A transformation in Indian healthcare has begun with the help of deep tech, including artificial intelligence and machine learning, which is making medical facilities more accessible and affordable to even the hinterland. While citizens in some parts of the country are beginning to feel empowered and confident, healthcare services in India still have a long way to go before digital technologies can ensure inclusion at the bottom of the pyramid.
Integration of teleconsultation and sample data-based diagnoses into traditional healthcare certainly received an impetus during the pandemic. While multiple initiatives towards improving primary healthcare have been executed successfully in several remote parts of the country by a few technology-based start-ups and significant investment has been made in the use of artificial intelligence in drug development, the progress still eludes a large section of the Indian population.
Experts point out that greater partnership between the private and the public sector is required to replicate the learnings from the fintech revolution that UPI brought about in the country, a transformation that has touched people and organisations across strata and sectors.
A NASSCOM report released in July 2021 found that despite its scale and growth, the healthcare sector in India faces challenges across the value chain. The sector is struggling to balance the cost, quality and accessibility of healthcare services, the report said.
No wonder then, the need for urgent and greater adoption of deep tech by healthcare stakeholders is undeniable. This assumes further importance due to the large, medically underserved population and the traditionally low doctor-patient ratio given in the country.
“The focus of healthcare-related funding is more on the licensor company and less on healthcare companies”
The report also indicated that data and artificial intelligence in healthcare had the potential to add $25 Billion to $30 Billion to the country’s Gross Domestic Product by 2025 and would play a pivotal role in enhancing the quality of healthcare services, reducing costs and increasing accessibility.
Well begun, but half done
Empirical evidence shows that the transformation led by digital technologies has already begun in drug development in India. The country has also covered a lot of ground towards creating the infrastructure for improving primary healthcare by setting up Ayushman Bharat Health and Wellness Centres across India and linking it with the eSanjeevni telemedicine services.
While the government seeks to establish 150,000 such centres, according to the health ministry data, 117,440 such centres have already been made operational by March 2022. The initiative ensures the availability of primary healthcare as well as early diagnosis of diseases. The ministry data indicates that the eSanjeevani platform has set a record of sorts by offering close to 200,000 consultations in a day, and around 50 Million consultations since it was started in April 2020.
Experts, however, believe that the healthcare sector needs make effort towards using digital technologies for curative purposes as well. “A lot of investment is happening on the drug-discovery side and emerging technologies related to it; maybe partly on diagnostic but very less on the cure side,” Vijay Bhaskaran, Partner Consulting at Ernst and Young said.
“Hence, the focus of healthcare-related funding is more on the licensor company and less on healthcare companies… It will take a bit more time for deep tech to have a grass-root level impact where a person in a village can see their lives becoming better as a result of artificial intelligence being adopted in the healthcare sector.”
Artificial intelligence and ML-based algorithms can be used to differentiate patients into high and low-risk categories and prioritise care according to risk. Moreover, early detection could be a game changer in grave diseases such as cancer and heart ailments.
The joint managing director of a leading hospital chain said in an EY report published in 2020, “About 62% of cancer patients come to us in India in stages 2 and 3. The story is equally bad in cardiac – all angioplasties are 2-vessels, 3-vessels, 4-vessels, we should have found them when the first vessel was slightly blocked.”
“Artificial intelligence would act as the lever to move us from image analytics to disease pathways to digital twins”
“Data modelling and standards are the foundational building blocks, and bandwidth and connectivity are the enablers. If you take this even further, the combination between the genotype and phenotype will be where in the next five years India can be. If we get there then we do not have to worry about 1.3 Billion population, we can pick vulnerable populations and treat them at 1/10th the cost using a preventive route,” he said.
Siemens Healthineers, the German health-tech powerhouse is investing heavily in software and new-age digital technology research in India as it envisions the next revolution in medical infrastructure to be routed via digital technology. Dileep Mangsuli, Executive Director of the company is reported to have said that artificial intelligence, in particular, would act as the “lever” to move from image analytics to disease pathways to digital twins with healthcare transcending from “disease management” to “wellness management”.
