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Showing posts with label author: Harleen Kaur. Show all posts
Showing posts with label author: Harleen Kaur. Show all posts

Thursday, August 19, 2021

How elements of the Indian state purchase drugs

by Harleen Kaur, Ajay Shah, Siddhartha Srivastava.

There is one well known problem in India: the problem of drug quality. A significant fraction of the drugs purchased and consumed are sub-standard.

There is another well known problem in India: the difficulties of government contracting. When state organisations choose to buy instead of make, they face difficulties in the entire pipeline from bid preparation to tendering to contract disputes to contract renegotiation to payments. Weaknesses in government contracting are a cross-cutting problem that hamper the emergence of state capacity in all fields.

Research on government drug purchase thus lies at the intersection of two literatures: the drug quality literature in the field of health and the government contracting literature in the field of public administration.

Government purchase of drugs is particularly important for three reasons:

  1. The government is a large buyer of drugs, and the people would become more healthy if the quality of government-purchased drugs could go up.
  2. If procedures for drug purchase by the government are improved, this could potentially have an impact on the optimisation of an important subset of firms who may then improve their quality standards, and this would impose positive externalities upon private buyers of drugs.
  3. There are some policy pathways based on information about government testing of drugs, where the release of test data into the public domain, as a side effect of a well structured government purchase procedure, can also reshape the incentives of private firms in favour of higher quality.

A research literature on government drug purchase is required. For all researchers looking at this field, obtaining basic institutional knowledge is a bottleneck. A first building block of this is a description of how various elements of the Indian state buys drugs. This is the kind of paper that everyone wants to read but nobody wants to write. We have made a first attempt at this descriptive paper.

Tuesday, June 01, 2021

Incentive compatibility and state-level regulation in Indian drug quality

by Harleen Kaur, Shubho Roy, Ajay Shah and Siddhartha Srivastava.

The Indian pharmaceutical market is the third largest in the world by volume of drugs sold and is dominated by local players that produce branded generics at low prices. Existing government estimates suggest that 3.16% of drugs at retail pharmacies and 10.02% of the drugs at government pharmacies are not of standard quality. Independent surveys hint at higher estimates of inadequate quality. While India is a powerhouse of drugs export, foreign drug regulators routinely classify Indian origin drugs as not of standard quality. This problem has been around for a while. Reports of the Comptroller and Auditor General of India (CAG) and Parliamentary Committees have repeatedly highlighted the problems and poor regulatory capacity.

There is a need for better policy pathways to address these problems. In this article, we argue that an incentive problem inhibits the existing regulatory structure. The present law is set up in such a way, that it may be in the interest of the regulator to not carefully monitor the manufacture of pharmaceuticals. Unlike other areas where a statutory regulator is responsible for the safety of an industry, the legislative system of for the pharmaceutical sector does not create a body dedicated to ensuring that medicines are safe and up to standards. Alongside this, there are long-standing problems with regulators in India, where laws create arbitrary power, and the feedback loops of accountability mechanisms do not create a striving for improved state capacity. Certain solutions flow directly from this reasoning.

The current system

Unlike the working of the market economy in most goods and services, market discipline through consumers in the field of pharmaceuticals is limited; there is market failure caused by asymmetric problem. The user (usually the patient) does not have the skills or experience to know if a pill actually contains the claimed active ingredient. When (say) a pen does not work, this is evident to a consumer. However, it is very difficult for an individual patient or even a doctor to know if a drug is substandard. When medication fails to cure the patient, this could be because of three different possibilities -- a wrong diagnosis, or the patient just did not respond to the correct drug, or a problem with drug quality. This induces an identification problem, so there is no feedback loop when a substandard drug is purchased. Similarly, when a patient does get better, a lot of the time, this would have happened through the working of the human body and is helped by a placebo effect. Here also, there are no feedback loops based on quality signals.

The consequences of inadequate quality can be grave: substandard medication can even cause the death of a patient. And even if a patient dies, it is extremely difficult to establish (after the fact) that the medication was defective.

As with most other countries, India has a law that creates a government apparatus for approval and manufacture of medicines in the country: the Drugs and Cosmetics Act, 1940 (DC Act). This divides the functions of regulation between the union government and state governments. The union government is responsible for the approval of new drugs, regulation of drug imports, and laying down standards for drugs, cosmetics, diagnostics and devices. State governments are responsible for licensing and monitoring manufacturers for drug quality and initiating legal action against offenders.

The parliamentary law does not separate the regulatory duties between the union and state governments. The primary legislation allows the union government to appoint licensing authorities (S. 33 of the Act). Under this authority, the union government has delegated licensing functions to state governments (Rule 59 under the Act).

What was the text of the law which generated this separation? Section 33 of the legislation empowers the union government to appoint the 'licensing authority' for the manufacturing and sale of drugs and the union government has used this power to anoint the state government using subordinate legislation (See rule 59 of the DC Rules). As a result of this delegation, State governments (through their State Drug Regulatory Agencies) are responsible for licensing pharmaceutical manufacturing facilities and inspecting them.

Misplaced incentives under the law

The present arrangement of delegating inspection of manufacturing facilities to the state government, however, has problematic implications. In a unified national market, where goods flow across state borders seamlessly, pharmaceutical manufacturing factories do not limit their sales to one state. Many firms are harnessing the economies of scale that come from producing for the entire country or even the global market from a few very large manufacturing plants. Small states like Himachal Pradesh and Goa contribute disproportionately to India's total pharmaceutical production.

This unification of markets creates a problem of incentives for the state governments where these plants are located. These states benefit from the tax revenue, jobs and licensing fees that these large plants bring to the state. If the state government is vigilant and runs a tight inspection regime, it risks discouraging pharmaceutical companies from setting up plants in their state. Companies may engage in jurisdiction-shopping, taking the tax base and manufacturing jobs to states with a lax regulatory regime. On the other hand the welfare costs associated with a poor regime -- the adverse impacts on the health of users -- is not borne by the state exclusively, but by the entire country. If the state has a small population (e.g. Goa or Himachal Pradesh) and the medicine is not commonly used, the failure of the regulatory regime may be invisible to the voters of the state. Therefore, it is not in the interest of a state government to run an efficient inspection regime.

Another dimension in the incentive problems of state governments lies in the cost and complexity of regulation. State governments are being asked to spend on manpower, testing facilities and institutional capacity for regulation, while the benefits of regulation are enjoyed by customers all over India.

This incentive problem leads to a race to the bottom with states competing on laxity of regulation. As an example, while a single database for providing information about substandard drugs to the public exists, only five state regulators provide such information through this database.

Finally, even if a drug manufactured in one state is found to be substandard by a regulatory agency in another state, it is difficult to organise enforcement actions that cut across state borders.

Additionally, the separation of roles between state and union is not clear and leads to confusion about who is actually responsible for inspecting manufacturing facilities. For instance, under the DC Act, drug inspectors are responsible for inspecting manufacturing sites and detecting substandard medicines (Sections 22, 23). However drug inspectors can be appointed by both the central and state governments (Section 21), and function under the control/directions of an officer appointed by the relevant government (Rule 50).

Crucially, the DC Act and Rules do not clarify the instances in which the drug inspectors are to be appointed by the central government and when they are to be appointed by the state government. Neither do they outline a scheme of accountability wherein the quality enforcement actions of the drug inspectors can be scrutinised or audited by either a state or central body.

This results in a quality enforcement framework where there is no clear statutory body responsible for the failure in drug quality at the central or state level and therefore no incentive for individual drug inspectors to investigate and prosecute quality violations adequately. Both levels of the governments may consider the other responsible for the failure to inspect a facility.

Solutions proposed in the prevailing literature

There are broadly two schools of thought on how to reform the problem of drug quality in India. The first set of arguments favour the creation of a new central regulatory authority (Pharmaceutical Enquiry Committee (1954), Drug Policy (1994), Mashelkar Committee Report (2003)). The second set of arguments suggest that the existing State Drug Regulatory Authorities (SDRAs) be strengthened for better implementation of drug quality regulation (Hathi Committee Report (1975), Department-related Parliamentary Standing Committee on Health and Family Welfare 59th Report on the Functioning of CDSCO (2012)).

