It is not surprising that India has a booming healthcare sector, considering that a population of 1.35 billion in 2018 is likely to exhibit myriad morbidities (World Bank, 2018). With a three-fold increase in the healthcare market and governmental projections pushing a 372 billion USD mark in 2022, the sector is ready for significant technological interventions. (IBEF, 2019). On the downside however, the sector is beleaguered by concerns that range from access barriers and poor doctor-patient ratio to affordability and poor healthcare infrastructure. Artificial intelligence (AI) comes with a promise of not only overcoming a majority of these barriers, but also eliminating predispositions, such as the recency bias, in medical sciences. Riding the investment wave AI—robotics and Internet of Things (IoTs) can revolutionise healthcare.
Healthcare concerns can be broadly classified into those which are predictive in nature—pre-empting a problem and providing a solution to abrogate the issue; and, prescriptive, where a treatment is offered based on an informed decision. When AI is deployed to prepare algorithms that help map patterns by collecting and analysing gathered data—both spatial and temporal, it is found that it can provide astounding results in preparing a response ahead of time and influencing outcomes. From early detection of diseases based on analysis of past data, to decentralised diagnostic testing, AI can singularly alleviate healthcare problems in rural and remote areas. AI algorithms are able, with a certain degree of precision, to screen diseases, which can help triaging high priority cases, enhancing the productivity of healthcare professionals.
In India, companies such as Artelus, a Bangalore based AI enabled healthcare unit, works to provide an image-based early detection facility for diabetic retinopathy . The Deep Learning and AI based setup in Artelus can help identify at a primary screening, lesions or abnormalities present in fundus images and report it to the doctor, making it impactful for areas that lack this facility. These healthcare capacities extend beyond the boundaries of hospitals and specialised clinics, reduce cost and improve health outcomes. There are many such applications for various anatomical disorders world over, such as IBM Watson for oncology and many private hospitals in India, such as the Manipal group of hospitals, make use of such interfaces.
Interestingly, AI can also screen mental disorders in its early stages, like depression. Wysa, a bot developed by Bangalore based start-up Touchkin, is delving into the domain of emotional wellness. Supported by human coaches, the bot helps cure depressive thoughts (wysa.io).The app records and analyses various physiological factors like sleep patterns, blood sugar levels and other behavioural insights and predicts the user’s mental health. In the event that the bot identifies an individual who needs intensive care, it refers the case to professionals, who can then intervene.
Niramai, a Bengaluru based healthcare start-up has developed a non-invasive, radiation free breast cancer detection software that uses a high resolution thermal sensing device and a cloud hosted analytics solution for screening thermal images that accurately leads to the early detection of tumours. Orbuculum, another start-up in Bengaluru analyses genomic data to predict a gamut of diseases.
Telangana in fact, has adopted a cloud-based analytics tool developed by Microsoft, for the state’s Rashtriya Bal Swasthya Karyakram, to reduce avoidable blindness among children by screening them for the ailment. Thus predictive AI usage in healthcare can provide actionable insights based on available data and thus improve healthcare penetration.
Prescriptive analytics on the other hand, make use of machine learning to determine the best solution or outcome among various courses of action. For instance, an AI algorithm in IBM Watson for oncology will use information from relevant literature to assess the information from a patient’s medical record and throw up potential treatment options ranked by level of confidence. The oncologist can then use the results along with the supporting evidence to arrive at the appropriate treatment option. Such AI interfaces aid human decision making for doctors and health administrators to use critical data to support clinical, financial and operational decisions. It can lower the cost of healthcare, improve patient efficiency and mitigate operational risks.
This technology has found its way into hospitals in India as well. Manipal uses IBM Watson for Oncology. Max Healthcare,India has deployed the GE Healthcare’s web-based radiology information system—the Centricity RIS-IC. Integrated with the GE -picture archive and communication system (PACS), the programme addresses a healthcare unit’s evolving radiology workflow to enable seamless access to images like X-Ray, MRI and more for patients across locations. It can therefore be used to create an integrated customer record of patients. Fortis Hospital, Bengaluru has partnered with Phable, a healthcare start-up in India, to provide an App to the patients that allows for constant monitoring by the doctor in the event any new symptoms emerge and can also help patients manage medication, tests, diet, exercise etc.