Signs of transformation
“Affordability, reach, accuracy, efficiency, empowerment of patients in decision-making – these are marked improvements that artificial intelligence has brought about in healthcare in India,” Rangaraj Sriramulu an independent artificial intelligence expert remarked.
The former Vice President of business transformation with Capgemini pointed out that during the last 7-8 years, models for cancer detection have been fed with more samples of a diagnosis at different levels arrived at through human judgment. Appreciating the large sample size of the data being analysed by the models, he indicated that the volume of the case studies would be much higher than the number of patients attended by a large team of doctors – individually or as a team in their lifetime. This assistance from artificial intelligence to medical practitioners has been a game changer in saving wastage of time and resources in the process of diagnosis.
“Previously, villages did not have access to these models. Now the village healthcare facilities are being given access to this model so that the doctors at these locations can get support from experts in cities like Manipal and Bangalore. Technology is ensuring that patients in the remotest villages get the best facility so that a disease can be detected earlier, and they can get cured.”
Sriramulu too admits that while there has been considerable technological advancement in the southern states of the country there has been relatively less penetration in the eastern belt.
Global health tech start-up, Qure.ai found that within two months of deploying its artificial intelligence-based chest x-ray solution for detecting tuberculosis in the remote Indian cities of Baran in Rajasthan and Sonbhadra in Uttar Pradesh, the notification rates shot to 90.14% from 67.8%. Within 18 months of rolling out the operation, the company saw enrolment at the Tuberculosis TB centres in these cities jump by nearly 85%. The detection of TB is significant for India as the country accounts for one-third of the world’s incidence of the disease.
In India, the company operates in a public-private partnership with the government’s NITI Aayog. It collaborates with NGOs and community healthcare workers on the ground to earn the trust of the locals. It also actively trains healthcare workers at its 24,855 rural and 5,190 urban public health centres so that they are equipped to provide a uniforFdem standard of care.
“Their community health workers regular networking and trust-building are critical when it comes to reassuring residents about technology. At the same time, it’s important to equip the team with the right set of tools to tackle the everyday challenges on the ground,” the company said in a written response to a set of questions from Business Transformation Asia.
“Our deployment of lung health suite includes more than our artificial intelligence-enabled chest X-ray solution. We provide the team with workflow optimisation and management solution called qTrack to get real-time updates on the cases and monitor the patient progression, treatment cycles and such. We also have a model where we deploy qBoxes – an alternate solution for remote locations where there is no competent network or connectivity.”
“Empowerment of patients are improvements that artificial intelligence has brought about in healthcare in India”
Curebay has been able to bridge the gap between patient and provider of medical care in rural Odisha, through its hybrid, e-clinic model in remote locations. The idea is to provide a gamut of high-quality and affordable medical services – diagnosis, consultation and medicine delivery in the last mile model to rural and semi-urban remote locations.
The hybrid model comprises primary health workers who assist patients at the locations before they are connected to doctors in urban locations via video calls. The technology platform then helps its customers understand their prescriptions and arranges for riders to deliver these medicines to the doorstep.
Bangalore-based Niramai Health Analytix uses artificial intelligence and a thermal sensing device to detect breast cancer in its early stages, the automated and portable medical device making it possible for screening in the remotest of clinics. Similarly, Tricog provides virtual services in the field of cardiology in remote locations.
A theme that is common to all of these ventures is connectivity, quality and cost-effectiveness, all very important requirements for healthcare inclusion in a country with as large and economically disparate a population as India. However, digital technologies including artificial intelligence-based solutions have helped do away with the geographical barriers at least for consultation across cities.
