The Centre for Internet and Society
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Unpacking Algorithmic Infrastructures: Mapping the Data Supply Chain in the Healthcare Industry in India
http://editors.cis-india.org/raw/unpacking-algorithmic-infrastructures
<b>The Unpacking Algorithmic Infrastructures project, supported by a grant from the Notre Dame-IBM Tech Ethics Lab, aims to study the Al data supply chain infrastructure in healthcare in India, and aims to critically analyse auditing frameworks that are utilised to develop and deploy AI systems in healthcare. It will map the prevalence of Al auditing practices within the sector to arrive at an understanding of frameworks that may be developed to check for ethical considerations - such as algorithmic bias and harm within healthcare systems, especially against marginalised and vulnerable populations. </b>
<p style="text-align: justify; ">There has been an increased interest in health data in India over the recent years, where health data policies encourage sharing of data with different entities, at the same time, there has been a growing interest in deployment of Al in healthcare from startups, hospitals, as well as multinational technology companies.</p>
<p style="text-align: justify; ">Given the invisibility of algorithmic infrastructures that underlie the digital economy and the important decisions these technologies can make about patients' health, it's important to look at how these systems are developed, how data flows within them, how these systems are tested and verified and what ethical considerations inform their deployment.</p>
<p style="text-align: justify; "><img src="http://editors.cis-india.org/home-images/ResearchersWork.png/@@images/00a848c7-b7f7-41b4-8bd9-45f2928fd44e.png" alt="Researchers at Work" class="image-inline" title="Researchers at Work" /></p>
<p style="text-align: justify; "><strong>The </strong><strong>Unpacking Algorithmic Infrastructures</strong> project, supported by a grant from the Notre Dame-IBM Tech Ethics Lab, aims to study the Al data supply chain infrastructure in healthcare in India, and aims to critically analyse auditing frameworks that are utilised to develop and deploy AI systems in healthcare. It will map the prevalence of Al auditing practices within the sector to arrive at an understanding of frameworks that may be developed to check for ethical considerations - such as algorithmic bias and harm within healthcare systems, especially against marginalised and vulnerable populations.</p>
<h3 style="text-align: justify; ">Research Questions</h3>
<ol>
<li style="text-align: justify; ">To what extent organisations take ethical principles into account when developing AI , managing the training and testing dataset, and while deploying the AI in the healthcare sector.</li>
<li style="text-align: justify; ">What best practices for auditing can be put in place based on our critical understanding of AI data supply chains and auditing frameworks being employed in the healthcare sector.</li>
<li style="text-align: justify; ">What is a possible auditing framework that is best suited to organisations in the majority world.</li>
</ol>
<h3>Research Design and Methods</h3>
<p>For this study, we will use a comprehensive mixed methods approach. We will survey professionals working towards designing, developing and deploying AI systems for healthcare in India, across technology and healthcare organizations. We will also undertake in-depth interviews with experts who are part of key stakeholder groups.</p>
<p>We hereby invite researchers, technologists, healthcare professionals, and others working at the intersection of Artificial Intelligence and Healthcare to speak to us and help us inform the study. You may contact Shweta Monhandas at <a href="mailto:shweta@cis-india.org">shweta@cis-india.org</a></p>
<ol> </ol>
<hr />
<p>Research Team: Amrita Sengupta, Chetna V. M., Pallavi Bedi, Puthiya Purayil Sneha, Shweta Mohandas and Yatharth.</p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/unpacking-algorithmic-infrastructures'>http://editors.cis-india.org/raw/unpacking-algorithmic-infrastructures</a>
</p>
No publisherAmrita Sengupta, Chetna V. M., Pallavi Bedi, Puthiya Purayil Sneha, Shweta Mohandas and YatharthHealth TechRAW BlogResearchData ProtectionHealthcareResearchers at WorkArtificial Intelligence2024-01-05T02:38:22ZBlog EntryCivil Society’s second opinion on a UHI prescription
http://editors.cis-india.org/internet-governance/blog/civil-society-second-opinion-on-uhi-prescription
<b>On January 13, Pallavi Bedi and Shweta Mohandas from CIS participated in an online collaboration organised by Internet Freedom Foundation for a joint submission to the Consultation Paper on Operationalising Unified Health Interface (UHI) in India released by the National Health Authority.</b>
<p>The article originally published by Internet Freedom Foundation can be <a class="external-link" href="https://internetfreedom.in/civil-societys-second-opinion-on-a-uhi-prescription/">accessed here</a>.</p>
<hr />
<p style="text-align: justify; ">The National Health Authority (NHA) released the Consultation Paper on Operationalising Unified Health Interface (UHI) in India on December 14, 2022. The deadline for submission of comments was January 13, 2023. We collaborated with the Centre for Health Equity, Law & Policy, the Centre for Internet & Society, & the Forum for Medical Ethics Society to submit comments on the paper.</p>
<h3 id="background">Background</h3>
<p style="text-align: justify; ">The UHI is proposed to be a “foundational layer of the Ayushman Bharat Digital Health Mission (ABDM)” and is “envisioned to enable interoperability of health services in India through open protocols”. The ABDM, previously known as the National Digital Health Mission, was announced by the Prime Minister on the 74th Independence Day, and it envisages the creation of a National Digital Health Ecosystem with six key features: Health ID, Digi Doctor, Health Facility Registry, Personal Health Records, Telemedicine, and e-Pharmacy. After launching the programme in six Union Territories, the National Health Authority issued a press release on August 26, 2020 announcing the public consultation for the Draft Health Data Management Policy for NDHM. While the government has repeatedly claimed that creation of a health ID is purely voluntary, contrary <a href="https://caravanmagazine.in/health/doctors-in-chandigarh-compelled-to-register-for-the-voluntary-national-health-id">reports</a> have emerged. In our <a href="https://drive.google.com/file/d/1H5zWsIPj92Vp_gxloBcBzjTwOFif47xY/view">comments</a> as part of the public consultation, our primary recommendation was that deployment of any digital health ID programme must be preceded by the enactment of general and sectoral data protection laws by the Parliament of India; and meaningful public consultation which reaches out to vulnerable groups which face the greatest privacy risks.</p>
<p style="text-align: justify; ">As per the synopsis document which accompanies the consultation paper, it aims to “seek feedback on how different elements of UHI should function. Inviting public feedback will allow for early course correction, which will in-turn engender trust in the network and enhance market adoption. The feedback received through this consultation will be used to refine the functionalities of UHI so as to limit any operational issues going forward.” The consultation paper contains a set of close-ended questions at the end of each section through which specific feedback has been invited from interested stakeholders. We have collaborated with the Centre for Health Equity, Law & Policy, the Centre for Internet & Society, & the Forum for Medical Ethics Society to draft the comments on this consultation paper.</p>
<p style="text-align: justify; ">Our main concern relates to the approach the Government of India and concerned Ministries adopt to draft a consultation paper without explicitly outlining how the proposed UHI fits into the broader healthcare ecosystem and quantifying how it improves it rendering the consultation paper and public engagement efforts inadequate. Additionally, it doesn’t allow the public at large, and other stakeholders to understand how it may contribute to people’s access to quality care towards ensuring realisation of their constitutional right to health and health care. The close-ended nature of the consultation process, wherein specific questions have been posed, restricts stakeholders from questioning the structure of the ABDM itself and forces us to engage with its parts, thereby incorrectly assuming that there is support for the direction in which the ABDM is being developed.</p>
<h3 id="our-submissions">Our submissions</h3>
<p>A. <b>General comments</b></p>
<p>a. <b>Absence of underlying legal framework</b></p>
<p style="text-align: justify; ">Ensuring health data privacy requires legislation at three levels- comprehensive laws, sectoral laws and informal rules. Here, the existing proposal for the data protection legislation, i.e., the draft Digital Personal Data Protection Bill, 2022 (DPDPB, 2022) which could act as the comprehensive legal framework, is inadequate to sufficiently protect health data. This inadequacy arises from the failure of the DPDPB, 2022 to give higher degree of protection to sensitive personal data and allowing for non-consensual processing of health data in certain situations under Clause 8 which relates to “deemed consent”. Here, it may also be noted that the DPDPB, 2022 fails to specifically define either health or health data. Further, the proposed Digital Information Security in Healthcare Act, 2017, which may have acted as a sectoral law, is presently before the Parliament and has not been enacted. Here, the absence of safeguards allows for data capture by health insurance firms and subsequent exclusion/higher costs for vulnerable groups of people. Similarly, such data capture by other third parties potentially leads to commercial interests creeping in at the cost of users of health care services and breach of their privacy and dignity.</p>
<p>b. <b>Issues pertaining to scope</b></p>
<p style="text-align: justify; ">Clarity is needed on whether UHI will be only providing healthcare services through private entities, or will also include the public health care system and various health care schemes and programs of the government, such as eSanjeevani.</p>
<p>c. <b>Pre-existing concerns</b></p>
<ol>
<li style="text-align: justify; "><b>Exclusion</b>: Access to health services through the Unified Health Interface should not be made contingent upon possessing an ABHA ID, as alluded to in the section on ‘UHI protocols in action: An example’ under Chapter 2(b). Such an approach is contrary to the Health Data Management Policy that is based on individual autonomy and voluntary participation. Clause 16.4 of the Policy clearly states that nobody will “be denied access to any health facility or service or any other right in any manner by any government or private entity, merely by reason of not creating a Health ID or disclosing their Health ID…or for not being in possession of a Health ID.” Moreover, the National Medical Commission Guidelines for Telemedicine in India also does not create any obligation for the patient to possess an ABHA ID in order to access any telehealth service. The UHI should explicitly state that a patient can log in on the network using any identification and not just ABHA.</li>
<li style="text-align: justify; "><b>Consent</b>: As per media <a href="https://caravanmagazine.in/health/chandigarh-administratio-aggressively-pushes-national-health-id-registrations-among-residents">reports</a>, registration for a UHID under the NDHM, which is an earlier version of the ABHA number under the ABDM, may have been voluntary on paper but it was being made mandatory in practice by hospital administrators and heads of departments. Similarly, <a href="https://www.thequint.com/tech-and-auto/govt-created-uhid-without-consent-say-vaccinated-indians">reports</a> suggest that people who received vaccination against COVID-19 were assigned a UHID number without their consent or knowledge.</li>
<li style="text-align: justify; "><b>Function creep</b>: In the absence of an underlying legal framework, concerns also arise that the health data under the NDHM scheme may suffer from function creep, i.e., the collected data being used for purposes other than for which consent has been obtained. These concerns arise due to similar function creep taking place in the context of data collected by the Aarogya Setu application, which has now pivoted from being a contact-tracing application to “<a href="https://indianexpress.com/article/technology/tech-news-technology/aarogya-setus-journey-from-a-quick-fix-for-contract-tracing-to-health-app-of-the-nation-8006372/">health app of the nation</a>”. Here, it must be noted that as per a RTI response dated June 8, 2022 from NIC, the Aarogya Setu Data Access And Knowledge Sharing Protocol “<a href="https://drive.google.com/file/d/1eSUoZtFqrIcqJH2Q2zK-LJmTDKF49l66/view">has been discontinued</a>".</li>
<li style="text-align: justify; "><b>Issues with the United Payments Interface may be replicated by the UHI</b>: The consultation paper cites the United Payments Interface (UPI) as “strong public digital infrastructure” which the UHI aims to leverage. However, a trend towards market concentration can be witnessed in UPI: the two largest entities, GooglePay and PhonePe, have seen their market share hover around 35% and 47% (by volume) for some time now (their share by value transacted is even higher). Meanwhile, the share of the NPCI’s own app (BHIM) has fallen from 40% in August 2017 to 0.74% in September 2021. Thus, if such a model is to be adopted, it is important to study the UPI model to understand such threats and ensure that a similar trend towards oligopoly or monopoly formation in UHI is addressed. This is all the more important in a country in which the decreasing share of the public health sector has led to skyrocketing healthcare costs for citizens.</li>
</ol>
<p style="text-align: justify; ">B. Our response also addressed specific questions about search and discovery, service booking, grievance redressal, and fake reviews and scores. Our responses on these questions can be found in our comments <a href="https://drive.google.com/file/d/1j9wUafZM10kmS_MOzk-D8LYIPMm_9JOa/view?usp=share_link">here</a>.</p>
