INTRODUCTION
Digital Technology has taken a huge leap in revolutionizing globally. Governments of developing countries across the globe is emphasizing on improved access to primary health facilities and services by setting country specific healthcare targets. However, according to the World Health Statistics 2019, there is a considerable gap in delivering and accessing the healthcare services in various developing countries. This has led to the deterioration in the health of general public resulting into poor health further aggravating poverty.
The government spending on healthcare in India is one of the lowest in the world. The patient doctor ratio in India is as low as 1,700:1. Also, ~70% of the healthcare infrastructure is in cities, which cater to ~30% of the country’s population.. Due to the unequal distribution in India’s healthcare sector, lack of trained healthcare clinicians, low governmental spending, inadequate infrastructure, weak doctorpatient ratio, late diagnosis, India provides a room for innovative, sustainable and scalable healthcare digital transformation to improve lives. The adoption of artificial intelligence (AI) is reshaping the Indian healthcare market significantly.
AI-enabled healthcare services like automated analysis of medical tests, predictive healthcare diagnosis, automation of healthcare diagnosis with the help of monitoring equipment, and wearable sensor-based medical devices, are expected to revolutionize medical treatment processes in the country. It is predicted that the applications of artificial intelligence in the healthcare space will be worth INR ~431.97 Bn by 2021, expanding at a rate of ~40%.
Based on this growth of AI application in healthcare, the doctor-patient ratio in India is expected to reach ~6.9:1,000 by 2023, from its 2017 ratio of ~4.8:1000. With the use of artificial intelligence applications, doctors can offer their services to more patients and reduce the existing gap in demand and supply of medical services in the country. AI-enabled healthcare services can be delivered at lower costs with increased efficiency and an emphasis on diagnostics.
Moreover, artificial intelligence enables hospitals to implement patient centric plans and eliminate unnecessary hospital procedures, making delivery of healthcare services faster in India. Though India is using Artificial Intelligence in its major healthcare segments i.e., Hospitals; Pharmaceuticals; Diagnostics; Medical equipment and supplies; Medical insurance; Tele-medicine, it still has a vast untapped potential for AI solutions to improve operational efficiencies and quality of healthcare. According to the Indian AI Healthcare Market 2019- 2025 report, Indian AI in the healthcare industry is estimated to grow significantly at a CAGR of 50.9% during the forecast period of 2019-2025.
DEVELOPMENT AND INNOVATION
Government initiatives: The Information Technology Act, 2000, and the Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011, mandate that service providers and patients exchange information constantly by using the latest technologies. National eHealth Authority (NeHA) – An authority which is responsible for the expansion of the integrated health information system within India. The government is putting in efforts to digitize the healthcare system in India. Planning for an Integrated Health Information Program (IHIP) to create Electronic Health Record for all citizens in order to enable the interoperability of existing EHRs is currently in development (National Health Portal of India, 2017).
In a recent discussion by NITI Aayog outlined the ambitions of creating a ‘National Health Stack (NHS)’ to organize both personal health records and service provider records available on cloud-based services to private healthcare stakeholders which is is expected to consist of mainly four elements – electronic health registries of health service providers and beneficiaries, coverage and claims platform, a federated personal health records framework and a national health analytics platform. The United States-India Science and Technology Endowment Fund, is aimed at helping teams of innovators and entrepreneurs from both countries, whose products will improve the quality of healthcare, by harnessing the power of artificial intelligence. India is approaching towards ‘Imaging AI in Practice’ wherein a patient is studied, along with the entire imaging workflow and the images are finally interpreted by the physician.
AIRad Companion, a cloudbased augmented workflow solution helps to reduce the burden of repetitive task and increases the diagnostic precision while interpreting medical images. The automatic post-processing of imaging datasets through AI-powered algorithms and high case volumes helps to ease the daily workflow in clinical scenario. The deployment of AI- Rad Companion extension via team play digital health platform eases regular updates and facilitates the integration of new ideas into existing IT market. In the field of biomedical research, viral culturing in laboratories is being practiced wherein quick insights are fleshed out by the scientists through accelerating simulation time between the interaction and reaction of compounds and virals.
With the help of AI based machine simulation becomes useful in testing environment where viral and strains take on polymorphic identities. Through deep learning, AI technology dives into knowledge repositories to learn from use-cases and help patients. Additionally, the pioneering work of artificial intelligence is also under its way to perform remote robotic surgeries where doctors from any location can treat the patients at any location in the world with the help of other collaborative technologies like AR and 5G.
LEGAL FRAMEWORK: CHALLENGES AND IMPLICATIONS
Challenges
The AI systems just being in their development have much of the challenges to be faced in that state relates to :-
DATA ACCESS
These AI systems are always dependent on the availability of large data access of their consumers, working the healthcare system on AI requires a lot of access of the patient’s previous medical history, records etc., which would be quite a challenge in India, especially in rural and semi-rural areas, where these records and data aren’t managed well.
BLIND SPOTS IN DATA COLLECTION
Currently, there are a lot of caste, gender, and class based irregularities in the medical systems in many areas of the nation, many lower cast women are denied of proper health care because of certain practice of elitism in those areas, this leads to fewer representation of a certain type of data in the medicine formulation, which in turn may be effective for only a certain amount of people in the population, and not all of them.
HIGHER COSTS
The whole structure employed in the AI systems is very expensive; the costs of training, testing, and deploying AI systems are very high. Collection of data is also expensive in itself, and most of the Healthcare companies would be relying over cloud services of foreign companies, because they don’t have that much of Technological support.