The medical equipment industry are also using AI and machine learning to develop smart wearables and insertables that gather individual data and detect anomalies. The US drug major Abott has launched an Insertable Cardiac Monitor (ICM) that can alert users about irregular heartbeats (arrhythmias) on their smartphone screen (cardiovascular.abbott). Ten3T, another Indian healthcare start-up has launched a wearable device named ‘Smart Patch’ that inter alia measures the patients’ temperature, pulse and blood pressure and provides real time monitoring facility (ten3thealth.com). AI also delves into solving problems related to the pharma supply chain with tools streamlining the entire process from drug generation to delivery. Pharmarack, a Pune based start-up has developed a tool to automate the sales and operational processes of pharma companies (pharmarack.com). It offers management solutions from the origin of order to its completion, in a seamless platform to process, track, and settle all orders, creating complete visibility of business operations in real time.
The AI and machine learning has begun to partner with the medical insurance sector as well. Embedded into existing insurance frameworks, the platform helps insurers to automate and expedite the process, minimising delays and frauds. ICICI Lombard and HDFC bank with their AI and Natural Language Processing (NLP) based chat bots named MyRA and SPOK, respectively, are using AI to categorise, prioritise and respond to customer emails and mine appropriate information for an improved operational efficiency (myralabs.com;
Dhawan 2018) .
Ethical Concerns in AI Healthcare
In 2008, Google Flu Trends (GFT), began aggregating and analysing big data from a range of countries based on Google search queries. GFT then went on to predict or ‘nowcast’ the onset on flu outbreaks days before they were reported by the global Centres for Disease Control and Prevention (Lazer and Kennedy, 2015). However, GFT failed to accurately predict the 2009 global swine flu pandemic, as its algorithm over relied on the Google search patterns rather than the traditional reporting of the disease. In 2013, the GFT failed again, missing predictions by 140 per cent at the peak of the flu season. The project was thereafter closed. It is true that big data is competent to model disease spread and identify emergencies, way faster than traditional methods, but the method and the data used becomes critical in identifying a trend—which is why the GFT lost out. AI and machine learning therefore, needs to be understood in the perspective of its own set of challenges. Apart from the data accuracy concerns, a faulty algorithm can distort the results. In a scenario where humans begin to depend on AI for its decisions, such errors can lead to critical drawbacks in healthcare.
AI, if handled improperly can result in data leaks, which would lead to privacy violations. In India the consent forms for data sharing are not mandatorily filled by the healthcare units—and patients too are barely aware of its need. In practice, doctor-patient confidentiality is in the realm of ethics. Therefore, there is always a chance that the profile of patients can be exploited by companies and consequent data breach can lead to an erosion of trust among the general public. For instance, in 2016, a Mumbai based diagnostic laboratory Health Solutions had to remove over 35,000 medical records of patients which included HIV reports, when its data leaked (Indian Express, 2019). Such breaches are a constant threat that AI needs to combat in order to maintain patient confidentiality.
Then of course there is the single language predisposition that AI holds, where English predominates, making it difficult for the technology to penetrate rural areas. With a huge internet connectivity of over 566 million people in 2018 (The Economics Time, 2019), AI can make greater headway if vernacular usage is encouraged.
Importantly, an AI enabled system thrives on data—generation of poor quality data coupled with poor digital infrastructure and storage can skew results, rendering programmes ineffective. In India lack of trained professionals for data handling also impedes the penetration of AI in this sector. Also, the focus of AI in healthcare in India is nascent and fairly narrow, with disease specific solutions.
