Interview with the Data Policy Circle of the Digital Transformation for Universal Health Coverage 2030 Coalition

On Tuesday 2 June 2020, Gabriela Ramos participated in an interview with UHC2030 on Data Protection. Find her speaking points below.


Introduction    

The COVID-19 pandemic is a fundamentally social crisis. The virus spreads between people, and impacts individuals, households and communities. Any country’s response to the pandemic must be guided by social data and expertise as much as by medical data and expertise. Failing to identify and address social impacts of the pandemic opens the way for devastating social damage and loss of life.

Clearly, a pandemic response guided by only medical or economic data alone is inadequate. Social data could also shape the response. 

Gender equality in universal health coverage

  • First, we need to understand that we will be living alongside this virus long past initial deconfinement efforts until vaccines are developed.
  • Thus, investment in R&D for accelerated development of diagnostics, treatments, and vaccines will be critical.
  • But more importantly, this crisis is an important reminder that high-quality and affordable universal health coverage is crucial to protect the most vulnerable and to ensure access to diagnostics and treatment. I know this personally as I contributed to dramatically increasing Mexico’s health coverage from only 48.3% of the population in 2002 to 89.3% today.
  • And if the aim of UHC is to leave no one behind then gender equality is an essential ingredient.
  • UHC needs to address sex-and gender-based determinants of health; including how sexual and reproductive health and rights (SRHR) and gender-based violence disproportionately affect the health of women, whereas men are more likely to die from tobacco use, suicide, and road injuries. The following factors need to be taken into account:
    • Women exposed to intimate partner violence (1 in 3 globally) are: twice as likely to experience depression, 1.5 times more likely to acquire HIV, 1.5 times more likely to contract sexually transmitted infections.
    • With the COVID-19 confinement measures, cases of domestic violence have risen sharply.  In Brazil it has been estimated that cases have risen by 40–50%, similar levels have been reported in the UK and many other countries.
    • Also, women live longer than men, but female longevity is associated with a greater lifetime risk of functional disability and chronic illnesses (incl. cancer, cardiovascular disease, dementia, and the need for long-term care).
    • Women typically care for her husband at the end of his life, and then go on without the same intensive personal care.
    • Therefore, compared to older men, older women are more likely to need long-term care, and need it for longer periods, while  also  being  less  likely  to  afford  it,  due  to,  among  other  reasons, lower  labour  market  participation, lower lifetime earnings and lower pensions.
    • Women have more unmet health needs than men. Across EU countries, women are 40% more likely to report some unmet needs for medical care than men, mainly due to financial reasons. 
    • Women are at a higher risk of poverty than men [Across the OECD, the average relative poverty rate for women is 12.3%, while 10.9% for men. The highest gender gap can be found in Korea, Latvia, Estonia in the OECD].
    • Twice as many women as men aged over 65 live alone in G20 countries. Pension payment to 65+ women are 25% lower than for men.
    • Also, we have estimated at the outset of the pandemic that 1 in 3 financially vulnerable people (including single mothers) will fall into poverty without 3 months’ of income loss.
  • Data disaggregated by sex and gender is urgently needed not only in the design of UHC interventions, but also in monitoring and evaluation, to ensure that the most vulnerable women and girls are not left behind. Gender-responsive UHC will even up life chances between genders, as well as between rich and poor women within and between countries.
  • This is also why the OECD has been partnering with WHO and ILO since the establishment of the Working for Health Programme in 2017 (a joint inter-agency multi-SDG programme to accelerate the expansion and transformation of the health and social workforce). In this programme, we embrace gender as a core tenant and seeks to utilize workforce plans, investments and actions to seize the opportunities to realise gender equality.