Does the solution to the problems of drug quality in India lie in building a single agency at the union government and giving it high powers to investigate and punish? In thinking about the federal architecture of the Republic, there is merit in the separation envisaged in the 1940 Act. It is difficult for the union government to build an operational capability in any field, which is effective all across the country. The Constitution of India is imbued with federalism: India is not a unitary country ruled from New Delhi, but a union of states. The Constitution envisages a limited role for the union government: the establishment of standards for quality of goods to be transported from one State to another (See Entry 51 of List I of Schedule 7 of the Constitution).

Multiple legislative attempts have been made so far to create a centralised drug authority along the lines of these recommendations but without much success. In all these instances, the bills have been opposed by state manufacturers associations and state drug regulators. But going beyond these political economy constraints, there are concerns about this pathway to policy design. Simplistic centralisation, drawing on the existing text of the DC Act, will be problematic both on the grounds that decentralisation is a valuable approach and on the grounds that the present Act has flaws on incentive compatibility. The proposals for reform have not analyzed the incentive problems and ambiguity created by the 1940 legislation. The regulatory framework for pharmaceuticals in India suffers from multiple failures which need to be addressed, over and beyond the question of decentralisation. For example, you can check the inspection dates and reports of all drug manufacturing plants in the U.S (here), but we do not know when Indian manufacturing plants are inspected. There is no obligation on either the state or union governments to regularly inspect manufacturing plants, and the DC Act is the site where such obligations need to be imposed upon state agencies.

One possibility lies in reversing the focus of state-level agencies from factories to consumers of their state. E.g. if a factory makes drugs in Goa which are sold in Maharashtra, their quality characteristics would be the responsibility of the Maharashtra drugs regulator. Such a drugs regulator would achieve greater alignment with the interests of consumers in Maharashtra, and have a reduced conflict of interest with jobs and prosperity. However, there are difficulties in establishing the powers of the Maharashtra drugs regulator over a factory in Goa. There are also dangers of creating barriers to inter-state commerce.

How to reshape incentives

Better working of regulators. An extensive body of knowledge has developed in India, in the last decade, on the working of regulators and regulation. This literature has argued that the path to high state capacity in regulation lies in: Clarity of purpose, the role/composition/working of the board, formal processes for legislative/executive/judicial functions which are written into the law, reporting and accountability mechanisms, the budget process, and low powers of investigation and punishment (FSLRC 2015, Roy et. al. 2019, Kelkar and Shah 2019). This knowledge needs to be brought into a deeper transformation of the DC Act.

Transparency reforms that reshape incentives. A low cost intervention could be based on reputation costs and can usefully be placed at the level of the union government. There are multiple channels through which drug testing is taking place in India today. Whenever a drug is found to be substandard, the union government should obtain this information and upload that information to a publicly available repository along with the name of the manufacturer and the state in which it was manufactured. This will impose a cost on states which are lax on inspecting manufacturing facilities. The public will come to associate drugs from that state to be of poor quality and avoid them. Pharmaceutical firms will then face a market based penalty if they locate manufacturing facilities in states with lax regulatory regimes. On the other hand, states which set up good regulatory regimes will benefit from the positive publicity. Pharmaceutical manufacturers would gain respectability and may even command a price premium by locating their manufacturing facilities in states with a reputation for high inspection standards. Consequently, such states would gain from licensing fees, revenue, and jobs by establishing a good regulatory regime. Therefore, with a modest work program at the union government, naming and shaming bad actors and their state level regulators, we can reverse the incentive problem and create a virtuous cycle instead of the present race to the bottom.

Greater transparency would also kick off market discipline. Households would become more aware of quality characteristics associated with the brand names of various drugs and that would kick off greater pricing power in the hands of higher quality drugs. This process would, however, be curtailed by the extant system of price controls for drugs.

Conclusion

The current regulatory framework does not adequately define the objective, functions or powers of the de-facto regulators, the CDSCO and the SDRAs in the primary law or rules thereunder. This leads to creation of unaccountable regulators that have misaligned incentives. In this article, we have shown elements of a drug regulatory regime that are consistent with the federal vision of the Republic, and can effectively reshape the incentives of state level regulators. The union should be responsible for national public goods : drug quality standards, cGMP standards, randomised testing on a national scale, and release of this testing data. The laws that create state level regulators need to draw on modern Indian thinking about how regulators should be constructed. Put together, these reforms will modify the incentives of state level regulators. 

References and further reading

Arrow, 1963: Kenneth J. Arrow, Uncertainty and the welfare economics of medical care The American Economic Review, December 1963.

National Drug Survey Report, 2016: Ministry of Health and Family Welfare, Survey of extent of problems of spurious and not of standard quality drugs in the Country, 2014-16, Ministry of Health and Family Welfare.

Government of India, 2012: Department-related parliamentary standing committee on health and family welfare, 59th report on the functioning of the Central Drugs Standard Control Organisation (CDSCO) Rajya Sabha Secretariat, May 2012.

CAG, 2007 Report No. 20 of 2007 for the perriod ended March 2006 - Performance audit of Procurement of medicines and medical equipment Comptroller and Auditor General, 2007.

Khan et al. 2016: AN Khan, RK Khar and Malairaman Udayabanu, Quality and affordability of amoxicillin generic products: A patient concern Indian Journal of Pharmacy and Pharmaceutical Sciences, 2016.

Stanton et al, 2014: Cynthia Stanton et al, Accessibility and potency of uterotonic drugs purchased by simulated clients in four districts in India BMC Pregnancy and Childbirth, 2014.

Thakur and Reddy, 2016: Dinesh S. Thakur and Prashant Reddy T, A report on fixing India's broken drug regulatory framework Spicy-IP, June 2016.

Singh et al, 2020: Prachi Singh, Shamika Ravi and David Dam, Medicines in India: Accessibility, Affordability and Quality Brookings India, March 2020.

Krishnan, 2020: KP Krishnan, The three tiers of government in public health The Leap Blog, August 2020.

MoHFW, 2017: Ministry of Health and Family Welfare, Department of Health and Family Welfare, Notification G.S.R. 1337(E), CDSCO, Oct 2017.

Drugs Enquiry Committee, 1930-31: Government of India, Report of the Drugs Enquiry Committee, 1930-31.

Pharmaceutical Enquiry Committee, 1954: Ministry of Commerce and Industry, Report of the pharmaceutical enquiry committee,1954.

Hathi Committee, 1975: Ministry of Petroleum and Chemicals, Report of the Committee on Drugs and Pharmaceutical Industry, 1975.

Drug Policy, 1986: Government of India, Measures for Rationalisation, Quality Control and Growth of Drugs and; Pharmaceutical Industry In India, 1986.

Drug Policy, 1994: Government of India, Modification in Drug Policy, 1986, 1994.

FSLRC, Indian Financial Code, version 1.1, Ministry of Finance, 2015.

Vijay Kelkar and Ajay Shah, In Service of the Republic: The art and science of economic policy, Penguin Allen Lane, 2019.

Mashelkar Committee, 2003: Ministry of Health and Family Welfare, Report of the expert committee on a comprehensive examination of drug regulatory issues, including the problem of spurious drugs, 2003.

Shubho Roy, Ajay Shah, B. N. Srikrishna and Somasekhar Sundaresan, Building State capacity for regulation in India in "Regulation in India: Design, Capacity, Performance" edited by Devesh Kapur and Madhav Khosla. Oxford: Hart Publishing, April 2019.

Task force under the Chairmanship of Dr. Pronab Sen, 2005: Government of India, Task Force to Explore Options other than Price Control for Achieving the Objective of Making Available Life-saving Drugs at Reasonable Prices, 2005.

Jeffery and Santhosh M.R., 2009: Roger Jeffery and Santhosh M.R., Architecture of Drug Regulation in India - What are the Barriers to Regulatory Reform?, 2009.

 

The authors acknowledge the support of Thakur Foundation in this work, and valuable conversations with Dinesh Thakur and Prashant Reddy. All errors are ours.

Sunday, July 12, 2020

Response to the Consultation Whitepaper on 'Strategy for National Open Digital Ecosystems (NODEs)'

by Rishab Bailey, Harleen Kaur, Faiza Rahman, and Renuka Sane.