<h3 id="our-previous-submissions-on-health-data">Our previous submissions on health data</h3>
<p style="text-align: justify; ">We have consistently engaged with the government since the announcement of the NDHM in 2020. Some of our submissions and other outputs are linked below:</p>
<ol>
<li>IFF’s comment on the Draft Health Data Management Policy dated May 21, 2022 (<a href="https://drive.google.com/file/d/1I4ZAVLNa00v_MeTDYoAv63Ueq6ICTwWT/view?usp=sharing">link</a>)</li>
<li>IFF’s comments on the consultation Paper on Healthcare Professionals Registry dated July 20, 2021 (<a href="https://drive.google.com/drive/folders/10x0IirdQTZCC9S_w83nTVp1GRsxArDt7">link</a>)</li>
<li>IFF and C-HELP Working Paper: ‘Analysing the NDHM Health Data Management Policy’ dated June 11, 2021 (<a href="https://drive.google.com/file/d/1sEBg-syzsbe159x4PGkAHzcZilct0cQq/view">link</a>)</li>
<li>IFF’s Consultation Response to Draft Health Data Retention Policy dated January 6, 2021 (<a href="https://drive.google.com/file/d/124iqcboTxkrPLMPX6erLXjhH1SDk_L0B/view?usp=sharing">link</a>)</li>
<li>IFF’s comments on the National Digital Health Mission’s Health Data Management Policy dated September 21, 2020 (<a href="https://drive.google.com/file/d/1H5zWsIPj92Vp_gxloBcBzjTwOFif47xY/view?usp=sharing">link</a>)</li>
</ol>
<h3 id="important-documents">Important documents</h3>
<ol>
<li style="text-align: justify; ">Response on the Consultation Paper on Operationalising Unified Health Interface (UHI) in India by Centre for Health Equity, Law & Policy, the Centre for Internet & Society, the Forum for Medical Ethics Society, & IFF dated January 13, 2023 (<a href="https://drive.google.com/file/d/1j9wUafZM10kmS_MOzk-D8LYIPMm_9JOa/view?usp=share_link">link</a>)</li>
<li>NHA’s Consultation Paper on Operationalising Unified Health Interface (UHI) in India dated December 14, 2022 (<a href="https://abdm.gov.in:8081/uploads/Consultation_Paper_on_Operationalising_Unified_Health_Interface_UHI_in_India_9b3a517a22.pdf">link</a>)</li>
<li>Synopsis of NHA’s Consultation Paper on Operationalising Unified Health Interface (UHI) in India dated December 14, 2022 (<a href="https://abdm.gov.in:8081/uploads/Synopsis_Operationalising_Unified_Health_Interface_UHI_in_India_308cd449fb.pdf">link</a>)</li>
</ol>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/civil-society-second-opinion-on-uhi-prescription'>http://editors.cis-india.org/internet-governance/blog/civil-society-second-opinion-on-uhi-prescription</a>
</p>
No publisherPallavi Bedi and Shweta MohandasHealth TechHealth ManagementInternet GovernanceHealthcare2023-02-15T08:20:15ZBlog EntryComments to the Draft National Health Data Management Policy 2.0
http://editors.cis-india.org/internet-governance/blog/comments-to-the-draft-national-health-data-management-policy-2.0
<b>Anamika Kundu, Shweta Mohandas and Pallavi Bedi along with 9 other organizations / individuals drafted comments to the Draft National Health Data Management Policy 2.0. </b>
<p style="text-align: justify; ">This is a joint submission on behalf of (i) Access Now, (ii) Article 21, (iii) Centre for New Economic Studies, (iv) Center for Internet and Society, (v) Internet Freedom Foundation, (vi) Centre for Justice, Law and Society at Jindal Global Law School, (vii) Priyam Lizmary Cherian, Advocate, High Court of Delhi (ix) Swasti-Health Catalyst, (x) Population Fund of India.</p>
<p style="text-align: justify; ">At the outset, we would like to thank the National Health Authority (NHA) for inviting public comments on the draft version of the National Health Data Management Policy 2.0 (NDHMPolicy 2.0) (Policy) We have not provided comments to each section/clause, but have instead highlighted specific broad concerns which we believe are essential to be addressed prior tothe launch of NDHM Policy 2.0.</p>
<hr />
<p style="text-align: justify; ">Read on to <a href="http://editors.cis-india.org/internet-governance/draft-national-health-management-policy" class="internal-link">view the full submission here</a></p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/comments-to-the-draft-national-health-data-management-policy-2.0'>http://editors.cis-india.org/internet-governance/blog/comments-to-the-draft-national-health-data-management-policy-2.0</a>
</p>
No publisherAnamika Kundu, Shweta Mohandas and Pallavi BediHealth TechHealth ManagementInternet GovernanceHealthcare2022-05-24T16:06:15ZBlog EntryRecommendations for the Covid Vaccine Intelligence Network (Co-Win) platform
http://editors.cis-india.org/internet-governance/blog/an-analysis-of-the-covid-vaccine-intelligence-network-co-win-platform
<b></b>
<p style="text-align: justify;" dir="ltr"> </p>
<p style="text-align: justify;" dir="ltr">The first confirmed case of Covid-19 was recorded in India on January 30, 2020, and India’s vaccination drive started 12 months later on January 16, 2021; with the anxiety and hope that this signals the end of the pandemic. The first phase of the vaccination drive identified healthcare professionals and other frontline workers as beneficiaries. The second phase, which has been rolled out from March 1, covers specified sections of the general population; those above 60 years and those between 45 years and 60 with specific comorbid conditions. The first phase also saw the deployment of the Covid Vaccine Intelligence Network (Co-Win) platform to roll out and streamline the Covid 19 vaccination process. For the purpose of this blog post, the term CoWIn platform has been used to refer to the CoWin App and the CoWin webportal. </p>
<p style="text-align: justify;" dir="ltr">During the first phase, <a href="https://www.livemint.com/news/india/covid-vaccination-in-india-health-min-says-registering-with-cowin-is-mandatory-11610678273260.html">it was mandatory </a>for the identified beneficiaries to be registered on the Co-Win App prior to receiving the vaccine. The Central Government had earlier indicated that it would be mandatory for all the future beneficiaries to register on the Co-Win app; however, the Health Ministry hours before the roll out of the second phase <a href="https://www.livemint.com/news/india/cowin-app-not-for-vaccine-registration-visit-its-portal-instead-ministry-of-health-11614581076188.html">tweeted t</a>hat beneficiaries should use the Co-Win web portal (not the Co-Win app) to register themselves for the vaccine. The App which is currently available on the play store is only for administrators; it will not be available for the general public. Beneficiaries can now access the vaccination by; (i) registering on the CoWin website; or (ii) Certain vaccination (sites) have a walk-in-facility: On-site registration, appointment, verification, and vaccination will all be on-site the same day; or (iii) register and get an appointment for the vaccination through the Aarogya Setu app. </p>
<p style="text-align: justify;" dir="ltr">The scale and extent of the global pandemic and the Covid-19 vaccination programme differs significantly from the vaccination/immunisation programmes conducted by India previously, and therefore, the means adopted for conducting the vaccination programme will have to be modified accordingly. However, as<a href="https://www.firstpost.com/india/glitches-in-cowin-2-0-hold-up-vaccination-centre-must-upgrade-app-capacity-to-meet-demand-say-experts-9361051.html"> several newspaper reports</a> have indicated the roll out of the CoWin platform has not been smooth. There are<a href="https://www.indiatoday.in/cities/mumbai/story/technical-glitches-in-cowin-app-again-affects-vaccination-drive-at-vaccination-centres-1769410-2021-02-15"> several glitch</a>es; from the user data being incorrectly registered, to beneficiaries not receiving the one time password required to schedule the appointment. </p>
<p style="text-align: justify;" dir="ltr">An entirely offline or online method (internet penetration is at 40% ) to register for the vaccine is not feasible and a hybrid model (offline registration and online registration) should be considered. However, the specified platform should take into account the concerns which are currently emanating from the use of Co-Win and make the required modifications. <br /> </p>
<h3 style="text-align: justify;">Privacy Concerns </h3>
<p style="text-align: justify;" dir="ltr">When the beneficiary uses the Co-Win website to register, she is required to provide certain demographic details such as name, gender, date of birth, photo identity and mobile number. Though Aadhar has been identified as one of the documents that can be uploaded as a photo identity, the Health Ministry in a response to a RTI filed by the Internet Freedom Foundation (IFF) clarified that Aadhaar is nor mandatory for registration either through the Co-Win website or through Aarogya Setu. While, the Government has clarified that the App cannot be used by the general public to register for the vaccination, it still leaves open the question of the status of the personal data of the beneficiaries identified in the first phase of the process, who were registered on the App, and whose personal details were pre-populated on the App. In fact in certain instances,<a href="https://www.thenewsminute.com/article/teething-troubles-privacy-concerns-look-co-win-india-s-vaccine-portal-142015"> Aadhar details</a> were uploaded on the app as the identity proof, without the knowledge of the beneficiary. </p>
<p style="text-align: justify;" dir="ltr">These concerns are exacerbated in the absence of a robust data protection law and with the knowledge that the Co-Win platform (App and the website) does not have a dedicated independent privacy policy. While the Co-Win web portal does not provide any privacy policy, the <a href="https://play.google.com/store/apps/details?id=com.cowinapp.app">privacy policy</a> hyperlinked on the App directs the user to the Health Data Policy of the <a href="https://ndhm.gov.in/health_management_policy">National Health Data Management Policy, 2020.</a> The Central Government approved the Health Data Management Policy on December 14, 2020. It is an umbrella document for all entities operating under the digital health ecosystem. </p>
<p style="text-align: justify;" dir="ltr">An analysis of the Health Policy against the key internationally recognised privacy principles which are represented in most data protection frameworks in the world, including the Personal Data Protection Bill, 2019, highlights that the Health Policy does not provide any information on data retention, data sharing and the grievance redressal mechanism. It is important to note that the Health policy has also been framed in the absence of a robust data protection law; the Personal Data Protection Bill is still pending before Parliament. </p>
<p style="text-align: justify;" dir="ltr">The Co-WIn website does not provide any separate information on how long the data will be retained, whether the data will be shared and how many ministries/departments have access to the data. </p>
<p style="text-align: justify;" dir="ltr">A National Health Policy cannot and should not be used as a substitute for specific independent privacy policies of different apps that may be designed by the Government to collect and process the health data of users. Health Data is recognised as sensitive personal data under the proposed personal data protection bill and should be accorded the highest level of protection. This was also reiterated by the Karnataka High Court in its<a href="https://www.livelaw.in/news-updates/karnataka-high-court-privacy-article-21-constitution-aarogya-setu-app-168950"> recent interim order</a> on Aarogya Setu. It held that medical information or data is a category of data to which there is a reasonable expectation of privacy, and “the sharing of health data of a citizen without his/her consent will necessarily infringe his/her fundamental right of privacy under Article 21 of the Constitution of India.” <br /><br /></p>
<h3 style="text-align: justify;">Link with Aarogya Setu</h3>
<p style="text-align: justify;" dir="ltr"> A beneficiary registered on the Co-Win platform can use the Aarogya Setu App to download their vaccination certificate. Beneficiaries have now also been provided an option to register for vaccination through Aarogya Setu. However, the rationale for linking the two separate platforms is not clear, especially as Aaroya Setu has primarily been deployed as a contact tracing application. </p>
<p style="text-align: justify;" dir="ltr">There is no information on whether the data (and to what extent) that is stored in the Co-Win platform will be shared with Aarogya Setu. It is also not clear whether the consent of the beneficiary registered on the Co-Win platform will be obtained again prior to sharing the data or whether registration on the Co-Win platform will be regarded as general consent for sharing the data with Aarogya Setu. This is contrary to the principle of informed consent (i.e the consent has to be unambiguous, specific, informed and voluntary), which a data fiduciary has to comply with prior to obtaining personal data from the data principal. The privacy policy of Aarogya Setu has also not been amended to reflect this change in the purpose of the App.<br /> </p>
<h3 style="text-align: justify;">Co-Win registration as an entry to develop health IDs?</h3>
<p style="text-align: justify;" dir="ltr"> One of the objectives of the Health Data Management Policy is to develop a digital unique health ID for all the citizens. The National Health Data Management Policy states that participation in the National Health Data Ecosystem is voluntary; and the participants will, at any time, have the right to exit from the ecosystem. Currently, the policy has been rolled out on a pilot basis in 6 union territories, namely; Chandigarh, Dadra & Nagar Haveli, Daman & Diu, Puducherry, Ladakh and Lakshadweep. As Health is a state subject under the Indian Constitution, <a href="https://scroll.in/latest/972361/new-health-data-policy-may-be-misused-for-surveillance-chhattisgarh-minister-writes-to-vardhan">Chhattisgarh</a> has raised concerns about the viability and necessity of the policy, especially in the absence of a robust data protection legislation. </p>