Way Forward
AI has significant scope in developing solutions in bettering the lives of humans, and healthcare is a priority area of research. Despite the many challenges AI and machine learning exhibit at present, ground is being made for larger and more accurate predictive and prescriptive programmes. An ambient policy framework by the Indian government that makes for favourable investments in the AI and machine learning sector can help augment the paucity of quality healthcare professionals in many locations of the nation
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Petrol in India is cheaper than in countries like Hong Kong, Germany and the UK but costlier than in China, Brazil, Japan, the US, Russia, Pakistan and Sri Lanka, a Bank of Baroda Economics Research report showed.
Rising fuel prices in India have led to considerable debate on which government, state or central, should be lowering their taxes to keep prices under control.
The rise in fuel prices is mainly due to the global price of crude oil (raw material for making petrol and diesel) going up. Further, a stronger dollar has added to the cost of crude oil.
Amongst comparable countries (per capita wise), prices in India are higher than those in Vietnam, Kenya, Ukraine, Bangladesh, Nepal, Pakistan, Sri Lanka, and Venezuela. Countries that are major oil producers have much lower prices.
In the report, the Philippines has a comparable petrol price but has a per capita income higher than India by over 50 per cent.
Countries which have a lower per capita income like Kenya, Bangladesh, Nepal, Pakistan, and Venezuela have much lower prices of petrol and hence are impacted less than India.
“Therefore there is still a strong case for the government to consider lowering the taxes on fuel to protect the interest of the people,” the report argued.
India is the world’s third-biggest oil consuming and importing nation. It imports 85 per cent of its oil needs and so prices retail fuel at import parity rates.
With the global surge in energy prices, the cost of producing petrol, diesel and other petroleum products also went up for oil companies in India.
They raised petrol and diesel prices by Rs 10 a litre in just over a fortnight beginning March 22 but hit a pause button soon after as the move faced criticism and the opposition parties asked the government to cut taxes instead.
India imports most of its oil from a group of countries called the ‘OPEC +’ (i.e, Iran, Iraq, Saudi Arabia, Venezuela, Kuwait, United Arab Emirates, Russia, etc), which produces 40% of the world’s crude oil.
As they have the power to dictate fuel supply and prices, their decision of limiting the global supply reduces supply in India, thus raising prices
The government charges about 167% tax (excise) on petrol and 129% on diesel as compared to US (20%), UK (62%), Italy and Germany (65%).
The abominable excise duty is 2/3rd of the cost, and the base price, dealer commission and freight form the rest.
Here is an approximate break-up (in Rs):
a)Base Price | 39 |
b)Freight | 0.34 |
c) Price Charged to Dealers = (a+b) | 39.34 |
d) Excise Duty | 40.17 |
e) Dealer Commission | 4.68 |
f) VAT | 25.35 |
g) Retail Selling Price | 109.54 |
Looked closely, much of the cost of petrol and diesel is due to higher tax rate by govt, specifically excise duty.
So the question is why government is not reducing the prices ?
India, being a developing country, it does require gigantic amount of funding for its infrastructure projects as well as welfare schemes.
However, we as a society is yet to be tax-compliant. Many people evade the direct tax and that’s the reason why govt’s hands are tied. Govt. needs the money to fund various programs and at the same time it is not generating enough revenue from direct taxes.
That’s the reason why, govt is bumping up its revenue through higher indirect taxes such as GST or excise duty as in the case of petrol and diesel.
Direct taxes are progressive as it taxes according to an individuals’ income however indirect tax such as excise duty or GST are regressive in the sense that the poorest of the poor and richest of the rich have to pay the same amount.
Does not matter, if you are an auto-driver or owner of a Mercedes, end of the day both pay the same price for petrol/diesel-that’s why it is regressive in nature.
But unlike direct tax where tax evasion is rampant, indirect tax can not be evaded due to their very nature and as long as huge no of Indians keep evading direct taxes, indirect tax such as excise duty will be difficult for the govt to reduce, because it may reduce the revenue and hamper may programs of the govt.
Globally, around 80% of wastewater flows back into the ecosystem without being treated or reused, according to the United Nations.
This can pose a significant environmental and health threat.