The Ministry of Electronics and IT, Government of India (MeitY) had sought public comments on a Consultation Whitepaper (CW) titled a "Strategy for National Open Digital Ecosystems (NODEs)" earlier this year. NODEs are defined as:

open and secure delivery platforms, anchored by transparent governance mechanisms, which enable a community of partners to unlock solutions and thereby transform social outcomes.

The NODES framework will allow the opening up, and sharing of personal and non-personal data held in various sectors (such as healthcare, agriculture, and skills development). Each NODE will consist of infrastructure developed and operated by the government. The private sector will utilise the common infrastructure and data to provide solutions to the public. Per the CW, this will enable greater intra-government and public-private coordination and create efficiency gains. This framework will promote access to innovative e-governance and other services for citizens while enabling robust governance processes to be implemented.

We wrote a detailed response to MeitY. In our submission, we make suggestions on four key issues with the CW:

  • Role of the state: The CW needs to demonstrate clarity on the need for government intervention on the scale proposed. The market failures that require State intervention must be identified on a sectoral basis.
  • Centralisation of governance and technical systems: The CW envisages establishing monolithic, stack-based digital systems in a variety of sectors. The government would be responsible for establishing and operating the technology infrastructure as well as the governance of such systems. However, excessive centralisation can reduce competition, innovation, and produce unsecure systems.
  • Alignment with the existing government policies: The CW needs to consider existing government policies on the adoption of open source software (OSS), open APIs and open standards. Further, the CW needs to account for existing open data and e-governance related initiatives in the identified sectors, and how these would interact with the NODEs framework.
  • Preserving and protecting Constitutional norms: The CW needs to ensure the protection of fundamental rights, democratic accountability, and transparency in the creation and regulation of NODEs. Further, it also needs to account for the federal division of competencies enshrined in the Constitution.

This article summarises our comments and suggestions on the above mentioned issues.

Role of the State

The CW adopts a 'solutionist' approach, in that it does not undertake sufficient analysis of the circumstances and problems in each sector. For instance, the CW identifies two market failure in the skills sector: (i) information asymmetry amongst the stakeholders, and (ii) a lack of trust in the information that is available. It proposes a Talent (Skilling and Job) NODE as a one-stop solution to connect employers, job seekers, counsellors and skilling institutes. Instead of the approach undertaken by the CW, one should consider if private entities can or are already innovating to bridge the information asymmetry and trust issues in the sector, and what policies could provide an environment where such information asymmetry may be reduced. If the problem in the skills sector is a lack of trust, it is unclear why this cannot be solved by interventions such as certification standards.

As a general rule, the State should be involved with building technological systems only for essential state activities (Kelkar and Shah, 2019). It is therefore critical to differentiate between sectors where the State has a legitimate role (say in the provision of its welfare and statutory functions), from sectors where private sector solutions could suffice. For example, the State could have a role in providing access to Public Distribution System (PDS), but need not be a player in building a platform for access to rail reservations.

The responsible ministry should analyse if the NODE is serving welfare or other essential function of government. In case there is no such element, the government should not use its finances on creating infrastructure for such a NODE. Such an approach would promote innovation, prevent the emergence of a state-centric technological mono-culture, and allow the private sector to respond appropriately to requirements of any particular sector. Entities would not be forced to build on top of state-mandated infrastructure, which may not always be necessary or appropriate.

In the context of the NODEs framework, the State should primarily have three roles:

  1. Open up data: The government must focus on building databases and providing access to the public, in a non-discriminatory manner. The benefits of enabling free flows of information are well known. That said, it is important to keep in mind the need to ensure non-discriminatory access to ensure data quality, and to prevent against privacy and other downstream harms. For instance, the Delhi government recently shared locations for COVID-19 relief centers on Google maps, thereby giving Google a competitive edge over other mapping solutions. We believe that an appropriate approach would involve the Delhi government making the relevant information open. This can be done by providing the geo-tagged locations on its open data governance website. Methods to embed this data in third-party apps and services could be provided to enable non-discriminatory access. Similarly, the benefits of opening up railways related data, which is currently monopolised by the IRCTC can enable the provision of customised travel solutions. Greater linkages could be formed with private players in the hospitality and tourism sectors, leading to mutual benefits to the railways as well as the private sector and consumers.
  2. Implement regulatory frameworks: The government should institute regulatory processes and norms based on the need to protect and promote fundamental rights and correct market failures. Interventions must be designed to (a) promote effective competition and the maintenance of a level playing field, (b) avoid function creep, (c) protect and promote fundamental rights, (d) ensure appropriate apportioning of functions, obligations and responsibilities/liabilities.
  3. Ensure democratic accountability: It is now well-established that "code is law" (Lessig, 1999). This makes it imperative for the government to establish systems of democratic accountability, transparency and openness in the creation and regulation of public digital systems. Transparency and accountability measures should be implemented both at the conceptualisation stage as well as thereafter. This should involve:
    • An open and transparent consultation process in the design of the NODEs, similar to the the Report of the Financial Sector Legislative Reforms Commission recommendations for regulation making.

    • A cost-benefit analysis that takes into account the economic costs and benefits of operationalising a NODE within a sector. This would also allow for suitable alternative approaches to be explored.

    • Integration of principles of participatory and democratic governance into the implementation and operation phases. This would promote citizen-centric governance, particularly in the context of privatisation of regulatory functions. For example, the National Payments Corporation of India (NPCI) functions as a quasi-regulatory agency due to the scope of its powers, functions, and de-facto regulatory monopoly. However, being a private entity, it has not been brought under the purview of the Right to Information Act, 2005. This limits citizen engagement with governance processes.

    • Mechanisms to enable allocation of responsibilities and coordination between government entities at different levels (local, state, and central). This is especially important when dealing with common issues (such as tagging of data sets, instituting grievance redress mechanisms, etc.) without usurping constitutional and statutory functions.

Centralisation of governance and technical systems

Enabling the government to pick technological winners and losers or enabling a technical monoculture would decrease innovation and competition. It is well-recognised that centralisation can lead to increased security concerns. One must also be wary of unintended consequences of even the best planned regulation in the technology space. Technology moves too fast and has multiple possible future use cases. Over-regulation or excessive centralisation could have negative effects on expected outcomes.

In cases where the government is required to create digital systems, these must be federated and decentralised to the extent possible. The creation of monolithic technical architectures, which are often de facto mandatory, must be avoided. For instance, the creation of a centralised identification system -Aadhaar- which was thereafter mandated for use across different sectors has caused various problems ranging from exclusions, intrusions into privacy rights of citizens and inhibiting innovation (i.e. such a system is preferred over other possible forms of identification that could suffice in any particular use-case). Implementing a centralised system of 'public infrastructure' may therefore not be necessary and may in fact reduce competition and civil liberties protections.

Instead, the focus of the government should be on enabling the private sector to develop relevant platforms and technologies that compete with one another on a level playing field, albeit with due consideration for regulatory, human rights and other problems that may arise in any given context. Such a system would also promote greater security. The use of federated databases, enabling the development of alternative technical solutions to be built on data, etc., would mean that problems associated with having a single source of truth or a single source of failure can be avoided.

Alignment with existing government policies

The CW proposes principles of open and interoperable delivery platforms. There are two concerns in the manner in which these are described in the CW.

  1. The CW does not refer to existing government policies on the use of OSS in e-Governance projects. Various policies specifically deal with the issue at hand (for example, National Policy on IT, 2012, the policy on Adoption of Open Source Software for Government of India, and the policy on Open Standards for e-Governance).

  2. The scope of the word 'open' as used in the CW is vague and appears to confuse concepts of "open access" and "open source". The CW suggests that each NODE will require a different degree of openness to adhere to specific objectives, context, or mitigate potential risks. This approach can dilute existing policies (mentioned above) that contain clear definitions and mandates on the use of open source solutions by the government.

It is imperative that the NODEs framework build on and strengthen existing government commitments towards the use of OSS solutions. This will unlock the benefits of OSS/Open APIs/open standards such as enhanced security and verifiability, no vendor lock-in, etc.

Preserving and promoting constitutional safeguards

The creation of NODEs platforms would significantly impact fundamental rights. We envisage three instances where the NODES environment needs to be careful about preserving constitutional safeguards.