Women in health care and lack of gender disaggregated data

  • This crisis should force us to give women in the health care workforce more priority because…
    • Facts:
      • Women comprise 70% of the health and social care workers, 85% of nurses and over 90% of long-term care workers across OECD countries. In some countries and regions, nursing homes are predominantly staffed by immigrant women, migrants and refugees – mostly women of colour.[1]
      • They will also be central to filling a global shortfall of 40 million new health and social care jobs globally by 2030 to achieve UHC. Then we need to go beyond business as usual to promote more investment and decent working condition for the female health workforce.
      • However, they hold only 25% of global health leadership posts and generally have lower status, lower pay [Overall, an average gender pay gap of around 28% exists in the health workforce. And 12% gender pay gap for nurses], or even unpaid roles [nearly half of the workload is unpaid].
    • There are huge gender gaps in data and research:
      • Widespread gaps in the data were found in low income countries.
      • Major gaps in data in all areas, particularly sexual harassment and data comparable across countries on the gender pay gap
      • For example, much of women’s work health/social care are unpaid and excluded in gender pay gap data.
    • What’s needed?
      • To map out the impact first, our priority should be to: apply a gender and intersectionality lens; include sex- and gender-disaggregated data; and include the entire health and social workforce, including the social care workforce. Research must go beyond describing the gender inequities to also evaluate the impact of gender-transformative interventions.
      • Such mapping will aid understanding of context- specific factors, including sociocultural dimensions. Moreover, research focused on implementation and translation into policy is needed to assess the viability and effectiveness of policies and inform gender-transformative policy action.