<p style="text-align: justify;" dir="ltr"> Mr. R.S. Sharma, the Chairperson of the ‘Empowered Group on Technology and Data Management to combat Covid-19’ had in an <a href="https://www.indiatoday.in/coronavirus-outbreak/vaccine-updates/story/exclusive-besides-co-win-aarogya-setu-self-register-indi-vaccine-drive-1760833-2021-01-20">interview to India Today</a> stated “ “Not just for vaccinations, but the platform will be instrumental in becoming a digital health database for India”. This indicates that this is an initial step towards generating health ID for all the beneficiaries. It would also violate the<a href="https://www.accessnow.org/india-cowin-app/"> principle of purpose limitatio</a>n, that data collected for one purpose (for the vaccine) cannot be reused for another (for the creation of the Digital Health ID system) without an individual’s explicit consent and the option to opt-out.<br /><br /></p>
<h3 style="text-align: justify;">Conclusion</h3>
<p style="text-align: justify;" dir="ltr"> <a href="https://www.thehindu.com/opinion/editorial/injecting-confidence-the-hindu-editorial-on-indias-covid-19-vaccination-drive/article33595220.ece">Given India’s experience and reasonable success with childhood immunisation</a>, there is reasonable confidence that the country has the ability to scale up vaccination. However, the vaccination drive should not be used as a means to set aside the legitimate concerns of the citizens with regard to the mechanism deployed to get pet people to register for the vaccination drive. As a first step it is essential that Co-Win has a separate dedicated privacy policy which conforms to the internationally accepted privacy principles and enumerated in the Personal Data Protection Bill. It is also essential that Co-Win or any other app/digital platform should not be used as a backdoor entry for the government to create unique digital health IDs for the citizens, especially without their consent and in the absence of a robust data protection law. </p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/an-analysis-of-the-covid-vaccine-intelligence-network-co-win-platform'>http://editors.cis-india.org/internet-governance/blog/an-analysis-of-the-covid-vaccine-intelligence-network-co-win-platform</a>
</p>
No publisherPallavi BediAarogya SetuHealth TechPiracyinternet governanceHealthcaree-Governance2021-03-25T13:14:46ZBlog EntryPandemic Technology takes its Toll on Data Privacy
http://editors.cis-india.org/internet-governance/blog/deccan-herald-aman-nair-and-pallavi-bedi-june-13-2021-pandemic-technology-takes-its-toll-on-data-privacy
<b>The absence of any legal framework has meant these tools are now being used for purposes beyond managing the pandemic.</b>
<p style="text-align: center; ">The article by Aman Nair and Pallavi Bedi was <a class="external-link" href="https://www.deccanherald.com/specials/pandemic-technology-takes-its-toll-on-data-privacy-996870.html">published in the Deccan Herald </a>on June 13, 2021.</p>
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<p style="text-align: center; "><img src="http://editors.cis-india.org/home-images/ArogyaSetuApp.jpg" alt="Arogya Setu App" class="image-inline" title="Arogya Setu App" /></p>
<p style="text-align: center; "><span class="discreet">People show Arogya Setu App installed in their phones while travelling by special New Delhi-Bilaspur train from New Delhi Railway Station. Credit: PTI File Photo<br /></span></p>
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<p style="text-align: center; "><img src="http://editors.cis-india.org/home-images/CovidCertificate.jpg/@@images/672b385b-d0b0-49af-953d-ae96a42be117.jpeg" alt="Covid Certificate" class="image-inline" title="Covid Certificate" /></p>
<p style="text-align: center; "><span class="discreet">Jabalpur: A beneficiary shows his certificate on his mobile phone after receiving COVID-19 vaccine dose, at Gyan Ganga College in Jabalpur, Saturday, May 15, 2021. (PTI Photo)</span></p>
<p style="text-align: justify; ">At a time when technology is spawning smart solutions to combat Covid-19 worldwide, India’s digital response to the pandemic has stoked concerns that surveillance could pose threats to the privacy of the personal data collected. Be it apps or drones, there is widespread criticism that digital tools are being misused to share information without knowledge or consent. At the other end of the spectrum, the great urban-rural digital divide is hampering the already sluggish vaccination drive, exposing vulnerable populations to a fast-mutating virus.</p>
<p style="text-align: justify; ">Last year, the Centre, states and municipal corporations launched more than 70 apps relating to Covid-19, demonstrating the country’s digital-driven approach to handling the pandemic. Chief among these was the central government’s contact tracing app Aarogya Setu. Launched under the Digital India programme, the app quickly came under scrutiny over data privacy.</p>
<p style="text-align: justify; ">As per its privacy policy, Aarogya Setu collects personal details such as name, age, sex, profession and location. As there is no underlying legislation forming its basis, and in the absence of a personal data protection bill, serious privacy concerns regarding the collection, storage and use of personal data have been raised.</p>
<p style="text-align: justify; ">The government has attempted to mitigate these concerns with reassurances that the data will be used solely in tracing the spread of the virus. However, recent reports from the Kulgam district of Jammu and Kashmir point to the sharing of application data with police. This demonstrates how easy it is to use personal data for purposes other than which it was collected, and presents a serious threat to citizen privacy.</p>
<p style="text-align: justify; ">Though Aarogya Setu was initially launched as ‘consensual’ and ‘voluntary’, it soon became mandatory for individuals to download the app for various purposes such as air and rail travel (this order was subsequently withdrawn) and for government officials. Initially it was also mandatory for the private sector, but this was later watered down to state that employers should, on a ‘best effort basis', ensure that the app is downloaded by all employees having compatible phones. However, the ‘best effort basis’ soon translated into mandatory imposition for certain individuals, especially those working in the ‘gig economy’.</p>
<p style="text-align: justify; ">Several states had also launched apps for various purposes ranging from contact tracing of suspected Covid patients to monitoring the movement of quarantined patients. As a report by the Centre for Internet and Society observed, given the attention on Aarogya Setu, most of the apps launched by the state governments escaped scrutiny and public attention.Most of these apps either did not have a privacy policy or the policy was vague and often did not provide important details such as who was collecting the data, the time period for retaining the data and whether personal data could be shared with other departments, most notably, law enforcement.Apart from contact tracing apps, the pandemic also ushered in a wave of other apps and digital tools by the government. These include systems such as drones to check whether people are following Covid-19 norms and facial recognition cameras to report to the police whether someone has broken quarantine. Similar to Aarogya Setu, these tools have also largely been brought about in the absence of a legal and regulatory framework.<br />The absence of any legal framework has meant these tools are now being used for purposes beyond managing the pandemic.</p>
<p style="text-align: justify; ">The government is now planning to use facial recognition technology along with Aadhaar toauthenticate people before giving them vaccine shots.</p>
<p style="text-align: justify; ">Aarogya Setu is now linked with the vaccination process. Beneficiaries have been provided an option to register through Aarogya Setu. The pandemic has also provided a means for the government to bring in changes to health policies and introduce the National Health Data Management Policy for the creation of a Unique Health Identity Number for citizens.</p>
<h3 style="text-align: justify; ">Vaccination and digital platforms</h3>
<p style="text-align: justify; ">The use of digital technology has extended to the vaccination process through the deployment of the Covid Vaccine Intelligence Network (Co-WIN) platform.During the first phase of inoculation, beneficiaries were required to register on the Co-WIN app while in the subsequent phases, registration was to be done on the Co-WIN website. The beneficiary is required to upload a photo identity proof.</p>
<p style="text-align: justify; ">While Aadhaar has been identified as one of the seven documents that can be uploaded for this, the Health Ministry has clarified that Aadhaar is not mandatory for registration either through Co-WIN or through Aarogya Setu. However, as per media reports, certain vaccination centres still seem to insist on Aadhaar identity even though beneficiaries may have used another identity proof to register on the Co-WIN website.</p>
<p style="text-align: justify; ">It is also pertinent to note that the website did not have a privacy policy till the Delhi High Court issued directions on June 2, 2021. The privacy policy hyperlinked on the Co-WIN app directed the user to the Health Data Policy of the National Health Data Management Policy, 2020.</p>
<p style="text-align: justify; ">The vaccination drive has been used as a means to push the health identity project forward as beneficiaries who have opted to provide Aadhaar identity proof have also been provided with a health identity number on their vaccination certificate. It is interesting to note that Co-WIN’s privacy policy now states that if the beneficiary uses Aadhaar as identity proof, it can 'opt' to get a Unique Health Id.However, as a recent report revealed, health identity numbers have already been generated for certain beneficiaries without obtaining consent from them for the purpose.</p>
<h3 style="text-align: justify; ">Have the apps been successful?</h3>
<p style="text-align: justify; ">One could argue that privacy concerns are a worthwhile tradeoffin order to contain the spread of thepandemic. But it is worth examining how successful these technologies have been. In reality, the use of digital technology at every stage of combating the pandemic has clearly highlighted the extent of our digital divide. As per data from TRAI, there are around 750 million Internet subscribers in India,which is only a little more than half of India’s estimated 1.3 billion citizens — with this gap having a significant impact on the efficacy of the government’s strategies. Aarogya Setu has fallen far short of its goal, of having near universal adoption. It has limited adoption in much of the country. This has severely limited its efficacy in tracing the spread of the virus. Research from Maulana Azad Medical College has cited socio-economic inequalities,educational barriers and the lack of smartphone penetration as being the key causes behind the app’s limited success, pointing back to the digital divide. Moreover, the app has also brought with it a host of associated problems including lateral surveillance and function creep caused by the addition of new features. All of which, along with the previously mentioned privacy concerns, have served to hamper public trust and adoption.</p>
<p style="text-align: justify; ">A similar situation is seen in the case of vaccination and the Centre’s Co-WIN web portal. The need for registration, first on the Co-WIN app and later on the Co-WIN web portal, has disproportionately affected those who either have no or limited digital access. Many of them belong to vulnerable groups such as migrant and informal sector workers (mainly from disadvantaged castes), LGBTQIA + individuals, sex workers and both urban and rural poor. These issues have also been acknowledged by the Supreme Court, which raised serious concerns about the government being able to achieve its stated object of universal vaccination.</p>
<p style="text-align: justify; ">As the inoculation exercise opened up for the 18-45 age group, it increasingly favoured the urban population who possessed the technological and digital literacy to either create or access a host of tools. One need to only look at the wave of automated CO-WIN bots that arose as soon as the vaccination process was expanded to see how these dynamics manifested.</p>
<p style="text-align: justify; ">Ultimately, the digital-driven approach that the governments have adopted has resulted in a number of issues — most notably, data privacy and exclusion. Going forward, government strategies must actively account for these factors and ensure that citize rights are adequately protected.</p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/deccan-herald-aman-nair-and-pallavi-bedi-june-13-2021-pandemic-technology-takes-its-toll-on-data-privacy'>http://editors.cis-india.org/internet-governance/blog/deccan-herald-aman-nair-and-pallavi-bedi-june-13-2021-pandemic-technology-takes-its-toll-on-data-privacy</a>
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No publisherAman Nair and Pallavi BediHealth TechPrivacyInternet GovernanceTechnological Protection MeasuresCovid19Healthcare2021-06-26T06:52:52ZBlog EntryComments to National Digital Health Mission: Health Data Management Policy
http://editors.cis-india.org/internet-governance/blog/comments-to-national-digital-health-mission-health-data-management-policy
<b>CIS has submitted comments to the National Health Data Management Policy. We welcome the opportunity provided to our comments on the Policy and we hope that the final Policy will consider the interests of all the stakeholders to ensure that it protects the privacy of the individual while encouraging a digital health ecosystem.
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<p>Read the full set of comments <a href="http://editors.cis-india.org/internet-governance/comments-to-national-digital-health-mission-health-data-management-policy-pdf" class="internal-link" title="Comments to National Digital Health Mission: Health Data Management Policy pdf">here</a>.</p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/comments-to-national-digital-health-mission-health-data-management-policy'>http://editors.cis-india.org/internet-governance/blog/comments-to-national-digital-health-mission-health-data-management-policy</a>
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No publisherShweta Mohandas, Pallavi Bedi, Shweta Reddy, and Saumyaa NaiduData Governanceinternet governanceInternet GovernanceHealthcare2020-10-05T15:56:51ZBlog EntryIs India's Digital Health System Foolproof?