  1. Right to equality, right to life, and personal liberty: Digitisation at the scale contemplated by the CW may lead to concerns about access to services and possible exclusions therefrom. Ensuring rights protection may be particularly important in the context of the use of AI-based solutions and possible discrimination that may arise as a result. The understanding of what amounts to discrimination must be evolved by each NODE distinctly and will depend on the sector.

  2. Right to privacy: Each of the NODEs will invariably result in the collection and processing of personal data and non-personal data by both government and private entities. The collection and use of personal data by different state entities must necessarily satisfy the tests laid down by the Supreme Court in the Puttaswamy decisions (2017 and 2018). Similarly, principles relating to the use of data by the private sector as laid down in the context of the Aadhaar judgment (Puttaswamy, 2018) must also be adhered to. Due regard must also be given to (the developing) regulatory frameworks concerning personal and non-personal data.

  3. Federal structure: The NODEs framework must also consider the impact on the division of subject matter competencies under the Constitution. One could envisage benefits arising from NODEs in areas such as agriculture, judicial services, healthcare, etc. However, these sectors fall under the State List in the Seventh Schedule to the Constitution. Implementation of NODEs in these sectors should not result in de facto centralisation of federated competencies. Instead, mechanisms to ensure coordination and cooperation between different levels of government must be considered.

We, therefore, recommend that each NODE be backed by an appropriate statute, to the extent possible. This would ensure greater democratic deliberations, prevent excessive and arbitrary executive action, set out the rights of citizens and private entities, and clarify the scope/ limits of any particular project. Providing statutory backing would also limit mission creep, while delineating rights and obligations and governance processes. For instance, despite its various faults, the statutory mandate provided to the Unique Identification Authority of India and the restrictions on data sharing in the Aadhaar Act have proven invaluable in ensuring that biometric and other data is not made freely available for non-Aadhaar purposes by the public sector, including for instance, in criminal investigations. In contrast, projects such as FASTags (which aims to digitise highway toll systems) are being gradually expanded with plans to integrate the system with criminal tracking networks, amongst others.

Conclusion

The CW provides a basic overview of the concept of a NODE and identifies certain sectors in which such a system could lead to gains (such as the skills and health sectors). For various reasons outlined in our submission, our recommendation is to not proceed with implementing the NODEs framework in the manner currently outlined in the CW. We believe that the CW should be seen as an exploratory document. Greater clarity is required on the need for interventions on the scale envisaged in the document, particularly in view of the proposed centralised, stack-based approach. The NODEs framework should consider the need for openness at lower layers of the stack (infrastructural layers), adhere to existing government policies on the use of OSS, Open APIs and Open Standards, and consider policy developments concerning the regulation of personal and non-personal data. The CW should also ensure greater transparency and democratic accountability of governance frameworks and the processes for the creation of a NODE.

References

Bailey et al, 2020: Rishab Bailey, Vrinda Bhandari, Smriti Parsheera and Faiza Rahman, Comments on the draft Personal Data Protection Bill, 2019: Part I, LEAP blog, 2020.

Centre for Digital Built Britain, 2018: A Bolton, M Enzer, J Schooling et al, The Gemini Principles: Guiding values for the national digital twin and information management framework, Centre for Digital Built Britain and Digital Framework Task Group, 2018.

FICCI & KPMG, 2014: FICCI and KPMG, Skilling India: A look back at the progress, challenges and the way forward, 2014.

Kelkar and Shah, 2019: Vijay Kelkar and Ajay Shah, In service of the republic: The art and science of economic policy, Penguin Allen Lane, 2019.

Lessig, 1999: Lawrence Lessig, Code and other laws of cyberspace, Basic Books, 1999.

Puttaswamy, 2018: Justice K.S. Puttaswamy v. Union of India (Aadhaar case), 2019 (1) SCC 1.

Leblanc, 2020: David Leblanc, E-participation: A quick overview of recent qualitative trends, DESA Working Paper No. 163, United Nations Department of Economic and Social Affairs, 2020.

Michealson, 2017: Rosa Michealson, Is Agile the answer? The case of UK universal credit, in Grand Successes and Failures in IT - Public and Private Sector, IFIP Advances in Information and Communication Technology, Springer, 2017.

Ministry of Rural Development, 2013:Ajeevika skills guidelines, Ministry of Rural Development, Government of India, 2013.

Puttaswamy, 2017: Justice K.S. Puttaswamy v. Union of India (Right to privacy case), 2017 (10) SCC 1.

Raghavan and Singh, 2020: Malavika Raghavan and Anubhutie Singh, Building safe consumer data infrastructure in India: Account aggregators in the financial sector - Part I, Dvara Research, 2020.

Steinberg and Castro, 2017: Michael Steinberg and Daniel Castro, The state of open data portals in Latin America, Centre for Data Innovation, 2017.

Zambrano, Lohanto and Cedac, 2009: Raul Zambrano, Ken Lohanto and Pauline Cedac, E-governance and citizen participation in West Africa: Challenges and opportunities, The Panos Institute, West Africa and the United Nations Development Programme, 2009.


The authors are researchers at NIPFP.

Friday, July 03, 2020

Legal and regulatory framework for laboratory testing in India: A case study for Covid-19

By Harleen Kaur, Ameya Paleja, and Siddhartha Srivastava.

Testing is central to understanding the spread of the SARS-CoV-2 virus at an individual & population level and designing suitable interventions (Shah, 2020). As of June 23, 2020, India has the fourth-largest number of SARS-CoV-2 cases worldwide. This is despite having conducted only 119 tests per million people. In comparison, the United States and Russia, countries with more cases than India have conducted 1518 and 2074 tests per million respectively. While India has somewhat improved its testing rate since the early stages of the SARS-CoV-2 pandemic (21 per million on April 24), we are still unable to test in adequate numbers. In this blog, we study the reasons behind insufficient testing rates in India by reviewing the legal environment for regulating medical testing.

The Indian diagnostics industry is dominated by the private sector. The legal framework for regulation of private labs is set up under the Clinical Establishments Act, 2010. The issues of non-standardisation of service quality and supplier-induced demands are prevalent in the industry (Competition Commission of India, 2018). Therefore, these labs have been functioning under market-led and self-imposed norms. The government did not depend on this regulatory framework during the SARS-CoV-2 pandemic. Instead, it granted unchecked discretionary power to the Indian Council of Medical Research (ICMR) to regulate the testing strategy. Under the regulatory framework set up by the ICMR, the private lab network is not being utilised optimally for SARS-CoV-2 testing. For instance, the private sector accounts for about 70% of the health care market in India. As of June 22, 2020, only 27% of all labs approved for SARS-CoV-2 testing in India are private labs. In this article, we argue that; i) the private labs are governed by a weak regulatory framework that has allowed market failure to persist in the diagnostics sector in India, and ii) the testing strategy mandated by the ICMR for SARS-CoV-2 pandemic has led to poor outcomes with respect to the participation of private labs. Hence, there is an immediate requirement for reviewing the powers of ICMR for managing the testing strategy and a long term requirement for rethinking the present regulatory framework for labs.

Concerns about market failure in the field of medical testing

A market failure occurs when the free market is unable to obtain efficient economic outcomes. Of the four types of market failures, viz; externalities, asymmetric information, market power, and public goods, the diagnostics sector in India is seen to be affected primarily by information asymmetry. Information asymmetry or information inequality occurs when one party such as a physician possesses much greater information than the other, a patient (Arrow, 1963). During a pandemic, testing becomes a crucial part of a nation's public health strategy and hence, the public goods element of market failure also comes into play. For instance, testing data is a public good in as much as it is useful to understand the spread of the disease in an area that helps the government to design public health policies, and sharing of such data by the government affects behavioral changes in individuals.

As a result of information asymmetry, the field of medical testing in India faces the recurring issue of quality control and standardisation of services. For instance, practices such as hiring unqualified professionals, using sub-standard equipment, and proxy digital signatures have become prevalent in the industry in the absence of effective regulation. In extreme cases, there have been instances of private labs disbursing 300-400 diagnostic reports within a matter of hours, often without conducting any testing at all.

The free market does not solve the issues of market failure on its own and requires state intervention. This can be done through effective regulation of the market either by itself or through State coercion. We now study the existing regulatory framework for labs in India and its limitations.