In the absence of cost-effective, sustainable, disruptive water management solutions, about 70% of sewage is discharged untreated into India’s water bodies.
A staggering 21% of diseases are caused by contaminated water in India, according to the World Bank, and one in five children die before their fifth birthday because of poor sanitation and hygiene conditions, according to Startup India.
As we confront these public health challenges emerging out of environmental concerns, expanding the scope of public health/environmental engineering science becomes pivotal.
For India to achieve its sustainable development goals of clean water and sanitation and to address the growing demands for water consumption and preservation of both surface water bodies and groundwater resources, it is essential to find and implement innovative ways of treating wastewater.
It is in this context why the specialised cadre of public health engineers, also known as sanitation engineers or environmental engineers, is best suited to provide the growing urban and rural water supply and to manage solid waste and wastewater.
Traditionally, engineering and public health have been understood as different fields.
Currently in India, civil engineering incorporates a course or two on environmental engineering for students to learn about wastewater management as a part of their pre-service and in-service training.
Most often, civil engineers do not have adequate skills to address public health problems. And public health professionals do not have adequate engineering skills.
India aims to supply 55 litres of water per person per day by 2024 under its Jal Jeevan Mission to install functional household tap connections.
The goal of reaching every rural household with functional tap water can be achieved in a sustainable and resilient manner only if the cadre of public health engineers is expanded and strengthened.
In India, public health engineering is executed by the Public Works Department or by health officials.
This differs from international trends. To manage a wastewater treatment plant in Europe, for example, a candidate must specialise in wastewater engineering.
Furthermore, public health engineering should be developed as an interdisciplinary field. Engineers can significantly contribute to public health in defining what is possible, identifying limitations, and shaping workable solutions with a problem-solving approach.
Similarly, public health professionals can contribute to engineering through well-researched understanding of health issues, measured risks and how course correction can be initiated.
Once both meet, a public health engineer can identify a health risk, work on developing concrete solutions such as new health and safety practices or specialised equipment, in order to correct the safety concern..
There is no doubt that the majority of diseases are water-related, transmitted through consumption of contaminated water, vectors breeding in stagnated water, or lack of adequate quantity of good quality water for proper personal hygiene.
Diseases cannot be contained unless we provide good quality and adequate quantity of water. Most of the world’s diseases can be prevented by considering this.
Training our young minds towards creating sustainable water management systems would be the first step.
Currently, institutions like the Indian Institute of Technology, Madras (IIT-M) are considering initiating public health engineering as a separate discipline.
To leverage this opportunity even further, India needs to scale up in the same direction.
Consider this hypothetical situation: Rajalakshmi, from a remote Karnataka village spots a business opportunity.
She knows that flowers, discarded in the thousands by temples can be handcrafted into incense sticks.
She wants to find a market for the product and hopefully, employ some people to help her. Soon enough though, she discovers that starting a business is a herculean task for a person like her.
There is a laborious process of rules and regulations to go through, bribes to pay on the way and no actual means to transport her product to its market.
After making her first batch of agarbathis and taking it to Bengaluru by bus, she decides the venture is not easy and gives up.
On the flipside of this is a young entrepreneur in Bengaluru. Let’s call him Deepak. He wants to start an internet-based business selling sustainably made agarbathis.
He has no trouble getting investors and to mobilise supply chains. His paperwork is over in a matter of days and his business is set up quickly and ready to grow.
Never mind that the business is built on aggregation of small sellers who will not see half the profit .
Is this scenario really all that hypothetical or emblematic of how we think about entrepreneurship in India?
Between our national obsession with unicorns on one side and glorifying the person running a pakora stall for survival as an example of viable entrepreneurship on the other, is the middle ground in entrepreneurship—a space that should have seen millions of thriving small and medium businesses, but remains so sparsely occupied that you could almost miss it.
If we are to achieve meaningful economic growth in our country, we need to incorporate, in our national conversation on entrepreneurship, ways of addressing the missing middle.
