, especially remote patient monitoring. The healthcare industry in India is projected to reach $372 billion by 2022, according to a recent report from Invest India. The hospital industry, which accounts for 80 per cent of the healthcare industry in India, is forecast to increase to $132.84 billion by FY22 from $61.79 billion in FY17 at a CAGR of 16-17 per cent.
IANS spoke to Girish Raghavan, VP, Software Engineering, GE Healthcare South Asia, on the emerging need for innovative technologies and diagnostic solutions in the fields of cardiology, oncology, genomics, and remote patient monitoring.
Excerpts from the interview below:
While the Covid pandemic exposed India’s fragile healthcare infrastructure, one silver lining was that it accelerated the digital transformation journeys of many industries, including healthcare. What were the key strategic pillars on which you built your digital strategy over the last two years?
The pandemic forced us to rethink healthcare delivery models. Before we knew it, virtual and remote patient monitoring systems became the global norms to drive healthcare outcomes.
The next important step was to orchestrate this transformation. This is where it became critical to transform healthcare systems into single data command centres featuring real-time decision support tools.
We introduced new technologies that helped clinicians diagnose earlier, better, and faster using devices that are leveraging artificial intelligence (AI). The idea was to ensure that healthcare providers can achieve a more precise diagnosis. We also saw increased adoption of virtual assistants during the pandemic.
The most important chapter in the digital transformation story is that of Data aggregation. The pandemic taught us the value of co-relating medical history with data analytics to join the dots.
The manifestation of diseases has changed. From a sore throat to gastritis, or a headache, the trigger to a more serious disease could be any. Therefore, it’s so important to integrate data for precision care, better patient outcomes and increasing access to healthcare.
How have you impacted the pace of digital innovation in the Indian healthcare landscape?
We understand and recognise the emergent need for innovative technologies and diagnostic solutions in the fields of cardiology, oncology, genomics, and remote patient monitoring. Over the years, we have collaborated with scientists, engineers, and innovators to develop deep tech integrative solutions that assimilate data from disparate sources, and apply advanced algorithms to generate clinical, operational, and financial insights.
When we launched GE Healthcare’s India Edison Accelerator, the objective was to nurture the start-up ecosystem and improve patient outcomes. We harness the brainpower of the start-up ecosystem to solve for some of the toughest healthcare challenges.
The programme has mentored three cohorts of 17 startups and nurtured a vibrant, synergistic ecosystem – leveraging GE’s tools and solutions to co-develop and deliver cutting-edge solutions.
In Cohort 3, we are working with six companies, helping them scale up their healthcare solutions. These companies will spend six months with healthcare industry experts from within and outside GE.
Collaborating with students and communities with hackathons like the GE Healthcare’s Precision Health Challenge 2022, we are encouraging students and hackathon enthusiasts to build the future of innovative healthcare.
Pushing the boundaries for precision care, we also launched the Healthcare Innovation Lab with/at IISc to help bring to market unique digital solutions, which can be integrated into our Edison platform and intelligent devices to solve some of the real healthcare issues that clinicians face.
The lab works with deep learning technology, artificial intelligence, and future-ready digital interfaces, powered by GE Healthcare to provide sophisticated diagnostic and medical image-reconstruction techniques.
Data is at the core of predictive health in precision medicine. How do you ensure that the quality of data used in your AI & ML models is optimal?
As part of GE’s Quality systems and processes, we have outlined a broad set of AI standards within which our data scientists operate. As part of this process, data diversity is assessed at every milestone of the product development process.
We have put together AI playbooks that guide the team at every step as they navigate this process. We also have subject matter experts in data science that are part of reviews, mentoring and signoffs as the teams go through the development process.
What stage is India at in terms of adoption of precision medicine? Do you see any challenges in creating awareness for its wide-spread adoption?
India in the early stages of Precision Medicine deployment. The first steps we are taking in healthcare are to bring access to the masses at affordable rates. The understanding of precision medicine must extend beyond its general definition because it includes everything from unique targeted medical products to diagnosing/treating patient-specific ailments, leveraging AI.
As we get deeper into the Digital Health Mission and build the data repositories, we will understand the profile and get to differential diagnosis, a step in Precision Dx. Consequently, as outcomes are recorded, we can use data evidence to define Precision Rx (Therapy). Clearly, there are research studies and trials that are in progress, but the translation is gradual.
What has cloud technology enabled you to do better?
What matters to us at GE Healthcare, was to move the digital world of machines to work in tandem with the logical world of software to better patient outcomes. In the larger scheme of things, we wanted to create solutions which are predictive, responsive, and connected. This is what AWS allowed us to do. AWS paced up the speed of Infrastructure scalability for both R&D and production. The team also ensured that compute, storage, database, and network services are readily available for integration and scalability. All this was done, while ensuring the highest level of security.