USE COLOR CODING AS BELOW
|Technology Enablers across the Drug Research and development Life Cycle|
|Artificial Intelligence||Augmented Reality and Virtual Reality||Genetics and Genomics|
|Identify new targets/indications and improve success rates||Improve trial participant experience||Identify responders for oncology therapies|
|Select appropriate research sites||Enhance molecule analysis||Develop targeted therapies outside oncology|
|Improve clinical trial patient matching and recruitment||Create new therapeutic modalities||Create individualised therapies|
|Reduce patient drop-outs|
|Predict trial risks, cost and quality|
|Improve clinical trial design|
|Blockchain||Cloud and Edge Computing||Wearables and Sensors|
|Secure research transfer||Improve data aggregation and storage||Capture real-world data for better trial design|
|Secure health data collection and sharing||Allow affordable high-throughput screening||Improve patient adherence|
|Increase efficiency in identity and access management||Help in continuous passive monitoring|
|Improve trial quality and patients’ safety at a reduced cost||Leverage digital endpoints in clinical trial|
|Today: already in use|
|Tomorrow: evidence of initial use cases and expected to become commonplace shortly|
|Source: Indian Pharmaceutical Industry 2021: Future is Now, February 2021; EY|
Most global pharma companies are leveraging technologies such as AI/ML, cloud computing, etc. in the drug discovery and research phase to increase productivity and reduce timelines while clinical development is also going virtual.
Partnerships driving change
Experts indicated that despite a large-scale adoption and willingness to transform the healthcare services, both at levels of the practitioners and policymakers, there are gaps that need to be plugged if India aims to deploy the AI model on a larger scale across the country.
The biggest problem in tier-3, tier-4 cities and villages, is the absence of data on the medical history of patients. Certain data is non-negotiable to run certain algorithms. A single repository of medical data is important for medical practitioners to be able to make quick diagnoses. Further, there are risks to free data sharing between institutions as well. There are serious gaps in data privacy laws in India which could lead to sensitive information regarding the patient’s medical history being leaked making them vulnerable.
Bhaskaran points out the need for an indigenous solution for India’s current situation. According to him, the country needs a partnership between the government and private sector for this model to work in India because the penetration of private-sector healthcare facilities is limited to big cities. Besides, the roadblock to the development of AI-based solutions in healthcare has been the country’s inconsistent regulations that have kept investors away from the sector.
Talking about interest from companies that manufacture original medical equipment in investing in big data solutions, Bhaskaran said, “There is a lot that can be worked through and there is a clear value behind it as well. Especially Siemens, GE. They are looking at this space very actively… They will also invest if they see a lot more happening from the government’s end as well. A lot of times the challenge is the unavailability of data to use the right kind of model and that is what the government needs to solve. Infrastructure and investments will be made by these companies if they see that the government is equally supportive of this.”
A report by Philips showed that leading healthcare leaders in India almost unanimously agreed that the government’s healthcare policies and plans were instrumental in building a resilient healthcare system. For instance, the Pradhan Mantri Jan Arogya Yojana PM-JAY is a public health insurance scheme that aims to provide free-of-cost insurance coverage to low-income groups. There is also a decisive move from the government towards increasing investment in public health and ensuring transparent and consistent healthcare protocols and procedures, the report noted.
“When the country is able to democratise healthcare across India, it will change the game in a big way. One needs to think of it as fundamental and then start to look at the ecosystem. Whether it is the government or the healthcare companies, or start-ups or specific medical companies, if all of them work for that end outcome model, there is potential for change,” Bhaskaran concluded.
The NASSCOM report iterated the need for a “strong, win-win” partnership of healthcare organisations with technology-based product companies, service providers, healthcare AI start-ups and academic institutions for India to unlock the true potential of deep technology in the sector.
- Integration of teleconsultation and sample data-based diagnoses into traditional healthcare certainly received an impetus during the pandemic.
- Deep tech, including AI/ML, have improved medical infrastructure and research; AI has been used in early diagnoses of life-threatening diseases like Lung Cancer and TB, increasing the chances of survival.
- Healthcare leaders in India are taking a three-step approach to transformation: short-term investment in telehealth to ensure healthcare for all, investment in AI for improving care outcomes, and collaboration with other stakeholders to facilitate the use of deep tech.
Conventional technology has been driving innovation in pharmaceuticals and healthcare practices, which now needs to adopt digital platforms to transform.