http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof
<b>This contribution by Aayush Rathi builds on "Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?" (by Aayush Rathi and Ambika Tandon, EPW Engage, Vol. 54, Issue No. 6, 09 Feb, 2019) and seeks to understand the role that state-run reproductive health portals such as the Mother and Child Tracking System (MCTS) and the Reproductive and Child Health will play going forward. The article critically outlines the overall digitised health information ecosystem being envisioned by the Indian state.</b>
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<h4>This article was first published in <a href="https://www.epw.in/engage/article/indias-digital-health-paradigm-foolproof" target="_blank">EPW Engage, Vol. 54, Issue No. 47</a>, on November 30, 2019</h4>
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<p>Introduced in 2013 and subsequently updated in 2016, the Ministry of Health and Family Welfare (MHFW) published a document laying out the standards for electronic health records (EHRs). While there exist varying interpretations of what constitutes as EHRs, some of its characteristics include electronic medical records (EMRs) of individual patients, arrangement of these records in a time series, and inter-operable linkages of the EMRs across various healthcare settings (Häyrinen et al 2008; OECD 2013).</p>
<p>To work effectively, EHRs are required to be highly interoperable so that they can facilitate exchange among health information systems (HIS) across participating hospitals. For this, the Integrated Health Information Platform (IHIP) is being developed so as to assimilate data from various registries across India and provide real-time information on health surveillance (Krishnamurthy 2018).</p>
<h3><strong>EHR Implementation: Unpacking the (Dis)incentive Structure</strong></h3>
<p>As the implementation of EHR standards is voluntary, anecdotal evidence indicates that their uptake in the Indian healthcare sector has been very slow. Here, the opposition of the Indian Medical Association to the Clinical Establishments (Registration and Regulation) Act, 2010, resulting in nationwide protests and subsequent legal challenges to the act, is instructive. To start with, the act prescribes the minimum standards that have to be maintained by clinical establishments which are registered or seeking registration (itself mandatory to run a clinic under the act) <strong>[1]</strong>. Further, Rule 9(ii) of the Clinical Establishments (Registration and Regulation) Rules, 2012, drafted under the act, requires clinical establishments to maintain EMRs or EHRs for every patient. However, with health being a state subject in India, the act has only been enforced in 11 states and all union territories except the National Capital Territory of Delhi (Jyoti 2018). The resistance to the act is largely due to protests by stakeholders from within the medical fraternity regarding its adverse impact on small- and medium-sized hospitals (Jyoti 2018).</p>
<h3><strong>Contextualising Clinicians' Inertia</strong></h3>
<p>Another major impediment to the adoption of EHRs by health service providers is reluctance on the part of individual physicians to transition to an EHR system. This is because compliance with EHR standards requires physicians to input clinical notes themselves.</p>
<p>Comparing the greater patient load faced by doctors in India vis-à-vis the United States (US), the chief medical officer of an EHR vendor in India estimates that the average Indian doctor sees about 40–60 patients a day, whereas in the US it may be around 18–20 patients (Kandhari 2017). This is suggestive of the wide disparity in the number of physicians per 1,000 citizens in both countries (World Bank nd). Given this, doctors in India tend to be more problem-oriented, time-strapped, and pay less attention to clinical notes (Kandhari 2017). Thus, clinicians will consider a system to be efficient only if the system reduces their documentation time, even if the time savings do not translate into better patient care (Allan and Englebright 2000). The inability of EHRs to help reduce documentation time deters clinicians from supporting their implementation (Poon et al 2004). Additionally, research done in the United States indicates that there is no evidence to suggest that an information system helps save time expended by clinicians on documentation (Daly et al 2002). Moreover, the use of an information system is stated to have had no impact on patient care, but doctors have acknowledged its use for research purposes (Holzemer and Henry 1992).</p>
<h3><strong>Prohibitive Costs of Implementation</strong></h3>
<p>While national-level EHRs have been adopted globally, their distribution across countries is telling. In a survey published in 2016 by the World Health Organization, wealthier countries were over-represented, with two-thirds from the upper-middle-income group and roughly half from the high-income countries having introduced EHR systems. On the other hand, only a third of lower-middle-income countries and 15% of low-income countries reported having implemented EHRs (World Health Organization 2016). A major reason for the slow uptake of EHRs in poorer countries is likely to be funding as EHR implementation requires considerable investment, with most projects averaging several million dollars (US) (Kuperman and Gibson 2003). Although various funding models for EHR implementation are being utilised globally, it is unclear what model will be adopted in India to bring in private healthcare service providers within its ambit (Healthcare Information and Management Systems Society 2007). This absence of funding direction for private actors poses to be a significant impediment in the integration of private databases with other public ones.</p>
<p>In general, poorer countries are also more likely to have less developed infrastructure and health Information and Communication Technology (ICT) to support EHR systems. Besides this, they not only lack the capacity and human resources required to develop and maintain such complex systems (Tierney et al 2010; McGinn et al 2011), but training periods have also been found to be long and more costly than expected (Kovener et al 1997).</p>
<h3><strong>Socio-economic Exclusions and Cross-cultural Barriers</strong></h3>
<p>There exists scant research investigating the existing use of EHRs in India, though preliminary work is being undertaken to assess EHR implementation in other developing countries (Tierney et al 2010; Fraser et al 2005). Even in the context of developed countries, where widespread adoption of EHRs has been gaining traction for some time now, very little data exists around implementation and efficacy in underserved regions and communities. This is further problematised as clinical information systems and user populations also vary in their characteristics and, for this reason, individual studies are unable to identify common trends that would predict EHR implementation success.</p>
<p>Underserved settings may lack the infrastructure needed to support EHRs. The risk of exclusion already exists in parts such as difficulties inherent in delivering care to remote locations, barriers related to cross-cultural communication, and the pervasive problem of providing care in the setting of severe resource constraints. Equally important is the fact that health workers who already report significant existing impediments in their delivery of routine care in these settings do not necessarily see EHRs as being useful in catering to the specific needs of their patient population (Bach et al 2004). Moreover, experience with EHRs also reveals that there are cultural barriers to capturing accurate data (Miklin et al 2019). What this could mean is that stigma associated with the diagnosis of conditions such as HIV/AIDS or induced abortions will result in their under-reporting even within EHR systems.</p>
<h3><strong>Stick or Twist?</strong></h3>
<p>Other modalities have been devised to nudge healthcare providers into adopting EHR standards voluntarily. The National Accreditation Board for Hospitals and Healthcare Providers (NABH), India, a constituent board of the Quality Council of India (a public–private initiative), has been reported to have incorporated the EHR standards within its accreditation matrix. NABH accreditation, considered an indicator of high quality patient care, is highly sought–after by hospitals in India in order to attract medical tourists as well as insurance companies: two prominent sources of income for hospitals (Kandhari 2017). Additionally, NABH accreditation is valid for a term of three years, thus requiring hospitals seeking to renew their accreditation to adopt EHR standards as well.</p>
<p>Another commercial use of EHR has been in health insurance. The Federation of Indian Chambers of Commerce and Industry (FICCI) and the Insurance Regulatory and Development Authority (IRDAI) have both voiced their support for expediting the implementation of the EHR standards (EMR Standards Committee 2013). Both, the FICCI and IRDAI have placed emphasis on adopting EHRs, seeing it as a necessary move for formalising the health insurance industry (FICCI 2015). They have also had representation on the committee that sent recommendations to the MHFW on the first version of the EHR standards in 2013 (FICCI 2015). FICCI had additionally played a coordination role in having the recommendations framed for the 2013 EHR standards.</p>
<h3><strong>Fluid Data Objectives</strong></h3>
<p>The push for EHR implementation is emblematic of a larger shift in the healthcare approach of the Indian state, that of an indirect targeting of demand-side financing by plugging data inefficiencies in health insurance.</p>
<p>The draft National Health Policy (NHP), published in 2015, reflected the mandate of the Ministry of Health and Family Welfare to strengthen the public health system by creating a right to healthcare legislation and reaching a public spend of 2.5% of the gross domestic product by 2018. The final version of the NHP, published in 2017, however, codified a shift in healthcare policy by focusing on strategic purchasing of secondary and tertiary care services from the private sector and a publicly funded health insurance model.</p>
<p>In line with the vision of the NHP 2017, in February 2018, the Union Minister for Finance and Corporate Affairs, Arun Jaitley, announced two major initiatives as a part of the government’s Ayushman Bharat programme (Ministry of Finance 2018). Administered under the aegis of the Ministry of Health and Family Welfare, these initiatives are intended to improve access to primary healthcare through the creation of 150,000 health and wellness centres as envisioned under the NHP 2017, and improve access to secondary and tertiary healthcare for over 100 million vulnerable families by providing insurance cover of up to ₹ 500,000 per family per year under the Pradhan Mantri–Rashtriya Swasthya Suraksha Mission/National Health Protection Scheme (PM–RSSM/NHPS) (Ministry of Health and Family Welfare 2018). The NHPS, modelled along the lines of the Affordable Care Act in the US, was later rebranded as the Pradhan Mantri–Jan Arogya Yojana (PM-JAY) at the time of its launch in September 2018. It is claimed to be the world’s largest government-funded healthcare programme and is intentioned to provide health insurance coverage for vulnerable sections in lieu of the Sustainable Development Goal-3 (National Health Authority nd).</p>
<p>To enable the implementation of the Ayushman Bharat programme, the NITI Aayog then proposed the creation of a supply-side digital infrastructure called National Health Stack (NHS) (NITI Aayog 2018). As outlined in the consultation and strategy paper, the NHS is “built for NHPS, but beyond NHPS.” The NHS seeks to leverage the digitisation push through IndiaStack, which seeks to digitalise “any large-scale health insurance program, in particular, any government-funded health care programs.” The synergy is clear, with the NHPS scheme also aiming to be “cashless and paperless at public hospitals and empanelled private hospitals" (National Health Authority nd) <strong>[2]</strong>.</p>
<p>The NHS is also closely aligned with the NHP 2017, which draws attention to leveraging technologies such as big data analytics on data stored in universal registries. The Vision document for the NHS emphasises the fragmented nature of health data as an impediment to reducing inequities in healthcare provision. The NHS, then, also seeks to be the master repository of health data akin to the IHIP. By creating a base layer of registries containing information about various actors involved in the healthcare supply chain (providers such as hospitals, beneficiaries, doctors, insurers and Accredited Social Health Activists), it potentially allows for recording of data from both public and private sector entities, plugging a significant gap in the coverage of the HIS currently implemented in India. With the provision of open, pullable APIs, the NHS also shares the motivations of the IndiaStack to monetise health data.</p>
<p>A key component of the proposed NHS is the Coverage and Claims platform, which the vision document describes as “provid[ing] the building blocks required to implement any large-scale health insurance program, in particular, any government-funded healthcare programs. This platform has the transformative vision of enabling both public and private actors to implement insurance schemes in an automated, data-driven manner through open APIs " (NITI Aayog2018). A post on the iSPIRT website further explains the centrality of this Coverage and Claims platform in enabling a highly personalised medical insurance market in India: “This component will not only bring down the cost of processing a claim but ... increased access to information about an individual’s health and claims history ... will also enable the creation of personalised, sachet-sized insurance policies." These data-driven customised insurance policies are expected to generate “care policies that are not only personalized in nature but that also incentivize good healthcare practices amongst consumers and providers … [and] use of techniques from microeconomics to manage incentives for care providers, and those from behavioural economics to incentivise consumers" (Productnation Network 2019). The Coverage and Claims platform, and especially the Policy (generation) Engine that it will contain, is aimed at intensive financialisation of personal healthcare expenses, and extensive experiments with designing personalised nudges to shape the demand behaviour of consumers.</p>
<p>The imagination of healthcare the NHS demonstrates is one where broadening health insurance coverage is equated to providing equitable healthcare and as a panacea for the public healthcare sector. The first phase of this push towards better healthcare provision is to focus on contextualising the historical socio-economic divide. The next phase is characterised by digitalisation: the introduction of ICT to bridge the socio-economic divide in healthcare provision. In this process, the resulting data divide has been invisibilised in reframing better healthcare as an insurance problem for which data needs to be generated. Each policy innovation is then characterised by further marginalisation of those that were originally identified as underserved. This is a result of increasing repercussions of the data-divide, with access to benefits increasingly being mediated by technology.</p>
<h3><strong>Concluding Remarks</strong></h3>
<blockquote>The idea that any person in India can go to any health service provider/ practitioner, any diagnostic center or any pharmacy and yet be able to access and have fully integrated and always available health records in an electronic format is not only empowering but also the vision for efficient 21st century healthcare delivery.<br />
— Ministry of Health and Family Welfare, Electronic Health Record Standards For India (2013)</blockquote>
<p>The objective of health data collection has evolved over the course of the institution of the HIS in 2011, to the development of the NHPS and National Health Policy in 2017. What began as a solution to measure and address gaps in access and quality in healthcare provisioning through data analysis has morphed into data centralisation and insurance coverage. Shifting goalposts can also be found in the objectives behind introducing digital systems to collect data.</p>
<p>In recent iterations of the healthcare imaginary, such as the IHIP and the NHS, data ownership by the beneficiaries is stressed upon. In the absence of a rights-based framework dictating the use of data, the role of ownership should be interrogated, especially in the context of a prevalent data divide (Tisne 2019). The legitimisation of data capture can be seen in the emergence of opt-in models of consent, data fiduciaries managing consent on the data subject’s behalf, etc. (Zuboff 2019).</p>
<p>This framing forecloses a discussion about the quality and kind of data being used. The push towards datafication needs to be questioned for its re-indexing of categorical meaning away from the complexities of narrative, context and history (Cheney-Lippold 2018). Instead, the proposed solution is one that stores datafied elements within a closed set (reproductive health= [abortion, aids, contraceptive,...vaccination, womb]). While this set may be editable, so new interpretations can be codified, it inherently remains stable, assuming a static relationship between words and meaning. Health is then treated as having an empirically definable meaning, thus losing the dynamism of what the health and wellness discourse could entail.</p>
<p>It has been historically demonstrated in the Indian context that multiple tools and databases for health data management are a barrier to an efficient HIS. However, generating centralised or federated databases without addressing concerns in data flows, quality, uses in existing data structures, and the digital divide across health workers and beneficiaries alike will lead to the amplification of existing exclusions in data and, consequently, service provisioning.</p>
<h3><strong>Acknowledgements</strong></h3>
<p>The author would like to express his gratitude to Sumandro Chattapadhyay and Ambika Tandon for their inputs and editorial work on this contribution. This work was supported by the Big Data for Development Network established by International Development Research Centre (Canada).</p>
<h3><strong>Notes</strong></h3>
<p><strong>[1]</strong> Section 2 (a) of the Clinical Establishments (Registration and Regulation) Act, 2010: A hospital, maternity home, nursing home, dispensary, clinic, sanatorium or institution by whatever name called that offers services, facilities requiring diagnosis, treatment or care for illness, injury, deformity, abnormality or pregnancy in any recognised system of medicine established and administered or maintained by any person or body of persons, whether incorporated or not.</p>