PRIVACY AND MISUSE OF PRIVATE DATA
These AI systems would be requiring a lot of Private Data of their patients, which in turn could be a big risk if not secured properly, because hackers may sell this data to foreign companies of intelligence services, causing a threat to our country and its people. There can be a lot of malpractices be taking place by misusing the customer data, many drug companies would directly know the ailments of patients, and may hike up their prices, many bankers may use this data to evaluate the eligibility of loans as a person with poor health may be seen as unable to work, and might be blacklisted by certain banks to get loans.
ACCOUNTABILITY
A computer most certainly cannot be held accountable in case of occurring of any error or misdiagnosis. There has to be a human in the loop, They AI systems should not be intended to replace doctors. Current Legal Framework and Implications Currently, the medical professional is held responsible for any deficiency or negligence in his/her services. Due to absence of any specific law enacted to deal with AI and the advanced technology in India it is difficult to distinguish cases where the error occurs in diagnosis malfunction of technology or use of inaccurate data. The healthcare organizations will have to face the growing cybersecurity challenges besides the policymakers will have the responsibility of enacting laws ensuring careful governance and security arrangements for stored data. Currently, the cases relating to AI in healthcare might be governed under other laws or acts like the COPRA (Consumer Protection Act), as the patient is a consumer using the services provided by the AI systems, and in case of any default may take any course of action according to COPRA, for instance, if a patient has been prescribed a certain drug, which contributes towards worsening his condition, he will have a remedy under the COPRA.
Similarly, if any patient’s personal information is being shared or either being leaked by mistake or any error in the AI system, and which the concerned company isn’t authorized to do so, may face certain legal implications under the Data Protection and Privacy laws of India. Admittedly, there is a void in the legal and regulatory framework affecting Artificial Intelligence. On one hand the AI applications along with supporting technologies are expected to bring transformative changes on the other hand it has disruptive potential in the healthcare sector across hospitals and hospital management, mental health and well-being, pharmaceuticals, insurance and medicine. The adoption of AI in healthcare sectors would require policy and institutional framework to guide and design the use of Artificial Intelligence system. With the availability of health related data, another challenge would be to address the questions of ethical, technical and legal nature.
The questions as to quality, safety, governance, privacy, consent and ownership poses a greater challenge that is still under-addressed. Another concern regarding the use and designing of AI is that it would be examining why and how AI has reached to a specific decision. Right to Privacy being fundamental right demands for citizen’s health data to be protected and therefore it becomes the key responsibility of those handling the sensitive data for AI purposes.
The use of AI based solutions entails constant exchange of information between the patients and AI service provider. Such exchange creates massive datasets which are further processed for training, validation and creating algorithms.
Therefore, the lack of adequate data privacy laws in India results in commercial exploitation of the datasets leading to challenges termed as ‘Black Box Phenomena’ that is beyond development of AI solutions Owing to the violation of privacy the Ministry of Health and Family Welfare released a draft of the Healthcare Security Act. The Act proposes to provide civil and criminal remedies for any breach of data and principles of data collections and its use. The Act also provides for institution of the National Digital Health Authority as a regulatory authority which will focus exclusively on enforcing healthcare data protection norms.
Further, under the IPR regime, the Patents Act expressly exempts the patentability of algorithms from being ‘inventions’ eligible for patent protection. However, since the algorithms are created by collating and analyzing human created work, the creator of the work can be granted copyright under the Indian laws with the exclusive rights to reproduce their own work. While addressing the question of accountability, AI system has been envisaged as only a decision-support system and is thus not intended to replace the doctors. It will help in providing first layer screening interpreted by the human and he will be responsible to point out errors if any.
However, it is essential to note that in which capacity of profession this human might be, because in rural setting the frontline health workers may not have the requisite knowledge, training and confidence to be able to interpret the AI based results. These concerns are accentuated in Indian context due to weak regulation in the Indian Healthcare sector. There are numerous reports showing negligence and malpractices even in the well-established hospitals the major reason being the lack of strict and uniform regulation of healthcare in the country. There is a lack of standardized guidelines in India for designing AI applications to be used in healthcare systems which further deters the use of artificial intelligence in the Indian Healthcare market.
The existing or recently developed AI companies are majorly startups due to which the medical practitioners do not trust the products easily as they are not nationally or internationally certified. Consequentially, the sales of start-ups get hampered resulting in the limited implementation of AI in the Indian Healthcare sector.
CONCLUSION
Use of AI systems is in its developing years in the country, and thus it needs an adequate amount of legal as well as financial support from the Indian government for its better reach in the country and also to gain faith of the population in the new structure. The government will need to put extensive legal measures in order to minimize the mentioned challenges for a smooth running AI system in the Healthcare sector of the nation. It is suggested and recommended that the private players embrace self-regulation, periodically conduct systematic and structured self-audit, and document it for record-keeping and regulatory purposes. This would help not only in the structured and orderly growth of the industry, but also allow the technology and businesses to grow in a laissez affaire manner.
A key obstruction that hinders the advancement of digital health is the policy environment. Failures and misalignments coming from the absence of proper policy formulation and coordination among various stakeholders and the lack of sustainable financing basically hinder medical care associations’ capacity to earn profit from digital healthcare initiatives. In many developing countries, regulations such as those related to patient data privacy are less stringent than those of developed countries, which can act as a facilitator to the diffusion of digital health technologies. The increasing demand and complexity in the diagnostic services is outpacing the supply of healthcare experts as a result of which new set of tools is required that can handle large volumes of medical data quickly and accurately, further allowing the patient to make more objective treatment decisions based on quantitative data and tailored to the needs of the individual patient. In order to develop the new toolset, the power of AI is to be drawn upon.
Co authored by Anchal Jain.
