by Pratik Avhad
India’s health care system is facing many challenges, including affordability, quality of care and access to services. India’s GDP per capita income is just $1,940, and out of pocket health care spending is almost 70 per cent, causing hardship for much of India’s population.1,2 In a systematic analysis of data from the Global Burden of Disease Study 2016, researchers ranked India’s quality of care and access as 145th out of 195 countries.3 However, with the fourth industrial revolution unfolding at pace, Pratik Avhad, the Centre’s India-based analyst, uses this week’s blog to explore whether artificial intelligence (AI) could be the answer to India’s quality and access challenges.
AI solutions for health care
In simple terms, AI refers to using computers to perform tasks that would usually require human intelligence.4 The deployment of AI within the health care industry currently includes a range of technologies that allow machines to sense, understand, act and learn in order to carry out administrative and clinical health care functions. AI technologies include natural language processing, machine learning, computer vision, chatbots and voice recognition. Research by Global Market Insights forecasts that globally, the health care AI market will grow at a CAGR (compound annual growth rate) of 40 per cent from 2017 to 2024, as it finds multiple applications across the industry.5 These include remote consultations, virtual nurses, AI-enabled hospital care, medical image diagnosis, drug discovery, robotic surgery, back office administrative solutions for clinical coding, health record maintenance, and connected medical devices. Some analysts are predicting that AI will decrease treatment costs by 50 per cent and improve outcomes by around 40 per cent.6
However, the health care AI market faces major challenge in the form of deployment issues, with a lot of inherent risks and difficulties in deploying these large and complex systems due to poor human-computer interaction.7 Questions remain, therefore, as to the extent to which AI will fulfill its potential and live up to the hype.
AI in India’s health care industry
The types of AI being used in health care are descriptive, predictive and prescriptive:
- descriptive: utilises data from past events to uncover further insights and trends that may have been missed by medical professionals
- predictive: used by medical professionals to predict future insights from descriptive data
- prescriptive: suggests possible courses of action for medical professionals.8
Accenture Research, in collaboration with Frontier Economics, modeled the impact of AI for India and determined that it could add $957 billion (15 per cent of current gross value added) to India’s economy by 2035.9 In India’s health care sector, investment in AI is primarily targeted at expanding access to medical services to underserved populations such as those living in rural areas, and to those members of the population where affordability is the greatest barrier to health care access.
Challenges in AI implementation in India’s health care industry
Although there is huge potential for AI to transform healthcare in India, ethical, legal, and cultural factors need to be considered by developers, practitioners, and policy makers when designing, using, and regulating AI. Implementing AI solutions in India will not be easy, and numerous challenges will need to be overcome, including:
- data access: having access to large data sets can enable players operating in this field to push for better solutions. Whilst India has adopted a policy on electronic health records (EHR), the roll-out has not been consistent across the industry and has been detrimental to the quality of data. A lack of robust open clinical data sets is also hindering the development of AI in India
- regulations: India currently has no appropriate regulatory authority for AI in health care, with no existing regulation around data anonymisation, raising concerns over privacy and security of data
- design guidelines: India currently lacks standard design guidelines for future AI systems, which can provide a framework to ensure privacy, security, quality, and accuracy of AI solutions, helping to address the existing issues of ethics and trust.
Other challenges include high resource costs, low awareness of benefits of adopting AI in business processes, inadequately skilled professionals, underdeveloped infrastructure, limited investment, and issues of information asymmetry between health care provider and AI solution developers.10
The future of AI in India’s health care industry
The implementation and development potential for AI in India is huge. India currently ranks third globally in AI implementation across all sectors behind only the US and China.11 For India to move closer towards the goal of achieving widespread implementation of AI in the health care industry, we have identified the following steps that could help address the above challenges:
- improve data access and quality: encouragement should be given to generating an Open Data system that meets the standards in terms of interoperability, privacy and safety. Increasing emphasis should also be placed on collating relevant data in a suitable form for AI analysis
- increase stakeholder collaboration: while India’s government has set up an AI Task Force to set recommendations for AI to boost the economy, it requires collaboration with industry and academia in order to ensure that the technologies employed align to the government’s plan12
- promote academic involvement: academic institutions, medical colleges and hospitals should establish AI research facilities to promote cross-country collaboration and knowledge sharing13
- generate a skilled workforce: an adequately skilled workforce is needed for developing AI solutions, and end-users need training to help adoption of technology in the sector
- develop a regulatory framework: establishing a dedicated national regulatory agency in India with the capability to build a framework for AI in health care will bring transparency and accountability, along with ensuring privacy and security of data.
While the use of AI in health care has the potential to supplement the current health care delivery model in India and help tackle the challenges of quality, access and affordability, much remains to be done before the full benefits of AI can be realised. In particular, improvements in data quality and an open data policy, developing a robust regulatory landscape, and equipping the labour force with the necessary skills to adopt AI and be open to the changes that AI could bring would go a long way to attracting investment into AI for the health care industry. It would also provide the foundation for a flourishing AI health care ecosystem in India, which would benefit millions of people across the country.