Spread out across India’s small towns and cities, this is a class of entrepreneurs that have been hit by a triple wave over the last five years, buffeted first by the inadvertent fallout of demonetization, being unprepared for GST, and then by the endless pain of the covid-19 pandemic.
As we finally appear to be reaching some level of normality, now is the opportune time to identify the kind of industries that make up this layer, the opportunities they should be afforded, and the best ways to scale up their functioning in the shortest time frame.
But, why pay so much attention to these industries when we should be celebrating, as we do, our booming startup space?
It is indeed true that India has the third largest number of unicorns in the world now, adding 42 in 2021 alone. Braving all the disruptions of the pandemic, it was a year in which Indian startups raised $24.1 billion in equity investments, according to a NASSCOM-Zinnov report last year.
However, this is a story of lopsided growth.
The cities of Bengaluru, Delhi/NCR, and Mumbai together claim three-fourths of these startup deals while emerging hubs like Ahmedabad, Coimbatore, and Jaipur account for the rest.
This leap in the startup space has created 6.6 lakh direct jobs and a few million indirect jobs. Is that good enough for a country that sends 12 million fresh graduates to its workforce every year?
It doesn’t even make a dent on arguably our biggest unemployment in recent history—in April 2020 when the country shutdown to battle covid-19.
Technology-intensive start-ups are constrained in their ability to create jobs—and hybrid work models and artificial intelligence (AI) have further accelerated unemployment.
What we need to focus on, therefore, is the labour-intensive micro, small and medium enterprise (MSME). Here, we begin to get to a definitional notion of what we called the mundane middle and the problems it currently faces.
India has an estimated 63 million enterprises. But, out of 100 companies, 95 are micro enterprises—employing less than five people, four are small to medium and barely one is large.
The questions to ask are: why are Indian MSMEs failing to grow from micro to small and medium and then be spurred on to make the leap into large companies?
At the Global Alliance for Mass Entrepreneurship (GAME), we have advocated for a National Mission for Mass Entrepreneurship, the need for which is more pronounced now than ever before.
Whenever India has worked to achieve a significant economic milestone in a limited span of time, it has worked best in mission mode. Think of the Green Revolution or Operation Flood.
From across various states, there are enough examples of approaches that work to catalyse mass entrepreneurship.
The introduction of entrepreneurship mindset curriculum (EMC) in schools through alliance mode of working by a number of agencies has shown significant improvement in academic and life outcomes.
Through creative teaching methods, students are encouraged to inculcate 21st century skills like creativity, problem solving, critical thinking and leadership which are not only foundational for entrepreneurship but essential to thrive in our complex world.
Udhyam Learning Foundation has been involved with the Government of Delhi since 2018 to help young people across over 1,000 schools to develop an entrepreneurial mindset.
One pilot programme introduced the concept of ‘seed money’ and saw 41 students turn their ideas into profit-making ventures. Other programmes teach qualities like grit and resourcefulness.
If you think these are isolated examples, consider some larger data trends.
The Observer Research Foundation and The World Economic Forum released the Young India and Work: A Survey of Youth Aspirations in 2018.
When asked which type of work arrangement they prefer, 49% of the youth surveyed said they prefer a job in the public sector.
However, 38% selected self-employment as an entrepreneur as their ideal type of job. The spirit of entrepreneurship is latent and waiting to be unleashed.
The same can be said for building networks of successful women entrepreneurs—so crucial when the participation of women in the Indian economy has declined to an abysmal 20%.
The majority of India’s 63 million firms are informal —fewer than 20% are registered for GST.
Research shows that companies that start out as formal enterprises become two-three times more productive than a similar informal business.
So why do firms prefer to be informal? In most cases, it’s because of the sheer cost and difficulty of complying with the different regulations.
We have academia and non-profits working as ecosystem enablers providing insights and evidence-based models for growth. We have large private corporations and philanthropic and funding agencies ready to invest.
It should be in the scope of a National Mass Entrepreneurship Mission to bring all of them together to work in mission mode so that the gap between thought leadership and action can finally be bridged.