Use of digital technology

  • Ongoing expansion of testing and tracing capacity is crucial, as is effective management of large and rapidly changing data flows on the spread of the pandemic. [Further below on privacy concerns]
  • SDG Goal 3 (UHC for all by 2030) is un be attainable without effective use of AI, digital and frontier technologies. Digital innovation will be key in addressing issues around financial risk protection, including fintech and digital financial solutions for health insurance schemes, and access to quality essential healthcare services. In this sense, I commend the work of the Digital Transformation for UHC 2030 Coalition that you are spearheading with other partners including Women Deliver.
  • Unfortunately, there is arguably no other sector than the healthcare that generates quite as much data and, at the same time, fails to coordinate the data in effective, useful ways.
  • The failure to extract and use information contained in health data, which exist already, is a significant missed opportunity to improve services and care.
    • Waste:
      • For example, the OECD finds that 10% of patients are unnecessarily harmed during care. The health burden of this in OECD countries is on par with diseases such as multiple sclerosis and some cancers.
      • The direct financial impact is as high as 15% of hospital expenditure, and the broader economic drag estimated to be in the trillions of dollars. The most common root cause is a failure of communication – information and knowledge not reaching the right person at the right time. Better information exchange makes care not only safer but also more effective and efficient.
      • Care can be better coordinated by different providers and integrated with other services, with better results and less duplication and waste (20-30% of the adult population in OECD countries have multiple chronic conditions, and for them, accessing care can be frustrating when not integrated as one service).
      • Enabling access to the electronic health or medical record (EHR or EMR) by all actors involved in a patient’s care is a key structural component of a high-quality health system
  • To harness the benefit while addressing the risks of data privacy, the OECD has already come up with the Recommendation of the OECD Council on Health Data Governance in 2017.
    • With 12 principles, this recommendation set the conditions to encourage greater cross-country comparison and harmonisation of data governance frameworks so that more countries are able to use health data for research, statistics and healthcare quality improvement.
    • Unfortunately, despite the important gender dimension in long-term care, there continues to be little gender-disaggregated data on many key indicators (e.g. ability to pay, access to care, working conditions, training, etc.)
    • Only half of the 35 OECD countries (with available data) have national policies in place to address how data from electronic health records can inform clinicians, monitor disease outbreaks, conduct research and improve patient safety. Only half of OECD countries regularly link their existing health datasets to monitor healthcare quality[2].
      • More specifically, approximately 70% of responding countries to the 2016 OECD survey reported that people can access their record, while only 43% reported that individuals could interact with their own record (e.g. enter information, send requests, communicate with providers).
      • Nevertheless, good progress can also be found in some countries.
        • Estonia has a unified EHR, which enables residents to view all of their medical data in one place – including diagnoses, test results, medications. Residents can also interact with their data. They can update their details, supplement existing information, and carry out administrative processes such as obtaining a medical certificate for a driver’s license without needing a specific appointment.
        • Lithuania has implemented a centralised ‘one resident – one record’ EHR system that covers 95% of the population.
    • Better governance of healthcare data is possible and can lift performance. For instance, public reporting of healthcare quality indicators gives patients the information needed to identify the best healthcare provider, and acts as a powerful incentive for failing healthcare providers to change for the better[3]
  • Looking forward data gaps must also be bridged to ensure better quality healthcare for women and girls, and appropriate data systems are needed to ensure that health care quality is monitored and improved.
  • Furthermore, today’s global health emergencies highlight the importance of coherent, comparable and timely data shared and used across borders, within and between countries. When data sharing and linkage are most needed, data are not trapped in silos, difficult to exchange or shared with significant delays.[4] Here are good examples:
    • Korea[5] was able to trace infections by combining location data (including data collected from mobile devices) with personal identification information, medical and prescription records, immigration records, card transaction data for credit, debit, and prepaid cards, transit pass records for public transportation, and closed-circuit television (CCTV) footage. While there are certainly privacy concerns, the approach has wide public support.
      • And Korea had a good foundation to move fast in using health data since already before the COVID-19 pandemic, the country was in the process of integrating the national health insurance database (NHID) with clinical records, health care activities as well as data from outside of the health system including climate, pollution and geolocation data.
    • Chinese Taipei [6] used real-time health data from existing insurance coverage databases, linked to other data such as customs and immigration data. During clinical visits, when health care providers scan patients’ health insurance cards, an alert can be issued based on patients’ travel history and clinical symptoms. This data can be analysed to identify and test patients for COVID-19 who had severe respiratory symptoms.
  • There are also opportunities to better leverage Artificial intelligence. (AI) algorithms that learn from human decisions will also learn human mistakes, biases and stereotypes.
    • However, the AI sector is very gender and race imbalanced[7], suggesting that biased and stereotypical predictions might not be flagged by developers working to validate model outputs.
    • For example, Apple’s HealthKit, an application to track intake of selenium and copper, neglected to include a women’s menstrual cycle tracker until iOS 9; the development team reportedly did not include any women.[8]
    • And more generally, a study found that men were almost 6 times more likely than women to be shown ads for high-paying executive jobs.
    • Research has shown that AI systems sold by tech giants have error rates of max1% for lighter-skinned men and 35% for darker-skinned women.
    • AI can infringe on human rights and privacy: risk of data manipulation & sharing; identification and tracking; speech and facial recognition. Evidence of AI tech being used by governments to spy on civil society and activists.
    • AI can infringe on democracy: algorithms and ‘bots’ help share fake news, violent images, harvest & sell data (Cambridge Analytica) and drive echo chambers, especially on social media.
    • Part of solution (common ground) can be found in the OECD AI Principles (AI should: contribute to inclusive and sustainable growth and well-being; be used in ways that respect human-centred values and fairness; be transparent and explainable; robust, secure and safe; and accountable).

Use of date in the COVID-19 pandemic: Privacy or effectiveness? We need an international consensus on health data governance…

  • Recent OECD research has found that around a half of all people across the OECD have accessed health information online.
  • These are encouraging examples of how data can help policymakers improve patients’ lives, but more needs to be done.
  • Health data are personal and sensitive, and in the wrong hands, can be used to harm patients through a loss of their privacy; discrimination in areas such as health insurance or employment; and identity theft. Such data breaches and misuses weaken public trust, not just in healthcare providers but in policymakers, too.
  • The rising risk of cyber attacks and the growing suite of new technologies to secure data, make the data protection environment as vital as it is challenging.