<p><strong>[2]</strong> The National Health Stack, then, is the latest manifestation of the Indian government’s push for a “Digital India.” A key component of Digital India has been e-governance, financial inclusion, and digitisation of transaction services. The nudge towards cashless modes of transaction and delivery, also accelerated by India’s demonetisation drive in November 2016, has led to rapid uptake of digital payment services in particular, and that of the IndiaStack initiative in general. Developed by iSPIRT, IndiaStack (https://indiastack.org/) aspires to transform service delivery by public and private actors alike through its “presence-less, paperless, and cashless” mandate.</p>
<h3><strong>References</strong></h3>
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<p>Bach, Peter, Hoangmai Pham, Deborah Schrag, Ramsey Tate and J Lee Hargraves (2004): “Primary Care Physicians Who Treat Blacks and Whites,” New England Journal of Medicine, Vol 351, pp 575–84.</p>
<p>Cheney-Lippold, John (2018): We Are Data: Algorithms and the Making of Our Digital Selves, New Delhi: Sage.</p>
<p>Daly, Jeanette, Buckwalter Kathleen and Meridean Maas (2002): “Written and Computerized Care Plans,” Journal of Gerontological Nursing, Vol 28, No 9, pp 14–23.</p>
<p>EMR Standards Committee (2013): “Recommendations on Electronic Medical Records Standards in India,” Ministry of Health and Family Welfare, Government of India, New Delhi, https://mohfw.gov.in/sites/default/files/24539108839988920051EHR%20Standards-v5%20Apr%202013.pdf.</p>
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<p>Jha, Ashish, Catherine DesRoches, Eric Campbell, Karen Donelan, Sowmya Rao, Timothy Ferris, Alexandra Shields, Sarah Rosenbaum and David Blumenthal (2009): "Use of Electronic Health Records in U.S. Hospitals," New England Journal of Medicine, Vol 360 No 16, pp 1628–1638.</p>
<p>Jyoti, Archana (2018): “States Give Clinical Establishment Act Cold Shoulder," Pioneer, https://www.dailypioneer.com/2018/india/states-give-clinical-establishment-act-cold-shoulder.html.</p>
<p>Kandhari, Ruhi (2017): “Why a Backdoor Push Towards eHealth,” Ken, https://the-ken.com/story/why-backdoor-push-towards-ehealth/.</p>
<p>Kovner, Christine, Lynda Schuchman and Catherin Mallard (1997): “The Application of Pen-Based Computer Technology to Home Health Care,” CIN: Computers, Informatics and Nursing, Vol 15, No 5, pp 237–44.</p>
<p>Krishnamurthy, R (2018): “Integrated Health Information Platform for Integrated Disease Surveillance Program,” Training of the Trainer Workshop, World Health Organisation, New Delhi, https://idsp.nic.in/WriteReadData/IHIP/IHIP%20ToT-Overview-Presentation.pdf.</p>
<p>Kuperman, Gilad and Richard Gibson (2003): “Computer Physician Order Entry: Benefits, Costs, and Issues,” Annals of Internal Medicine, Vol 139 No 1, pp 31–9.</p>
<p>Leung, Gabriel, Philip Yu, Irene Wong, Janice Johnston and Keith Tin (2003): “Incentives and Barriers That Influence Clinical Computerization in Hong Kong: A Population-based Physician Survey,” Journal of the American Medical Informatics Association, Vol 10 No 2, pp 201–12.</p>
<p>McGinn Carrie Anna, Sonya Grenier, Julie Duplantie, Nicola Shaw, Claude Sicotte, Luc Mathieu, Yvan Leduc, France Légaré and Marie-Pierre Gagnon (2011): “Comparison of User Groups' Perspectives of Barriers and Facilitators to Implementing Electronic Health Records: A Systematic Review,” BMC Medicine, Vol 9 No 46.</p>
<p>Miklin, Daniel, Sameera Vangara, Alan Delamater and Kenneth Goodman (2019): “Understanding of and Barriers to Electronic Health Record Patient Portal Access in a Culturally Diverse Pediatric Population,” JMIR Medical Informatics, Vol 7, No 2.</p>
<p>Ministry of Finance (2018): “Budget 2018-19: Speech of Arun Jaitley,” New Delhi, https://www.indiabudget.gov.in/ub2018-19/bs/bs.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2008): "4 Years of Transforming India-Healthcare for All," New Delhi. https://mohfw.gov.in/ebook2018/gvtbook.html.</p>
<p>Ministry of Health and Family Welfare, Government of India (2013): “Electronic Health Record Standards For India,” Government of India, New Delhi, https://www.nhp.gov.in/NHPfiles/ehr_2013.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2017): Request for Proposal: Development and Implementation of Integrated Health Information Platform (IHIP), Centre for Health Informatics, National Institute of Health and Family Welfare, New Delhi, https://nhp.gov.in/NHPfiles/IHIP_RFP%20.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2018): “IDSP Segment of Integrated Health Information Platform,” New Delhi, https://idsp.nic.in/index4.php?lang=1&level=0&linkid=454&lid=3977.</p>
<p>National Health Authority (nd): “About Pradhan Mantri Jan Arogya Yojana (PM-JAY) | Ayushmaan Bharat,” https://www.pmjay.gov.in/about-pmjay.</p>
<p>NITI Aayog (2018): “National Health Stack- Strategy and Approach,” NITI Aayog, New Delhi, http://www.niti.gov.in/writereaddata/files/document_publication/NHS-Strategy-and-Approach-Document-for-consultation.pdf.</p>
<p>Organisation for Economic Co-operation and Development (2013): “Strengthening Health Information Infrastructure for Health Care Quality Governance: Good Practices, New Opportunities and Data Privacy Protection Challenges,” OECD Health Policy Studies, Paris, OECD Publishing, https://read.oecd-ilibrary.org/social-issues-migration-health/strengthening-health-information-infrastructure-for-health-care-quality-governance_9789264193505-en.</p>
<p>Poon, Eric, David Blumenthal, Tonushree Jaggi, Melissa Honour, David Bates and Rainu Kaushal (2004): “Overcoming Barriers to Adopting and Implementing Computerized Physician Order Entry Systems in U.S. Hospitals,” Health Affairs, Vol 23 No 4, pp 184–90.</p>
<p>Productnation Network (2019): “India’s Health Leapfrog–Towards A Holistic Healthcare Ecosystem,” iSpirt, https://pn.ispirt.in/towards-a-holistic-healthcare-ecosystem/.</p>
<p>Rathi, Aayush and Ambika Tandon (2019): “Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?” EPW Engage, https://www.epw.in/engage/article/data-infrastructures-inequities-why-does-reproductive-health-surveillance-india-need-urgent-attention.</p>
<p>Sequist, Thomas, Theresa Cullen, Howard Hays, Maile Taualii, Steven Simon, and David Bates (2007): “Implementation and Use of an Electronic Health Record Within the Indian Health Service,” Journal of the American Medical Informatics Association, Vol 14, No 2, pp 191–97.</p>
<p>World Bank (nd): Physicians (per 1,000 people) | Data, https://data.worldbank.org/indicator/SH.MED.PHYS.ZS.</p>
<p>Tierney, William et al. (2010): “Experience Implementing Electronic Health Records in Three East African Countries,” Studies in Health Technology and Informatics, Vol 160, No 1, pp 371–75.</p>
<p>Tisne, Martin (2018): “It’s Time for a Bill of Data Rights,” MIT Technology Review, https://www.technologyreview.com/s/612588/its-time-for-a-bill-of-data-rights/.</p>
<p>World Health Organization (2016): “Global Diffusion of eHealth: Making Universal Health Coverage Achievable,” https://apps.who.int/iris/bitstream/handle/10665/252529/9789241511780-eng.pdf;jsessionid=9DD5F8603C67EEF35549799B928F3541?sequence=1.</p>
<p>Zuboff, Soshana (2019): The Age of Surveillance Capitalism, New York: PublicAffairs.</p>
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For more details visit <a href='http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof'>http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof</a>
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No publisheraayushEHRBig DataBig Data for DevelopmentResearchBD4DHealthcareResearchers at Work2019-12-30T17:58:00ZBlog EntryThe Mother and Child Tracking System - understanding data trail in the Indian healthcare systems
http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare
<b>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. In this article, published by Privacy International, Ambika Tandon presents some findings from a recently concluded case study of the MCTS as an example of public data-driven initiatives in reproductive health in India. </b>
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<h4>This article was first published by <a href="https://privacyinternational.org/news-analysis/3262/mother-and-child-tracking-system-understanding-data-trail-indian-healthcare" target="_blank">Privacy International</a>, on October 17, 2019</h4>
<h4>Case study of MCTS: <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">Read</a></h4>
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<p>On October 17th 2019, the UN Special Rapporteur (UNSR) on Extreme Poverty and Human Rights, Philip Alston, released his thematic report on digital technology, social protection and human rights. Understanding the impact of technology on the provision of social protection – and, by extent, its impact on people in vulnerable situations – has been part of the work the Centre for Internet and Society (CIS) and Privacy International (PI) have been doing.</p>
<p>Earlier this year, <a href="https://privacyinternational.org/advocacy/2996/privacy-internationals-submission-digital-technology-social-protection-and-human" target="_blank">PI responded</a> to the UNSR's consultation on this topic. We highlighted what we perceived as some of the most pressing issues we had observed around the world when it comes to the use of technology for the delivery of social protection and its impact on the right to privacy and dignity of benefit claimants.</p>
<p>Among them, automation and the increasing reliance on AI is a topic of particular concern - countries including Australia, India, the UK and the US have already started to adopt these technologies in digital welfare programmes. This adoption raises significant concerns about a quickly approaching future, in which computers decide whether or not we get access to the services that allow us to survive. There's an even more pressing problem. More than a few stories have emerged revealing the extent of the bias in many AI systems, biases that create serious issues for people in vulnerable situations, who are already exposed to discrimination, and made worse by increasing reliance on automation.</p>
<p>Beyond the issue of AI, we think it is important to look at welfare and automation with a wider lens. In order for an AI to function it needs to be trained on a dataset, so that it can understand what it is looking for. That requires the collection large quantities of data. That data would then be used to train and AI to recognise what fraudulent use of public benefits would look like. That means we need to think about every data point being collected as one that, in the long run, will likely be used for automation purposes.</p>
<p>These systems incentivise the mass collection of people's data, across a huge range of government services, from welfare to health - where women and gender-diverse people are uniquely impacted. CIS have been looking specifically at reproductive health programmes in India, work which offers a unique insight into the ways in which mass data collection in systems like these can enable abuse.</p>
<p>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. India’s health programme instituted such an information system in 2009, the Mother and Child Tracking System (MCTS), which is aimed at collecting data on maternal and child health. The Centre for Internet and Society, India, <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">undertook a case study of the MCTS</a> as an example of public data-driven initiatives in reproductive health. The case study was supported by the <a href="http://bd4d.net/" target="_blank">Big Data for Development network</a> supported by the International Development Research Centre, Canada. The objective of the case study was to focus on the data flows and architecture of the system, and identify areas of concern as newer systems of health informatics are introduced on top of existing ones. The case study is also relevant from the perspective of Sustainable Development Goals, which aim to rectify the tendency of global development initiatives to ignore national HIS and create purpose-specific monitoring systems.</p>
<p>After being launched in 2011, 120 million (12 crore) pregnant women and 111 million (11 crore) children have been registered on the MCTS as of 2018. The central database collects data on each visit of the woman from conception to 42 days postpartum, including details of direct benefit transfer of maternity benefit schemes. While data-driven monitoring is a critical exercise to improve health care provision, publicly available documents on the MCTS reflect the complete absence of robust data protection measures. The risk associated with data leaks are amplified due to the stigma associated with abortion, especially for unmarried women or survivors of rape.</p>
<p>The historical landscape of reproductive healthcare provision and family planning in India has been dominated by a target-based approach. Geared at population control, this approach sought to maximise family planning targets without protecting decisional autonomy and bodily privacy for women. At the policy level, this approach was shifted in favour of a rights-based approach to family planning in 1994. However, targets continue to be set for women’s sterilisation on the ground. Surveillance practices in reproductive healthcare are then used to monitor under-performing regions and meet sterilisation targets for women, this continues to be the primary mode of contraception offered by public family planning initiatives.</p>
<p>More recently, this database - among others collecting data about reproductive health - is adding biometric information through linkage with the Aadhaar infrastructure. This data adds to the sensitive information being collected and stored without adhering to any publicly available data protection practices. Biometric linkage is aimed to fulfill multiple functions - primarily authentication of welfare beneficiaries of the national maternal benefits scheme. Making Aadhaar details mandatory could directly contribute to the denial of service to legitimate patients and beneficiaries - as has already been seen in some cases.</p>
<p>The added layer of biometric surveillance also has the potential to enable other forms of abuse of privacy for pregnant women. In 2016, the union minister for Women and Child Development under the previous government suggested the use of strict biometric-based monitoring to discourage gender-biased sex selection. Activists critiqued the policy for its paternalistic approach to reduce the rampant practice of gender-biased sex selection, rather than addressing the root causes of gender inequality in the country.</p>
<p>There is an urgent need to rethink the objectives and practices of data collection in public reproductive health provision in India. Rather than continued focus on meeting high-level targets, monitoring systems should enable local usage and protect the decisional autonomy of patients. In addition, the data protection legislation in India - expected to be tabled in the next session in parliament - should place free and informed consent, and informational privacy at the centre of data-driven practices in reproductive health provision.</p>
<p>This is why the systematic mass collection of data in health services is all the more worrying. When the collection of our data becomes a condition for accessing health services, it is not only a threat to our right to health that should not be conditional on data sharing but also it raises questions as to how this data will be used in the age of automation.</p>
<p>This is why understanding what data is collected and how it is collected in the context of health and social protection programmes is so important.</p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare'>http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare</a>
</p>
No publisherambikaBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceResearchBD4DHealthcareBig Data for Development2019-12-30T17:18:05ZBlog EntryBig Data and Reproductive Health in India: A Case Study of the Mother and Child Tracking System
http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts
<b>In this case study undertaken as part of the Big Data for Development (BD4D) network, Ambika Tandon evaluates the Mother and Child Tracking System (MCTS) as data-driven initiative in reproductive health at the national level in India. The study also assesses the potential of MCTS to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data.</b>
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<h4>Case study: <a href="https://github.com/cis-india/website/raw/master/bd4d/CIS_CaseStudy_AT_BigDataReproductiveHealthMCTS.pdf" target="_blank">Download</a> (PDF)</h4>
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<h3>Introduction</h3>
<p>The reproductive health information ecosystem in India comprises of a range of different databases across state and national levels. These collect data through a combination of manual and digital tools. Two national-level databases have been launched by the Ministry of Health and Family Welfare - the Health Management Information System (HMIS) in 2008, and the MCTS in 2009. 4 The MCTS focuses on collecting data on maternal and child health. It was instituted due to reported gaps in the HMIS, which records monthly data across health programmes including reproductive health. There are several other state-level initiatives on reproductive health data that have either been subsumed into, or run in
parallel with, the MCTS.</p>
<p>With this case study, we aim to evaluate the MCTS as data-driven initiative in reproductive health at the national level. It will also assess its potential to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data. The methodology for the case study involved a desk-based review of existing literature on the use of health information systems globally, as well as analysis of government reports, journal articles, media coverage, policy documents, and other material on the MCTS.</p>
<p>The first section of this report details the theoretical framing of the case study, drawing on the feminist critique of reproductive data systems. The second section maps the current landscape of reproductive health data produced by the state in India, with a focus on data flows, and barriers to data collection and analysis at the local and national level. The case of abortion data is used to further the argument of flawed data collection systems at the
national level. Section three briefly discusses the state’s imagination of reproductive health policy and the role of data systems through a discussion on the National Health Policy, 2017 and the National Health Stack, 2018. Finally, we make some policy recommendations and identify directions for future research, taking into account the ongoing shift towards big data globally to democratise reproductive healthcare.</p>
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For more details visit <a href='http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts'>http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts</a>
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No publisherambikaBig DataData SystemsResearchers at WorkReproductive and Child HealthResearchFeaturedPublicationsBD4DHealthcareBig Data for Development2019-12-06T04:57:55ZBlog EntryData Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?