Regulation of diagnostic labs

Health care is a state subject under the Indian Constitution. This means that in the usual course of events, states have exclusive powers to make laws concerning different aspects of health care such as diagnostic laboratories. Article 249 of the Constitution provides exceptional powers to the union government to make laws on state subjects in the national interest. For such matters, the states retain the power to accept or reject the union law. The Clinical Establishment Act has been passed by the union government under this provision and 11 states have enacted it as of now. However, there are two difficulties with the law which have created a gap between aspiration and outcome. First, under our constitutional arrangement the Clinical Establishments Act is only applicable to those states that choose to adopt it, and only 11 states have adopted this law. Second, the law has serious difficulties in design and implementation.

In the 11 states where the Act is present and implemented, the regulatory function is limited to granting registration to labs and maintaining a register of clinical establishments. The labs interact with the regulatory authority only at the time of registration when they submit evidence of having complied with the prescribed standards for registration to the regulatory authority. Once a permanent registration is granted, there is no mechanism to review the functioning of the labs or provide grievance redressal to patients under the Act. If a person starts a lab without registration, the maximum punishment under the law is a monetary penalty of rupees five lakhs.

Other than the Clinical Establishments Act, private labs have to comply with the standard regulatory requirements under the state Shops and Establishments Act (relating to hours of work, cleanliness, holidays, etc.) and obtain registration under the provisions of the Biomedical Waste Management Rules, 2016. Additionally, diagnostic kits and reagents used by labs are defined as 'drugs' under the Drugs and Cosmetics Act, 1940, and therefore have to be approved by the Central Drugs Standard Control Organisation (CDSCO).

We see that there is effectively no legal framework for regulating private labs in India. The labs only comply with allied regulatory requirements such as disposal requirements for biomedical waste and approval of diagnostic kits under the Drugs and Cosmetics Act. Given this regime, two mechanisms namely accreditation and public procurement have sought to fill the regulatory void in the diagnostics industry.

Alternative methods of regulation

In the absence of an overarching law that assures the quality of clinical establishments, private labs have turned to voluntary accreditation for establishing credibility in the vast diagnostics market. Accreditation of labs is not mandatory in India. The National Accreditation Board for Testing and Calibration Laboratories (NABL), an autonomous body under the Quality Council of India, prescribes accreditation criteria for various kinds of labs. Of the estimated 100,000-110,000 labs present in India, around 4000 have NABL accreditation. Some labs prefer obtaining certifications from international accreditation bodies in addition to obtaining NABL accreditation. Accreditation helps in assuring the quality of labs to the public as well as the government.

The second method to ensure quality standards and avoid market failure is public procurement. The government has dealt with the absence of a regulatory framework in the past by using contractual mandates to avail the services of private labs. The standards expected from these labs are contractually specified by the government while entering into public-private partnership (PPP) agreements for diagnostics. For instance, the union government under the National Health Mission (NHM) has a Free Diagnostics Services Initiative which contains detailed requirements from diagnostic/pathology labs. NABL accreditation is one of the common requirements for private labs to participate in such government programmes.

To compensate for weak regulation under the Clinical Establishments Act, voluntary accreditation by the NABL and public procurement through PPP agreements have acted as alternative strategies for regulation. These alternatives help in reducing information asymmetry and assuring the quality of services to the public and could have played an important part in the regulation of the labs for SARS-CoV-2. Yet, we find that the government strategy for medical labs for SARS-CoV-2 is based on a command-and-control approach under ICMR.

Regulation of medical labs for SARS-CoV-2

Under the existing regulatory framework, private labs did not have to follow any criteria or adhere to any standards before starting a new/novel test, such as the SARS-CoV-2 test. This means that patients would have been able to get SARS-CoV-2 tests done in any private lab offering the test using reagents/test kits approved by the CDSCO and having a valid bio-waste and other local licenses.

The lack of a regulatory framework led to confusion regarding the role of private labs in the response to the SARS-CoV-2 pandemic. As a result, the government set up an emergency regulatory framework for the SARS-CoV-2 crisis using provisions of the Epidemic Diseases Act, 1987, and the Disaster Management Act, 2005. Using these laws, it appointed the Indian Council of Medical Research (ICMR) as the apex decision-making body for India's diagnostic testing strategy through the MoHFW (see notifications here and here).

The Epidemics Act authorises the state governments to take exceptional measures and prescribe regulations to contain the spread of a dangerous epidemic disease. It lists a set of basic subjects for which regulations may be made such as travel restrictions, examination and quarantine of suspected cases, and inspections of any ship or vessel leaving or arriving at any port of call. The role of the union government under this law is limited to managing epidemic diseases at ports.

The Disaster Management Act contains an administrative framework for disaster management. Section 6 of the Act sets up the National Disaster Management Authority (NDMA) as a nodal body for disaster management. Any directions issued by the NDMA and the union government must be followed by the Union Ministries, State Governments and State Disaster Management Authorities. The SARS-CoV-2 pandemic has been notified as a disaster under this Act. Under this, the government has passed various directives on different aspects of the SARS-CoV-2 response using the umbrella clauses of this legislation such as section 6(2)(i) (The NDMA may lay down the policies, plans and guidelines for disaster management) and Section 10(2)(l) (The National Executive Committee may lay down guidelines or give directions to union ministries, state governments and state authorities for responding to the disaster) have been invoked to respond to the SARS-CoV-2 crisis.

Using the powers granted to it by the government, the ICMR has placed severe restrictions on private labs to test for SARS-CoV-2. These restrictions include requiring approvals from ICMR for lab facilities, commercial testing kits, and cost-capping for testing. We now study the ICMR decisions on testing strategy in detail to understand its role in the testing outcomes for SARS-CoV-2.

The role of the ICMR

The ICMR has been responsible for the regulation of public labs under a 2012 scheme called the Viral Research and Diagnostic Laboratories (VRDL) network under the MoHFW. The scheme was initiated to increase government capacity for the timely detection of emerging/re-emerging viral diseases. The VRDL labs were exclusively responsible for testing in the initial phase of the SARS-CoV-2 pandemic in India.

The initial advisories issued by the ICMR contained no mention of private labs and focused only on directing public labs to undertake SARS-CoV-2 testing. At the time, some state governments explicitly banned private labs from testing as per their regulations issued under section 2 of the Epidemic Diseases Act, 1897. For instance, the Delhi Epidemic Diseases COVID-19 Regulations, 2020 and the Bihar Epidemic Diseases COVID-19 Regulations, 2020 contain the following provision on testing of potential SARS-CoV-2 cases by private laboratories:

"No private laboratory has been authorised to take samples for COVID-19 in the State. All such samples will be collected as per the guidelines of the Government of India..."

Subsequently, the ICMR issued guidelines for private labs to undertake SARS-CoV-2 testing on March 21, 2020. Since then, the ICMR has been responsible for approving private labs to test for SARS-CoV-2. The ICMR conducts checks on the capability of private labs to test for SARS-CoV-2 and updates the list of approved private labs regularly. It also issues detailed guidelines for other aspects of testing such as procurement of reagents, evaluation of commercial testing kits, etc. In doing so, it has usurped the regulatory functions of existing statutory regulators such as the CDSCO, as well as voluntary bodies like the NABL. For instance, while diagnostic kits for SARS-CoV-2 are considered "drugs" and should be approved by the CDSCO, they also require validation by the ICMR. Similarly, NABL approved private labs are required to get a mandatory clearance from ICMR for SARS-CoV-2 testing. This means that while NABL has accredited 278 labs for RT PCR RNA testing for SARS-CoV-2, the ICMR has approved 258 of these labs for testing as of June 21, 2020. The ICMR does not document the rationale or process of performing these regulatory functions. The Epidemics Act and the Disaster Management Act do not require the ICMR to adhere to minimum standards of accountability, transparency, and public engagement. The invocation of these laws to empower the ICMR means that there is no coherent or intellectually defensible framework for reviewing the ICMR's actions during the pandemic except that the basic rule of law principles are followed by it.