http://editors.cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india
<b>In order to bring out certain conceptual and procedural problems with health monitoring in the Indian context, this article by Aayush Rathi and Ambika Tandon posits health monitoring as surveillance and not merely as a “data problem.” Casting a critical feminist lens, the historicity of surveillance practices unveils the gendered power differentials wedded into taken-for-granted “benign” monitoring processes. The unpacking of the Mother and Child Tracking System and the National Health Stack reveals the neo-liberal aspirations of the Indian state. </b>
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<p><em>The article was first published by <a href="https://www.epw.in/engage/article/data-infrastructures-inequities-why-does-reproductive-health-surveillance-india-need-urgent-attention" target="_blank">EPW Engage, Vol. 54, Issue No. 6</a>, on 9 February 2019.</em></p>
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<h3><strong>Framing Reproductive Health as a Surveillance Question</strong></h3>
<p>The approach of the postcolonial Indian state to healthcare has been Malthusian, with the prioritisation of family planning and birth control (Hodges 2004). Supported by the notion of socio-economic development arising out of a “modernisation” paradigm, the target-based approach to achieving reduced fertility rates has shaped India’s reproductive and child health (RCH) programme (Simon-Kumar 2006).</p>
<p>This is also the context in which India’s abortion law, the Medical Termination of Pregnancy (MTP) Act, was framed in 1971, placing the decisional privacy of women seeking abortions in the hands of registered medical practitioners. The framing of the MTP act invisibilises females seeking abortions for non-medical reasons within the legal framework. The exclusionary provisions only exacerbated existing gaps in health provisioning, as access to safe and legal abortions had already been curtailed by severe geographic inequalities in funding, infrastructure, and human resources. The state has concomitantly been unable to meet contraceptive needs of married couples or reduce maternal and infant mortality rates in large parts of the country, mediating access along the lines of class, social status, education, and age (Sanneving et al 2013).</p>
<p>While the official narrative around the RCH programme transitioned to focus on universal access to healthcare in the 1990s, the target-based approach continues to shape the reality on the ground. The provision of reproductive healthcare has been deeply unequal and, in some cases, in hospitals. These targets have been known to be met through the practice of forced, and often unsafe, sterilisation, in conditions of absence of adequate provisions or trained professionals, pre-sterilisation counselling, or alternative forms of contraception (Sama and PLD 2018). Further, patients have regularly been provided cash incentives, foreclosing the notion of free consent, especially given that the target population of these camps has been women from marginalised economic classes in rural India.</p>
<p>Placing surveillance studies within a feminist praxis allows us to frame the reproductive health landscape as more than just an ill-conceived, benign monitoring structure. The critical lens becomes useful for highlighting that taken-for-granted structures of monitoring are wedded with power differentials: genetic screening in fertility clinics, identification documents such as birth certificates, and full-body screeners are just some of the manifestations of this (Adrejevic 2015). Emerging conversations around feminist surveillance studies highlight that these data systems are neither benign nor free of gendered implications (Andrejevic 2015). In continual remaking of the social, corporeal body as a data actor in society, such practices render some bodies normative and obfuscate others, based on categorisations put in place by the surveiller.</p>
<p>In fact, the history of surveillance can be traced back to the colonial state where it took the form of systematic sexual and gendered violence enacted upon indigenous populations in order to render them compliant (Rifkin 2011; Morgensen 2011). Surveillance, then, manifests as a “scientific” rationalisation of complex social hieroglyphs (such as reproductive health) into formats enabling administrative interventions by the modern state. Lyon (2001) has also emphasised how the body emerged as the site of surveillance in order for the disciplining of the “irrational, sensual body”—essential to the functioning of the modern nation-state—to effectively happen.</p>
<h3><strong>Questioning the Information and Communications Technology for Development (ICT4D) and Big Data for Development (BD4D) Rhetoric</strong></h3>
<p>Information and Communications Technology (ICT) and data-driven approaches to the development of a robust health information system, and by extension, welfare, have been offered as solutions to these inequities and exclusions in access to maternal and reproductive healthcare in the country.</p>
<p>The move towards data-driven development in the country commenced with the introduction of the Health Management Information System in Andhra Pradesh in 2008, and the Mother and Child Tracking System (MCTS) nationally in 2011. These are reproductive health information systems (HIS) that collect granular data about each pregnancy from the antenatal to the post-natal period, at the level of each sub-centre as well as primary and community health centre. The introduction of HIS comprised cross-sectoral digitisation measures that were a part of the larger national push towards e-governance; along with health, thirty other distinct areas of governance, from land records to banking to employment, were identified for this move towards the digitalised provisioning of services (MeitY 2015).</p>
<p>The HIS have been seen as playing a critical role in the ecosystem of health service provision globally. HIS-based interventions in reproductive health programming have been envisioned as a means of: (i) improving access to services in the context of a healthcare system ridden with inequalities; (ii) improving the quality of services provided, and (iii) producing better quality data to facilitate the objectives of India’s RCH programme, including family planning and population control. Accordingly, starting 2018, the MCTS is being replaced by the RCH portal in a phased manner. The RCH portal, in areas where the ANMOL (ANM Online) application has been introduced, captures data real-time through tablets provided to health workers (MoHFW 2015).</p>
<p>A proposal to mandatorily link the Aadhaar with data on pregnancies and abortions through the MCTS/RCH has been made by the union minister for Women and Child Development as a deterrent to gender-biased sex selection (Tembhekar 2016). The proposal stems from the prohibition of gender-biased sex selection provided under the Pre-Conception and Pre-Natal Diagnostics Techniques (PCPNDT) Act, 1994. The approach taken so far under the PCPNDT Act, 2014 has been to regulate the use of technologies involved in sex determination. However, the steady decline in the national sex ratio since the passage of the PCPNDT Act provides a clear indication that the regulation of such technology has been largely ineffective. A national policy linking Aadhaar with abortions would be aimed at discouraging gender-biased sex selection through state surveillance, in direct violation of a female’s right to decisional privacy with regards to their own body.</p>
<p>Linking Aadhaar would also be used as a mechanism to enable direct benefit transfer (DBT) to the beneficiaries of the national maternal benefits scheme. Linking reproductive health services to the Aadhaar ecosystem has been critiqued because it is exclusionary towards women with legitimate claims towards abortions and other reproductive services and benefits, and it heightens the risk of data breaches in a cultural fabric that already stigmatises abortions. The bodies on which this stigma is disproportionately placed, unmarried or disabled females, for instance, experience the harms of visibility through centralised surveillance mechanisms more acutely than others by being penalised for their deviance from cultural expectations. This is in accordance with the theory of "data extremes,” wherein marginalised communities are seen as living on the extremes of data capture, leading to a data regime that either refuses to recognise them as legitimate entities or subjects them to overpolicing in order to discipline deviance (Arora 2016). In both developed and developing contexts, the broader purpose of identity management has largely been to demarcate legitimate and illegitimate actors within a population, either within the framework of security or welfare.</p>
<h3><strong>Potential Harms of the Data Model of Reproductive Health Provisioning</strong></h3>
<p>Informational privacy and decisional privacy are critically shaped by data flows and security within the MCTS/RCH. No standards for data sharing and storage, or anonymisation and encryption of data have been implemented despite role-based authentication (NHSRC and Taurus Glocal 2011). The risks of this architectural design are further amplified in the context of the RCH/ANMOL where data is captured real-time. In the absence of adequate safeguards against data leaks, real-time data capture risks the publicising of reproductive health choices in an already stigmatised environment. This opens up avenues for further dilution of autonomy in making future reproductive health choices.</p>
<p>Several core principles of informational privacy, such as limitations regarding data collection and usage, or informed consent, also need to be reworked within this context.<sup>[1]</sup> For instance, the centrality of the requirement of “free, informed consent” by an individual would need to be replaced by other models, especially in the context of reproductive health of rape survivors who are vulnerable and therefore unable to exercise full agency. The ability to make a free and informed choice, already dismantled in the context of contemporary data regimes, gets further precluded in such contexts. The constraints on privacy in decisions regarding the body are then replicated in the domain of reproductive data collection.</p>
<p>What is uniform across these digitisation initiatives is their treatment of maternal and reproductive health as solely a medical event, framed as a data scarcity problem. In doing so, they tend to amplify the understanding of reproductive health through measurable indicators that ignore social determinants of health. For instance, several studies conducted in the rural Indian context have shown that the degree of women’s autonomy influences the degree of usage of pregnancy care, and that the uptake of pregnancy care was associated with village-level indicators such as economic development, provisioning of basic infrastructure and social cohesion. These contextual factors get overridden in pervasive surveillance systems that treat reproductive healthcare as comprising only of measurable indicators and behaviours, that are dependent on individual behaviour of practitioners and women themselves, rather than structural gaps within the system.</p>
<p>While traditionally associated with state governance, the contemporary surveillance regime is experienced as distinct from its earlier forms due to its reliance on a nexus between surveillance by the state and private institutions and actors, with both legal frameworks and material apparatuses for data collection and sharing (Shepherd 2017). As with historical forms of surveillance, the harms of contemporary data regimes accrue disproportionately among already marginalised and dissenting communities and individuals. Data-driven surveillance has been critiqued for its excesses in multiple contexts globally, including in the domains of predictive policing, health management, and targeted advertising (Mason 2015). In the attempts to achieve these objectives, surveillance systems have been criticised for their reliance on replicating past patterns, reifying proximity to a hetero-patriarchal norm (Haggerty and Ericson 2000). Under data-driven surveillance systems, this proximity informs the preexisting boxes of identity for which algorithmic representations of the individual are formed. The boxes are defined contingent on the distinct objectives of the particular surveillance project, collating disparate pieces of data flows and resulting in the recasting of the singular offline self into various 'data doubles' (Haggerty and Ericson 2000). Refractive, rather than reflective, the data doubles have implications for the physical, embodied life of individual with an increasing number of service provisioning relying on the data doubles (Lyon 2001). Consider, for instance, apps on menstruation, fertility, and health, and wearables such as fitness trackers and pacers, that support corporate agendas around what a woman’s healthy body should look, be or behave like (Lupton 2014). Once viewed through the lens of power relations, the fetishised, apolitical notion of the data “revolution” gives way to what we may better understand as “dataveillance.”</p>
<h3><strong>Towards a Networked State and a Neo-liberal Citizen</strong></h3>
<p>Following in this tradition of ICT being treated as the solution to problems plaguing India’s public health information system, a larger, all-pervasive healthcare ecosystem is now being proposed by the Indian state (NITI Aayog 2018). Termed the National Health Stack, it seeks to create a centralised electronic repository of health records of Indian citizens with the aim of capturing every instance of healthcare service usage. Among other functions, it also envisions a platform for the provisioning of health and wellness-based services that may be dispensed by public or private actors in an attempt to achieve universal health coverage. By allowing private parties to utilise the data collected through pullable open application program interfaces (APIs), it also fits within the larger framework of the National Health Policy 2017 that envisions the private sector playing a significant role in the provision of healthcare in India. It also then fits within the state–private sector nexus that characterises dataveillance. This, in turn, follows broader trends towards market-driven solutions and private financing of health sector reform measures that have already had profound consequences on the political economy of healthcare worldwide (Joe et al 2018).</p>
<p>These initiatives are, in many ways, emblematic of the growing adoption of network governance reform by the Indian state (Newman 2001). This is a stark shift from its traditional posturing as the hegemonic sovereign nation state. This shift entails the delayering from large, hierarchical and unitary government systems to horizontally arranged, more flexible, relatively dispersed systems.<sup>[2]</sup> The former govern through the power of rules and law, while the latter take the shape of self-regulating networks such as public–private contractual arrangements (Snellen 2005). ICTs have been posited as an effective tool in enabling the transition to network governance by enhancing local governance and interactive policymaking enabling the co-production of knowledge (Ferlie et al 2011). The development of these capabilities is also critical to addressing “wicked problems” such as healthcare (Rittel and Webber 1973).<sup>[3]</sup> The application of the techno-deterministic, data-driven model to reproductive healthcare provision, then, resembles a fetishised approach to technological change. The NHSRC describes this as the collection of data without an objective, leading to a disproportional burden on data collection over use (NHSRC and Taurus Glocal 2011).</p>
<p>The blurring of the functions of state and private actors is reflective of the neo-liberal ethic, which produces new practices of governmentality. Within the neo-liberal framework of reproductive healthcare, the citizen is constructed as an individual actor, with agency over and responsibility for their own health and well-being (Maturo et al 2016).</p>
<h3><strong>“Quantified Self” of the Neo-liberal Citizen</strong></h3>
<p>Nowhere can the manifestation of this neo-liberal citizen can be seen as clearly as in the “quantified self” movement. The quantified self movement refers to the emergence of a whole range of apps that enable the user to track bodily functions and record data to achieve wellness and health goals, including menstruation, fertility, pregnancies, and health indicators in the mother and baby. Lupton (2015) labels this as the emergence of the “digitised reproductive citizen,” who is expected to be attentive to her fertility and sexual behaviour to achieve better reproductive health goals. The practice of collecting data around reproductive health is not new to the individual or the state, as has been demonstrated by the discussion above. What is new in this regime of datafication under the self-tracking movement is the monetisation of reproductive health data by private actors, the labour for which is performed by the user. Focusing on embodiment draws attention to different kinds of exploitation engendered by reproductive health apps. Not only is data about the body collected and sold, the unpaid labour for collection is extracted from the user. The reproductive body can then be understood as a cyborg, or a woman-machine hybrid, systematically digitising its bodily functions for profit-making within the capitalist (re)production machine (Fotoloulou 2016). Accordingly, all major reproductive health tracking apps have a business model that relies on selling information about users for direct marketing of products around reproductive health and well-being (Felizi and Varon nd).</p>
<p>As has been pointed out in the case of big data more broadly, reproductive health applications (apps) facilitate the visibility of the female reproductive body in the public domain. Supplying anonymised data sets to medical researchers and universities fills some of the historical gaps in research around the female body and reproductive health. Reproductive and sexual health tracking apps globally provide their users a platform to engage with biomedical information around sexual and reproductive health. Through group chats on the platform, they are also able to engage with experiential knowledge of sexual and reproductive health. This could also help form transnational networks of solidarity around the body and health (Fotopoulou 2016).</p>
<p style="text-align: justify;">This radical potential of network-building around reproductive and sexual health is, however, tempered to a large extent by the reconfiguration of gendered stereotypes through these apps. In a study on reproductive health apps on Google Play Store, Lupton (2014) finds that products targeted towards female users are marketed through the discourse of risk and vulnerability, while those targeted towards male users are framed within that of virility. Apart from reiterating gendered stereotypes around the male and female body, such a discourse assumes that the entire labour of family planning is performed by females. This same is the case with the MCTS/RCH.</p>
<p>Technological interventions such as reproductive health apps as well as HIS are based on the assumption that females have perfect control over decisions regarding their own bodies and reproductive health, despite this being disproved in India. The Guttmacher Institute (2014) has found that 60% of women in India report not having control over decisions regarding their own healthcare. The failure to account for the husband or the family as stakeholder in decision-making around reproductive health has been a historical failure of the family planning programme in India, and is now being replicated in other modalities. This notion of an autonomous citizen who is able to take responsibility of their own reproductive health and well-being does not hold true in the Indian context. It can even be seen as marginalising females who have already been excluded from the reproductive health system, as they are held responsible for their own inability to access healthcare.</p>
<h3><strong>Concluding Remarks</strong></h3>
<p>The interplay that emerges between reproductive health surveillance and data infrastructures is a complex one. It requires the careful positioning of the political nature of data collection and processing as well as its hetero-patriarchal and colonial legacies, within the need for effective utilisation of data for achieving developmental goals. Assessing this discourse through a feminist lens identifies the web of power relations in data regimes. This problematises narratives of technological solutions for welfare provision.</p>
<p>The reproductive healthcare framework in India then offers up a useful case study to assess these concerns. The growing adoption of ICT-based surveillance tools to equalise access to healthcare needs to be understood in the socio-economic, legal, and cultural context where these tools are being implemented. Increased surveillance has historically been associated with causing the structural gendered violence that it is now being offered as a solution to. This is a function of normative standards being constructed for reproductive behaviour that necessarily leave out broader definitions of reproductive health and welfare when viewed through a feminist lens. Within the larger context of health policymaking in India, moves towards privatisation then demonstrate the peculiarity of dataveillance as it functions through an unaccountable and pervasive overlapping of state and private surveillance practises. It remains to be seen how these trends in ICT-driven health policies affect access to reproductive rights and decisional privacy for millions of females in India and other parts of the global South.</p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india'>http://editors.cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india</a>
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No publisherAayush Rathi and Ambika TandonBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceResearchBD4DHealthcareSurveillanceBig Data for Development2019-12-30T16:44:32ZBlog EntryNational Health Stack: Data For Data’s Sake, A Manmade Health Hazard
http://editors.cis-india.org/internet-governance/blog/bloomberg-quint-murali-neelakantan-swaraj-barooah-swagam-dasgupta-torsha-sarkar-august-14-2018-national-health-stack-data-for-datas-sake-a-manmade-health-hazard
<b>On Oct. 5, 2017, an HIV positive woman was denied admission in Hyderabad’s Osmania General Hospital even though she was entitled to free treatment under India’s National AIDS Control Organisation programme. Another incident around the same time witnessed a 24-year-old pregnant woman at Tikamgarh district hospital in Madhya Pradesh being denied treatment by hospital doctors once she tested positive for HIV. The patient reportedly delivered the twins outside the maternity ward after she was turned away by the hospital, but her newborn twin girls died soon after.</b>
<p style="text-align: justify; ">The op-ed was <a class="external-link" href="https://www.bloombergquint.com/opinion/2018/08/14/data-for-datas-sake-a-manmade-health-hazard#gs.bT20zK4">published in Bloomberg Quint</a> on August 14, 2018.</p>
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<p style="text-align: justify; ">Apart from facing the severity of their condition, patients afflicted with diseases such as HIV, tuberculosis, and mental illnesses, are often subject to social stigma, sometimes even leading to the denial of medical treatment. Given this grim reality would patients want their full medical history in a database?</p>
<p style="text-align: justify; ">The ‘National Health Stack’ as described by the NITI Aayog in its consultation paper, is an ambitious attempt to build a digital infrastructure with a “deep understanding of the incentive structures prevalent in the Indian healthcare ecosystem”. If the government is to create a database of individuals’ health records, then it should appreciate the differential impact that it could have on the patients.</p>
<blockquote>The collection of health data, without sensitisation and accountability, has the potential to deny healthcare to the vulnerable.</blockquote>
<p style="text-align: justify; ">We have innumerable instances of denial of services due to Aadhaar and there is a real risk that another database will lead to more denial of access to the most vulnerable.</p>
<p style="text-align: justify; ">Earlier, we had outlined some key aspects of the NHS, the ‘world’s largest’ government-funded national healthcare scheme. Here we discuss some of the core technical issues surrounding the question of data collection, updating, quality, and utilisation.</p>
<h3>Resting On A Flimsy Foundation: The Unique Health ID</h3>
<p style="text-align: justify; ">The National Health Stack envisages the creation of a unique ID for registered beneficiaries in the system — a ‘Digital Health ID’. Upon the submission of a ‘national identifier’ and completion of the Know Your Customer process, the patient would be registered in the system, and a unique health ID generated.</p>
<p style="text-align: justify; ">This seemingly straightforward process rests on a very flimsy foundation. The base entry in the beneficiary registry would be linked to a ‘strong foundational ID’. Extreme care needs to be taken to ensure that this is not limited to an Aadhaar number. Currently, the unavailability of Aadhaar would not be a ground for denial of treatment to a patient only for their first visit; the patient must provide Aadhaar or an Aadhaar enrolment slip to avail treatment thereafter. This suggests that the national healthcare infrastructure will be geared towards increasing Aadhaar enrollment, with the unstated implication that healthcare is a benefit or subsidy — a largess of government, and not, as the courts have confirmed, a fundamental right.</p>
<blockquote style="text-align: justify; ">Not only is this project using government-funded infrastructure to deny its citizens the fundamental right to healthcare, it is using the desperate need of the vulnerable for healthcare to push the ‘Aadhaar’ agenda.</blockquote>
<p style="text-align: justify; ">Any pretence that Aadhaar is voluntary is slowly fading with the government mandating it at every step of our lives.</p>
<p style="text-align: justify; "><img alt="Aadhaar Seva kendra. (Source: Aadhaar Official Account/Facebook)&nbsp;" class="qt-image" src="https://images.assettype.com/bloombergquint%2F2018-01%2Fd7f4b53a-b069-484d-8c28-511c516aa4d5%2F3a192ed0-8a18-4518-95be-ac5234239e94.jpg?w=480&auto=format%2Ccompress" /></p>
<div class="visualClear" style="text-align: justify; ">Aadhaar Seva kendra. (Source: Aadhaar Official Account/Facebook</div>
<div class="visualClear" style="text-align: justify; "></div>
<h3>Is The Health ID An Effective And Unique Identifier?</h3>
<p style="text-align: justify; ">Even if we choose to look past the fact that the validity of Aadhaar is still pending the test of legality before the apex court, a foundational ID would mean that the data contained within that ID is unique, accurate, incorruptible, and cannot be misused. These principles, unfortunately, have been compromised by the UIDAI in the Aadhaar project with its lack of uniqueness of identity (i.e, fake IDs and duplicity), failure to authenticate identity, numerous alleged data leaks (‘alleged’ because UIDAI maintains that there haven’t been any leaks), lack of connectivity to be able to authenticate identity and numerous instances of inaccurate information which cannot be corrected.</p>
<p>Linking something as crucial and basic as healthcare data with such a database is a potential disaster.</p>
<p>There is a real risk that incorrect linking could cause deaths or inappropriate medical care.</p>
<h3>The High Risk Of Poor Quality Data</h3>
<p style="text-align: justify; ">The NITI Aayog paper envisages several expansive databases that are capable of being updated by different entities. It includes enrollment and updating processes but seems to assume that all these extra steps will be taken by all the relevant stakeholders and does not explain the motivation for stakeholders to do so.</p>
<p style="text-align: justify; ">In a country where government doctors, hospitals, wellness centres, etc are overburdened and understaffed, this reliance is simply not credible. For instance, all attributes within the registries are to be digitally signed by an authorised updater, there must be an audit trail for all changes made to the registries, and surveyors will be tasked with visiting providers in person to validate the data. Identifying these precautions as measures to assure accurate data is a great step towards building a national health database, but this seems an impossible task.</p>
<blockquote>Who are these actors and what will incentivise them to ensure the accuracy and integrity of data?</blockquote>