Building state capacity for regulation is a gradual process that requires backing by a comprehensive legal framework (Roy et al, 2018). ICMR was abruptly thrust into a role for which it did not have the required organisational or procedural capacity. Hence, it compensated for the lack of a regulatory framework by issuing strict command and control orders. We see that after being appointed as the government regulator for the testing strategy for SARS-CoV-2, the ICMR barred all private labs from testing unless approved by it. Given that the labs are already approved by NABL, the rationale for re-approval for testing of private labs by ICMR was never shared. Additionally, ICMR started regulation of reagents, test-kits and costs of tests. This has had an adverse impact on the testing outcomes as seen below.

Implications of regulation of private labs by ICMR

ICMR has been responsible for advising on the SARS-CoV-2 testing strategy for the country. The restrictive policies by the ICMR have led to the inaccessibility of the tests for a vast population. As a result, various courts in India are being involved to challenge such policies.

In April, the Supreme court heard the issue of cost-capping of lab testing for SARS-CoV-2 by ICMR and ordered that the tests shall be free for persons falling under government schemes such as Ayushman Bharat or any other category of economically weaker section of the society as notified by the government. The ICMR cost-cap of INR 4500 per test for private labs was not examined by the court in this petition, but it emphasised on the need for affordable tests to the population.

The Delhi high court reviewed the cost fixed by ICMR for the procurement of rapid testing kits in April. It held that the costs at which ICMR procured the kits had an unduly high profit-margin for the vendors and ordered the cost per kits to be reduced from INR 600 to INR 400. Furthermore, the kits procured by ICMR were later found to be faulty. The court criticised the government and ICMR for low testing of SARS-CoV-2 cases in another order dated June 18, 2020. It ordered the government to review ICMR policies on labs such as the protocol for sample collection, approval of labs, data sharing by labs, and costs per test through an existing government committee.

The Gujarat high court is monitoring the state response to SARS-CoV-2 under a suo-motu writ petition. Under this petition, in an order dated May 29, 2020, the court modified the ICMR guidelines on testing for different categories of patients as it found the patient categories to be non-exhaustive. The court has also decided to review the rationale behind the ICMR SARS-CoV-2 testing strategy.

The ICMR has been criticised for its advisories on the evolving SARS-CoV-2 testing strategy by experts. For instance, its restrictions on the usage of RT-PCR and rapid antigen testing are seen to be unreasonable as the testing capacity has been increasing over time. Additionally, the issue of lack of transparency in sharing testing data and its regulatory procedure makes ICMR decisions difficult to understand and implement.

The ICMR policies regarding the testing strategy for SARS-CoV-2 are restrictive for private labs. This is indicative of a trust-deficit between ICMR and the labs. The ICMR regulatory strategy to reduce this trust-deficit is to micromanage every aspect of testing sought to be done by the private labs. This has led to lower participation of such labs in testing for SARS-CoV-2 and issues of unavailability of tests to the public.

Conclusion

The bulk of the health care services in India are provided by the private sector despite the presence of public health care facilities (Hooda, 2015). Recognising the growth and demand of the private sector, the policy framework in health has gradually shifted from the government providing health care services to being a financier of these services (Patnaik et. al, 2018). Recently, the Indian government conceded before the Supreme Court that the testing capacity of the public sector for SARS-CoV-2 is insufficient.

In this article, we studied the regulatory framework with respect to medical laboratories in India. We find that in the regular course of events, the Clinical Establishment Act, 2010, and the rules thereunder are responsible for such regulation. Issues with the adoption and implementation of this Act leave the sector effectively unregulated. Despite the presence of some alternative methods of regulation, the regulatory gap in the diagnostic sector persists. Therefore, there is a need for a comprehensive law to deal with the market failure of information asymmetry and public goods. However, the enactment of such a law is a long-term deliberative process and should not be attempted in the face of a pandemic.

For SARS-CoV-2 testing, the government has deviated from the existing course of minimal intervention in regulating private labs to regulating every aspect of testing through the ICMR. Government laboratories set up under the VRDL framework were initially the exclusive bodies allowed to test for SARS-CoV-2. While private labs have now been allowed to test for SARS-CoV-2, they are still heavily regulated by the ICMR. The rationale for this approach has not been provided. We believe such an approach is unsuitable for managing the SARS-CoV-2 pandemic. Using the broad powers given to it, the ICMR has reduced the capacity for testing in India by introducing prescriptive testing guidelines, licensing requirements, and cost-capping. This has resulted in non-utilisation of a bulk of the testing capacity for SARS-CoV-2 in India so far. Therefore, we suggest that the power given to the ICMR for SARS-CoV-2 regulation be minimised by specifically disallowing any duplication of regulatory functions already being performed by bodies such as CDSCO and NABL. Further, for the powers delegated to ICMR for regulating the testing strategy, due process requirements such as documenting the rationale, public consultation, sharing of public data should be mandated by the government to increase the accountability of ICMR.

References and further reading:

Arrow, 1963: Kenneth J. Arrow, Uncertainty and the welfare economics of medical care The American Economic Review, December 1963.

Nandraj, 2012: Sunil Nandraj, Unregulated and Unaccountable: Private Health Providers, Economic and Political Weekly, January, 2012.

Srinivasan, 2013: Sandhya Srinivasan, Clinical Establishments Act, 2010 Regulation and the Medical Profession, Economic and Political Weekly, 19 January, 2013.

Hooda, 2015: Shailendra Kumar Hooda, Private Sector in Health Care Delivery Market in India: Structure, Growth and Implications, Institute for Studies in Industrial Development, Working Paper 185, December, 2015.

Patnaik et. al, 2018: Ila Patnaik, Shubho Roy, and Ajay Shah, The rise of government funded health insurance in India, NIPFP Working Paper Series, No. 231, 21 May 2018.

Roy et al, 2018: Shubho Roy, Ajay Shah, B. N. Srikrishna, and Somasekhar Sundaresan, Building State capacity for regulation in India NIPFP Working Paper Series, No. 237, 3 August, 2018.

Competition Commission of India, 2018, Policy Note: Making markets work for affordable health care, Competition Commission of India, October, 2018.

Kelkar and Shah, 2019: Vijay Kelkar and Ajay Shah, In service of the Republic: The Art and Science of Economic Policy, Penguin Allen lane, December 2019.

Shah, 2020: Ajay Shah, More testing: From concept to implementation, The Leap Blog, 06 April, 2020.


Ameya Paleja is a molecular biologist and science blogger based in Hyderabad. Harleen and Siddhartha are researchers at NIPFP. The authors are thankful to Ajay Shah, Renuka Sane, Amrita Agarwal, Smriti Parsheera, Shubho Roy, Anand Prakash, Arjun Sinha, and three anonymous referees for their valuable comments.

Saturday, June 13, 2020

Information about COVID-19 in India

By Natasha Agarwal and Harleen Kaur.

The presence of timely and reliable data enables informed decision-making by government organisations and individuals. When a machine-readable dataset is released on a website, it is non-rival, and thus has characteristics of a public good. There is a case for state financing or production of information. As Carl Malamund says, "Government information is a form of infrastructure, no less important to our modern life than our roads, electrical grid or water systems". Open Data Governance (ODG) are structured datasets produced by government institutions that are released in a machine-readable format. These datasets contain information such as statistics, plans, maps, environmental data, spatial data, materials of agencies, ministries, parliamentary data, budgetary data, and laws.

Governments across the globe have been actively opening their data through national and regional data transparency portals recognising the need for making data available to the public. The process is informed by ODG principles. There are three main reasons for opening government data; increasing transparency, releasing the social and commercial value of the data, and to encourage participatory governance (Attard et al. (2015)). As an example, the COVID-19 pandemic is best controlled through behavioral changes by each individual. To support such changes, the governments need to open their data about the pandemic at an individual and community level.

The ODG principles defining best practices of data sharing include; i) identifying and publishing high-value datasets in a standardised format (such as a directory of medical professionals, tests conducted and results and information about surveillance), ii) adopting open data scheme protocol to share human and machine-readable, non-proprietary format and include universal resource identifier and linked data to provide access, iii) removing barriers to data access such as requirements of establishing an account, of proving identity, or payments for data access, and iv) making information available in perpetuity by not deleting/changing data permanently.

In this article, we examine the information systems on COVID-19 in India from the viewpoint of these issues in the design of a high performance statistical system.

Data.gov.in and its limitations

In India, an open data policy the National Data Sharing and Accessibility Policy (NDSAP) was announced in 2012 to open government data to the public by following ODG principles.