<p style="text-align: justify; ">In other words, what incentive and accountability structures will ensure that data entry and updating is accurate, and not approached from a more ‘<i>jugaad</i>’ ‘let’s just get this done for the sake of it’ attitude that permeates much of the country. How will patients have access to the database to be able to check its accuracy? Is it possible for a patient (who will presumably be ill) to gain easy access to an updater to change their data? If so, how? It is worth noting that the patient’s ‘right’ to check her data assumes that they have access to a computer that is connected to the internet as well as a good level of digital literacy, which is not the case in India for a significant section of the population. Even data portability loses its potential benefits if the quality of data on these registries is not reliable. In this case, healthcare providers will need to verify their patients’ health history using physical records instead, rendering the stack redundant.</p>
<p>Who will be liable to the patient for misdiagnosis based on the database?</p>
<p><img alt="A sonographic image is displayed on a monitor as a patient undergoes an ultrasound scan in Bikaner, Rajasthan, India. (Photographer: Prashanth Vishwanathan/Bloomberg)" class="qt-image" src="https://images.assettype.com/bloombergquint%2F2018-08%2Fe1659408-49ba-4188-b57e-aef377c69eb0%2Fm1291107.jpg?w=480&auto=format%2Ccompress" /></p>
<div class="visualClear">A sonographic image is displayed on a monitor as a patient undergoes an ultrasound scan in Bikaner, Rajasthan, India. (Photographer: Prashanth Vishwanathan/Bloomberg)</div>
<p style="text-align: justify; ">Leaving the question of accountability vague opens updaters to the possibility of facing dangerous and unnecessarily punitive measures in the future. The NITI Aayog paper fails to address this key issue which arose recently. Despite being a notifiable disease, there are reports that numerous doctors from the private sector failed to notify or update TB cases to the Ministry of Health and Family Welfare ostensibly on the grounds that they did not receive consent from their patients to share their information with the government. This was met with a harsh response from the government which stated that clinical establishment that failed to notify tuberculosis patients would face jail time. According to a few doctors, the government’s new move would coerce patients to go to ‘underground clinics’ to receive treatment discreetly and hence, would not solve the issue of TB.</p>
<blockquote>The document also offers no specific recommended procedures regarding how inaccurate entries will be corrected or deleted.</blockquote>
<p style="text-align: justify; ">It is then perhaps not a stretch to imagine that these scenarios would affect the quality of the data stored; defeating NITI Aayog’s objective of researchers using the stack for high-quality medical data.</p>
<p style="text-align: justify; ">The reason why the quality and integrity of data is at the head of the table is that all the proposed applications of the NHS (analytics, fraud detection etc.) assume a high quality, accurate dataset. At the same time, the enrolment process, updating process and disclosed measures to ensure data quality will effectively lead to poor quality data. If this is the case, then applications derived from the NHS dataset should assume an imperfect data, rather than an accurate dataset, which should make one wonder if no data is better than data that is certainly inaccurate.</p>
<h3>Lack Of Data Utilisation Guidelines</h3>
<p style="text-align: justify; ">Issues with data quality are exacerbated depending on how and where it is used, and who uses it. The paper has identified some users to be health-sector stakeholders such as healthcare providers (hospitals, clinics, labs etc), beneficiaries, doctors, insurers and accredited social health activists but misses laying down utilisation guidelines. The foresight to create a dataset that can be utilised by multiple actors for numerous applications is commendable, but potentially problematic -- especially if guidelines on how this data is to be used by stakeholders (especially the private sector) are ignored.</p>
<p style="text-align: justify; ">In order to bridge this knowledge gap, India has the opportunity to learn from the legal precedent set by foreign institutions. As an example, one could examine the Health Information Technology for Economic and Clinical Health Act (HITECH) and the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. which sets out strict guidelines for how businesses are to handle sensitive health data in order to maintain the individual’s privacy and security. It goes one step further to also lay down incentive and accountability structures in order that business associates necessarily report security breaches to their respective covered entities.</p>
<blockquote>If we do not take necessary precautions now, we not only run the risk of poor security and breach of privacy but of inaccurate data that renders the national health data repository a health risk for the whole patient population.</blockquote>
<p style="text-align: justify; ">There’s also the lack of clarity on who is meant to benefit from using such a database or whether the benefits are equal to all stakeholders, but more on that in a subsequent piece.</p>
<p style="text-align: justify; "><img alt="A medical team uses a glucometer to check the blood glucose level of a patient at a mobile clinic in Pancharala, on the outskirts of Bengaluru, India. (Photographer: Dhiraj Singh/Bloomberg)" class="qt-image" src="https://images.assettype.com/bloombergquint%2F2018-08%2F5e7e7b41-1513-4161-b195-5b8a77c6e4f1%2F314780590_1_20.jpg?w=480&auto=format%2Ccompress" /></p>
<div class="visualClear" style="text-align: justify; ">A medical team uses a glucometer to check the blood glucose level of a patient at a mobile clinic in Pancharala, on the outskirts of Bengaluru, India. (Photographer: Dhiraj Singh/Bloomberg)</div>
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<h3>It’s Your Recipe, You Try It First!</h3>
<p style="text-align: justify; ">If the NITI Aayog and the government are sure that there is a need for a national healthcare database, perhaps they can start using the Central Government Health Scheme (which includes all current and retired government employees and their families) as a pilot scheme for this. Once the software, database and the various apps built on it are found to be good value for money and patients benefit from excellent treatment all over the country, it could be expanded to those who use the Employees’ State Insurance system, and then perhaps to the armed forces. After all, these three groups already have a unique identifier and would benefit from the portability of healthcare records since they are likely to be transferred and posted all over the country. If, and only if, it works for these groups and the claimed benefits are observed, then perhaps it can be expanded to the rest of the country’s healthcare systems.</p>
<p><i>Murali Neelakantan is an expert in healthcare laws. Swaraj Barooah is Policy Director at The Centre for Internet and Society. Swagam Dasgupta and Torsha Sarkar are interns at The Centre for Internet and Society.</i></p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/bloomberg-quint-murali-neelakantan-swaraj-barooah-swagam-dasgupta-torsha-sarkar-august-14-2018-national-health-stack-data-for-datas-sake-a-manmade-health-hazard'>http://editors.cis-india.org/internet-governance/blog/bloomberg-quint-murali-neelakantan-swaraj-barooah-swagam-dasgupta-torsha-sarkar-august-14-2018-national-health-stack-data-for-datas-sake-a-manmade-health-hazard</a>
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No publisherMurali Neelakantan, Swaraj Barooah, Swagam Dasgupta and Torsha SarkarPrivacyAadhaarInternet GovernanceHealthcare2018-09-16T05:01:18ZBlog EntryComments on the Draft Digital Information Security in Healthcare Act
http://editors.cis-india.org/internet-governance/blog/comments-on-the-draft-digital-information-security-in-healthcare-act
<b>The Centre for Internet & Society submitted comments to the Ministry of Health & Family Welfare, Government of India on the draft Digital Information Security in Healthcare Act on April 21, 2018.
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<p style="text-align: justify; ">This submission presents comments by the Centre for Internet and Society, India (“CIS”) on the Draft Digital Information Security in Healthcare Act, released by Ministry of Health & Family Welfare, Government of India. CIS has conducted research on the issues of privacy, data protection and data security since 2010 and is thankful for the opportunity to put forth its views. This submission was made on April 21, 2018.</p>
<p style="text-align: justify; "><a class="external-link" href="http://cis-india.org/internet-governance/files/comments-on-draft-digital-information-security-in-healthcare-act">Download the full submission here</a></p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/comments-on-the-draft-digital-information-security-in-healthcare-act'>http://editors.cis-india.org/internet-governance/blog/comments-on-the-draft-digital-information-security-in-healthcare-act</a>
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No publisherAmber Sinha and Shweta MohandasInternet GovernanceHealthcare2018-05-01T02:05:58ZBlog EntryRoundtable on Artificial Intelligence & Healthcare
http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare
<b>Centre for Internet & Society (CIS) is organizing a roundtable on artificial intelligence (AI) and healthcare at 'The Energy and Resources Institute' (TERI) in Bengaluru on November 30, 2017 from 2 p.m. to 5 p.m. The roundtable seeks to discuss the various issues and challenges surrounding the implementation of AI and related technologies in the Indian healthcare sector.</b>
<p style="text-align: justify; ">The Indian healthcare industry, powered by Artificial Intelligence, is moving into a new era of increased innovation and independence. With multiple new healthcare start-ups and large ICT companies such as Microsoft, IBM, and Google offering AI solutions to healthcare challenges in the country, it is evident that AI is attempting to enhance the accessibility, affordability, quality and awareness of healthcare in India. Major target areas sought to be enhanced by use of AI in healthcare include addressing the uneven ratio of skilled doctors to patients and making doctors more efficient at their jobs, delivery of personalized and high-quality healthcare to rural areas, and training doctors and nurses in complex procedures.</p>
<p style="text-align: justify; ">Through the application of machine learning, data mining, natural language processing (NLP), and advanced analytics, AI can help doctors in speedy diagnosis of diseases. AI is also mobilised as ‘smart advisors’ or virtual humans who are capable of making informed decisions by better comprehending data and information through sensing interfaces and analytics, in various forms.</p>
<p style="text-align: justify; ">Some of these forms include ‘customer service agents’ that can expedite simple tasks like appointment scheduling, or more complex decisions like selecting health plan benefits, ‘clinicians’ that can help with primary screening in understaffed rural areas possibly substituting for human labour, and ‘cognitive agents’ that can efficiently manage existing clinical knowledge alongside physicians, nurses and researchers, thereby reducing the cognitive load on humans. AI based Indian healthcare start-ups such as SigTuple, Aindra, Ten3T, Touchkin and many others are offering a range of solutions including automation of medical diagnosis, automated analysis of medical tests, detection and screening of diseases, wearable sensor based medical devices and monitoring equipment, patient management systems, predictive healthcare diagnosis and disease prevention.</p>
<p style="text-align: justify; ">However, AI in healthcare raises many potential concerns, a common one being the lack of comprehensive, representative, interoperable, and clean data - a challenge that is beginning to be addressed through the Electronic Health Records Standards developed by the Ministry of Health and Family Welfare in 2016 by the Ministry of Health and Family Welfare. Other major challenges include patient adoption and the need for personal interaction with doctors, concerns over mass-scale job losses, distrust in technology, and ethical concerns.</p>
<p style="text-align: justify; ">It is imperative to note that implementing AI in healthcare, which is bound to disrupt it, does not imply replacing doctors but augmenting their efforts to create a more efficient healthcare landscape in the country. A harmonious collaboration of man and machine is expected to bring about a meaningful and long-lasting impact and stakeholders should be prepared to adapt to this change and the challenges that come with it.</p>
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<h3 style="text-align: justify; ">Roundtable Agenda</h3>
<p dir="ltr"><span>Thursday, November 30, 2017, 2:00pm - 5:00pm </span></p>
<p dir="ltr"><span>2:00 - 2:30: Introduction and setting the scene </span></p>
<p dir="ltr"><span>2:30 - 3:30: Discussion on the AI landscape in health in India: </span></p>
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<li><span>Manner and extent of integration of AI into products/services of healthcare companies.</span><span></span></li>
<li><span>Relevant stakeholders and their roles in implementing AI into products/services of healthcare companies.</span><span></span></li>
<li><span>Future of AI and related technologies in the healthcare sector</span><span></span></li>
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<p dir="ltr" style="text-align: justify; "><span>3:30 - 4:30: Discussion on challenges and solutions towards regulating AI in India: </span></p>
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<li dir="ltr" style="list-style-type:disc; "><span>Challenges faced in the conception and implementation of the AI product/service, and reasons for such challenges.</span><span></span></li>
<li dir="ltr" style="list-style-type:disc; "><span>Regulatory provisions for implementation of AI in healthcare products/services under the existing laws, and need for reforms.</span><span></span></li>
<li dir="ltr" style="list-style-type:disc; "><span>Challenges posed by AI to existing policy and regulatory frameworks in the Indian as well as the global context, and possible solutions. </span></li>
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<p><a class="external-link" href="http://cis-india.org/internet-governance/files/a-i-and-manufacturing-and-services">Click to download the invite</a></p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare'>http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare</a>
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No publisherAdminEventArtificial IntelligenceHealthcare2018-01-02T13:49:14ZEvent