The policy requires all ministries, departments, subordinate bodies, organisations, and autonomous bodies of the Indian Government to share all publicly generated non-sensitive data in both human-readable and machine-readable formats. The data is disseminated through a common government data platform deployed and managed by the National Informatics Centre (NIC), Ministry of Communications and Information Technology. It mandated that datasets be periodically updated by government agencies along with comprehensive meta-data which enables data discovery and access through departmental portals.

Furthermore, NDSAP requires the Department of Information Technology (DIT) to publish guidelines to implement NDSAP. The implementation guidelines provide details of the data contribution process including; the role and responsibilities of the data controller, approval, publishing process for catalogs and resources, and management of published datasets.

In compliance with NDSAP, India's national data transparency website, data.gov.in was launched in 2012. Accordingly, data.gov.in provides a unified catalog of datasets allowing users to browse the dataset catalog, view the meta-data associated with each dataset, comment on and rank various datasets, download available datasets, submit suggestions and queries on the published dataset, and submit a request for those that are not available yet (Chattapadhyay (2013)).

Despite the comprehensiveness of the policy and the accompanying guidelines, agencies have responded predictably, i.e. they neither comply with NDSAP nor with the implementation guidelines. As a result, data.gov.in contains issues such as the absence of databases, duplicate datasets, lack of follow-up, or meta-data (Agarwal (2016) and Buteau et al. (2015)). The terms 'policy document' and 'guidelines' which are often used in India are ineffective in that they do not constrain the executive. Hence, these documents amount to exhortations that have little impact on the incentives of officials in favour of greater opacity, reduced work, or gaining power through the control of data.

Ministry of Health and Family Welfare (MoHFW) and COVID-19 data

We examine the data in the public domain emanating from MoHFW during the ongoing COVID-19 pandemic. To understand the availability of resources for healthcare, we searched for a directory of healthcare providers (both institutions and individuals). The latest hospital directory available on data.gov.in was for 2016 and the latest data for the number of registered allopathic doctors and dental surgeons was available for the year 2013.

The MoHFW is disseminating limited data on the spread of COVID-19 through the data.gov.in portal. For example, as of 1st June 2020, the data reported under mygov.in (not in data.gov.in) contains information on three variables namely (i) total number of persons infected with COVID-19; (ii) COVID-19 infected persons who have been cured/discharged/migrated; and (iii) COVID-19 infected persons who have died. The state-wise distribution of these three variables is available for a given date "T = Today". This data cannot be downloaded. The meta-data for this information is also not available. On the other hand, the data.gov.in only releases daily factsheets in a pdf format summarising this data.

The dissemination of COVID-19-related data by the MoHFW has problems. It gathers detailed COVID-19-related data from the National Centre for Disease Control (NCDC) (surveillance data from the field) and Indian Council of Medical Research (ICMR) (data through the testing laboratory network), which is not reflected in data.gov.in.

The NCDC, under the Integrated Disease Surveillance Project (IDSP), consists of union, state, and district-level units responsible for the surveillance of infectious diseases in India. Although it releases weekly outbreak reports notifying the status of infectious diseases in India, the reports are available only on its website and not integrated on data.gov.in. On the COVID-19 pandemic, the weekly outbreak report dated 10th-16 February, 2020 was the latest available report under IDSP as of 8 June, 2020.

Similarly, ICMR, the designated body under the National Disaster Management Act to coordinate the testing strategy for COVID-19 has been releasing its data through its website and not through data.gov.in. Through its website, ICMR releases information on two parameters, the total number of samples tested for COVID-19 over time, and in the last 24 hours.

Therefore, data.gov.in is not being utilised by the union government agencies for releasing information. Individuals and researchers interested in the government data on the pandemic have to access information available in different silos according to their skills and knowledge. Moreover, none of the information shared is available in a machine-readable or standardised format. This leads to a weak information base on Covid-19 available to the public and to researchers, which hampers the decision making of individuals on the appropriate care that they should take, and hampers policymaking by government organisations for want of data and research.

Data disseminated by state governments

The union agencies are not the only government source on COVID-19 information. We now study the data dissemination protocols for COVID-19 as followed by the states.

We could not find state data on COVID-19 on the data.gov.in website. As a result, the following information was collected through individual COVID-19 portals set up by the states. Table 1 shows that there is heterogeneity in reporting across states. The information shared by the states is classified into three categories; "state-level", "district-level" and "individual-level".

Parameters

Delhi

Kerala

Maharashtra

Gujarat

Karnataka

Madhya Pradesh

State-level data

Total COVID-19 confirmed cases

Y

Y

Y

Y

Y

Y

Active cases

Y

Y

Y

Y

Y

Y

Total COVID-19 tests conducted

N

Y

N

Y

Y

N

Hospitalisation status of positive cases

Y

Y

N

N

Only ICU patients

N

Isolated/ quarantined patients

Y

Y

N

Y

Y

N

Total recovered patients

Y

Y

Y

Y

Y

Y

Total deaths

Y

Y

Y

Y

Y

Y

District-level data

Number of people under observation

N

Y

N

N

Y

N

Number of quarantined/ isolated people

N

Y

N

N

Y

N

Individual-level data

Age

N

Y

N

N

N

N

Gender

N

N

N

N

Y

N

Comorbidity

N

Y

N

N

N

N

Table 1: State-level reporting parameters for COVID-19 (As of 9 June, 2020)

Table 1, placed above, shows the data sharing protocol for COVID-19 in selected states. We may point out a few facts that influence the interpretation of this table:

  1. Data as of 10th June, 2020. Sources: Delhi, Kerala, Maharashtra, Gujarat, Karnataka and Madhya Pradesh.

  2. Maharashtra, Gujarat, and Karnataka share information about the same parameters at the State and District level. The information depicted here is about parameters in addition to the duplicate information.

  3. In the studied states, Gujarat and Delhi inform about the number of patients on ventilators at the state level. However, the information on available hospital beds and ventilators in Delhi is shared under a separate website, https://coronabeds.jantasamvad.org/.

  4. District-level information in Kerala is available for patients hospitalised, symptomatic patients hospitalised, the chronology of positive cases, and hotspots. No other states releases data on these parameters.

  5. Karnataka is the only state which shared anonymised patient data related to their travel history, district, and location of isolation. It also has a dedicated patient case number for individual patients for whom information is shared.

  6. Madhya Pradesh had a dedicated website for individual-level data which was discontinued from 11th May 2020 onwards following the raising of privacy concerns over social media.

We find that in most states, the baseline data includes overall state data about testing rates, persons infected, deaths, and recovery data. However, some states provide additional information such as the number of COVID-19 tests conducted, the number of isolated/quarantined persons, the counts of patients on ventilators, and stable patients. While some states like Maharashtra report data at the district level along with the overall state data, others like Karnataka share information at the individual level. There is a high variation in the type of data shared by the states. For instance, at an individual level, Karnataka reports anonymised information about the demographic details in addition to the baseline data. On the other hand, Madhya Pradesh used to share the name and addresses of the suspected COVID-19 patients to the public while reporting individual-level data. Similarly, Kerala, Maharashtra, and Gujarat report their data at the district level. Kerala reports its surveillance data which is not reported by Maharashtra, and Gujarat. Some states provide daily reports in English, while others do not. For example, Gujarat provides daily reports only in Gujarati.

Most states disseminate data through their COVID-19 websites. However, some resort to reporting through social media. For example, the Maharashtra government website on COVID-19 does not provide information other than that reported in table 1. However, the Maharashtra government has been releasing daily reports providing COVID-19-related information across age, gender, comorbidities amongst other variables through Twitter. While twitter can amplify the transmission of information in a public statistical system, it should not supplant the foundational systems. Data disseminated through a tweet cannot be traced to any government website. Besides, there is inconsistency in the reports shared by the Maharashtra government through twitter. For example, the report dated 22nd April 2020 provides for district-wise distribution of COVID-19 cases in Maharashtra which is not available in the report dated 1st April 2020. The data is a "delete-tweet" away from not being available.

There is also variation in the data sharing format. Most state governments provide data in human-readable formats like pdf. However, some state governments provide some data in machine-readable formats. For example, district-wise data on variables available on dashboard for Gujarat which contains the total number of cases tested for COVID-19, positive cases, patients recovered, people under quarantine, and total deaths can be exported to a csv document. Nevertheless, demographic details of COVID-19 patients or data patients on ventilator/stable, are only available in daily reports in pdf format.

We find that the states do not share their COVID-19 data through the data.gov.in framework. Users have to look for multiple information sources about COVID-19 data to access this data. Within the framework of stand-alone websites providing information, there are two concerns. The first concern is the lack of standardised parameters for information releasing. For instance, few states share the hospitalisation status and the availability of beds which would be useful for the general public in case of emergency. The second concern is the quality of data shared by the states. As discussed, most states share human-readable data and not machine-readable, downloadable data. Meta-data is not available for any state studied making it difficult to interpret. Moreover, the lack of data standardisation makes data non-interoperable. The state-level historical information is unavailable for most states. Therefore, not all data shared by the states is permanent.

Difficulties of CoVID-19 data release seen elsewhere in the world

So far, we have documented variation in what data is being released, and how the same is disseminated, in India. This is a global concern for COVID-19. We map the data reported by selected countries in table 2 below. We find that countries are using two forms of data distribution methods. These are daily updates and dashboards. While daily updates are usually pdf documents, dashboards provide progress of COVID-19 over time. The type of information shared by countries can broadly be classified according to the level of data as "country-level" and "individual-level". Country-level data consists of aggregate information such as the total number of tests conducted, the total number of COVID-19 positive patients, the number of patient hospitalised and deaths, etc. Some countries also share aggregate surveillance data which consists of information about individuals isolated, quarantined, and contact traced. At an individual level, we see a wide variation of data shared by the countries. While India does not provide individual-level data through its Ministry of Health, other countries share demographic information such as age, gender, race/ethnicity, and occupation. A comparison of data disclosed by selected countries is shared in table 2.

Country Daily updates (DU) or Dashboard (DB) Total Number of tests conducted Total Number of COVID-19 +ve patients Total Number of patients hospitalised Total Number of deaths Surveillance data Individual level data
Age Gender Race/ Ethnicity Occupa-tion

India

DU and DB

Y

Y

N

Y

N

N

N

N

N

USA

DU and DB

Y

Y

N

Y

Y

Y

N

Y

N

UK

DU and DB

Y

Y

N

Y

N

Y

Y

Y

Y

South Korea

DU and DB

Y

Y

N

Y

Y

Y

N

N

N

Singapore

DU and DB

Y

Y

Y

Y

Y

N

N

N

N

Canada

DB

Y

Y

Y

Y

Y

Y

Y

N

N

Australia

DU and DB

Y

Y

Y

Y

Y

Y

Y

N

N
Table 2: Country-level data parameters for COVID-19 (As of 10 May, 2020)

It can be seen from the above table that most countries report testing data (information about the number of tests conducted), and the number of positive cases and deaths. At the national level, India only reports these minimum consistent variables. Some countries report more variables to the public. For instance, the US, South Korea, Singapore, Canada, and Australia report surveillance data in varying details. A few countries like Canada share their database in a downloadable format. This includes information about quarantined and isolated individuals and details about contact tracing and source of infection. Singapore, Canada, and Australia also report data on the number of cases hospitalised. The UK has recently started reporting information about COVID-19 deaths, disaggregated into deaths inside and outside hospitals. Individual-level data such as age, gender, race/ethnicity, and occupation, is visible in some countries, as is the case in some states (though not the union government) in India. The US releases data about age and race, while the UK releases information about age, gender, race, and occupation. South Korea releases age details for only severe cases and Singapore releases individual-level data only in the event of the death of the individual. Canada releases data about age and pre-existing conditions of the individuals and Australia releases information about age and gender.

Therefore, we find that data release for COVID-19 has issues of lack of standardisation and inter-operability globally. In India, the union and state governments have important deficiencies.

Implications for India

India's existing data infrastructure does not meet the demands of a public health emergency. The implications of this are multifaceted. For example, amid the COVID-19 pandemic, the government had to create a Covid19-warriors dashboard that provides information on doctors, nurses, ASHA workers, and others who could be deployed for immediate response. If data.gov.in had worked well, then the government would have had this information already.

Likewise, the problem of inaccurate databases highlighting data discrepancies in reporting COVID-19 infected persons could have been avoided. An available database infrastructure in data.gov.in would have avoided the need for ICMR to evolve its own data-dissemination method in the middle of the COVID19 pandemic. Besides, the problem of collecting, processing, and releasing COVID-19 data with other databases would have been eased. For example, if the existing data infrastructure had data collection and reporting standards across space like district names with their respective codes, then it would not only be easy to collect the data but also facilitate easier collation with other datasets for enabling interoperability.

Conclusion

In the present article, we highlighted one element of the public health response, the issue of data release by the Indian government authorities for COVID-19. We show that the statistical system for disease surveillance dissemination in India is in a need of reform.

The ODG platform in India, data.gov.in, can play an important role in strengthening India's public health data infrastructure. To realise the utility of public data, a data protocol framework with a legally enforceable mandate on the government is required, as is seen in countries like the US. The principles of standardising, anonymising, interoperability, meta-data release, and grievance redressal in the event of non-release should be in this legal framework.

For the union government, a data.gov.in which utilises the sound principles of OGD release could become a better foundation for data release, and thus improve India's response to an epidemic. State and city governments could choose to use the services of data.gov.in or build their own systems. An indicative list of the essential components of such a portal (as seen in NDSAP and ODG principles) are provided below:

  1. Standardising data release: Standardisation of reported variables such as reporting unit, disease data, language, individual, and community-level data is required. Elements that go towards this include geotagging and coding of hospitals/labs and the adoption of International Classification of Diseases (ICD) for diagnosis and treatment of diseases.

  2. Ensuring privacy: Privacy is a fundamental right in India (Supreme Court of India (2017)). Despite this, states like Madhya Pradesh and Karnataka were seen to be disseminating personally identifiable information of suspected COVID-19 patients. The government would need to adopt various tools at its disposal to protect these rights at an individual and community level. These tools include tagging appropriate data, incorporating principles of Privacy by design (PBD), anonymising and utilising appropriate fiduciary principles (Cavoukian (2011) and Bailey and Goyal (2019)).

  3. Interoperability: Facilitating systems interoperability by incorporating common formats, software standards, and semantic interoperability by incorporating e-governance standards so that the meaning of data is not lost across data silos is required (Wright et al. (2010)).

  4. Adopting an open data scheme: Legislators need to create the frameworks through which the executive is required to release meta-data, and release data in a machine-readable format.

  5. Setting up governance framework: Union, state, and city governments have legitimate authority on how they organise their work, but greater consistency and predictability for API-based access is desirable.

References

Attard et al. (2015): Judie Attard, Fabrizio Orlandi, Simon Scerri, and Sören Auer, A systematic review of open government data initiatives, Government Information Quarterly, 2015.

Chattapadhyay (2013): Sumandro Chattapadhyay, Towards an Expanded and Integrated Open Government Data Agenda for India, IDRC Digital Library.

Agarwal (2016): Natasha Agarwal, Open Government Data: An Answer to India's Growth Logjam, SSRN, 16 August, 2016.

Buteau et al. (2015): Sharon Buteau, Aurelie Larquemin and Jyoti Prasad Mukhopadhyay, Open data and applied socio-economic research in india: An overview, IFMR Working Paper, 27 May, 2015.

Supreme Court of India (2017): Justice K.S. Puttaswamy v. Union of India, 2017 (10) SCC 1.

Cavoukian (2011): Ann Cavoukian, Privacy by design: The seven foundational principles, Information and Privacy Commissioner of Ontario, 2011.

Wright et al. (2010): Glover Wright, Pranesh Prakash Sunil Abraham, Nishant Shah, Open government data study: India, The Centre for Internet and Society, 2010.

Bailey and Goyal (2019): Rishab Bailey and Trishee Goyal, Fiduciary relationships as a means to protect privacy: Examining the use of the fiduciary concept in the Draft Personal Data Protection Bill, 2018, Data Governance Network, 2019.

 

Natasha Agarwal is an independent research economist. Harleen Kaur is a researcher at NIPFP. The authors are thankful to Ajay Shah and two anonymous referees for their valuable comments and inputs on the article.