Then comes the issue of data governance and privacy…

  • Half of the world’s population now connected to the Internet. As data becomes a key resource, issues of data governance rise. Foremost amongst these is the challenge of preserving openness by advancing trust in digital technologies [i.e., criminals taking advantage of the free flow of information; greater potential for fraud; loss of control over privacy and personal data; digital security breaches; and of course conflicting laws across legal jurisdictions creating friction.]
  • And at the OECD, we found that privacy is a top priority for citizens.
    • In 2016, more than 70% of Internet users in the EU provided personal information online, with many also performing actions to control access to these data.
    • In 2017, 46% of all Internet users in Europe refused to allow the use of personal information for advertising and 40% limited access to their profile or content on social networking sites.
    • More than 1/3 of Internet users read privacy policy statements before providing personal information and restricted access to their geographical location.
  • This caution is certainly warranted.
    • In 2015, around 3% of all Internet users across OECD countries reported having experienced a privacy violation in the three months prior to being surveyed. And keep in mind that this is the figure just for reported violations.
    • In countries such as Norway, Portugal, Sweden and Turkey, there was a notable increase in privacy violations as reported by individuals between 2010 and 2015.
    • In 2016, 64% of individuals in the United States experienced or had been notified of a significant data breach pertaining to their personal data or accounts.
    • People are also concerns over the protection of personal data handled by the public authority. In 2018, 18% of EU28 citizens chose not to submit forms to public authorities, 20% of them citing concerns about the protection of personal data as the reason.
  • IP theft has become a serious concern 
    • Small businesses accounted for 43 % of all attacks, while healthcare and financial services organizations made up 15 % and 10 %, respectively.
    • In 51% cases, IP theft resulted from human error (e.g. lost device, unintended disclosure or tailgating), malware infiltrations were reported in 43%.   
  •  And as we all know, data breaches have increased in scale and frequency [Facebook and WhatsApp data breach is fresh in our memory].
  • People need to know their rights, and have a say on how their data is used. We cannot harness the digital economy to improve people’s lives without ensuring the trust of citizens in digital technologies. But we must move forward together.
  • Against this backdrop, the OECD Privacy Guidelines (adopted in 1980, revised in 2013) will continue to serve as a key reference point. The OECD is a leader in the filed of privacy, working for almost 40 years. The Guidelines were the first internationally agreed set of privacy principles that apply to the protection of personal data, whether in the public or private sectors, and have influenced legislation and policy in OECD Member countries and beyond.
    • Since digital security and privacy is a moving target and there are also emerging threats to contend with, the OECD is currently undertaking a review of the Guidelines.  
    • One area we think is of as particularly important with regard to industry and government collaboration is further elaborating on mechanisms for increased accountability.
      • We will undergo further consultation with experts over the course of 2020 to review the Guidlines particularly in the áreas of:
        • Data ethics (recognising the importance of issues that are complementary to regulatory privacy issues, including issues like fairness, respect for human dignity, autonomy, self-determination, the risk of bias and discrimination).
        • Data portability (aiming to address still unresolved challenges such as regarding the scope of data portability regulation (i.e. what type of data should be subject to the data portability regulation), the role of voluntary data portability initiatives, and the need for standards.)

Contact tracing app (the case of France and TTT concerns in general)

  • And just today (2 June noon) in France where I am now, StopCovid tracking application was made available. Now we can freely download and use the app on our phone. And this coincides with the cautious reopening of bars and restraurants terraces across France.
  • The purpose of the StopCovid application is to let users know if they have been in the vicinity of people who may have been infected with the Covid-19 virus.
  • Of course there are privacy fears, but the value for money is also highlighted by the French State Minister for Digital Affairs, Cedric O (no more than a few hundred thousand euros per month).
  • And also there is concern over effectiveness – we need 50-60% of French people installing the app for contact-tracing to be effective. But this will be difficult because 25% of French people don’t have a smartphone.
  • But already, 22 countries have chosen to develop a contact-tracing app that relies on the interface developed by Apple and Google. 
  • A digital approach to widespread use of TTT is likely to be a key part of a successful exit strategy, but there is a risk of public identification of individuals and resulting stigma, whether confirmed infected, suspected infected or susceptible, even with anonymised data.
  • All OECD countries either have existing legal provisions or may enact laws that enable infringement of privacy due to a threat to public security. In enacting new laws or provisions, individuals should have a right to a judicial remedy and the provisions should be time bound so that the surveillance does not become permanent.
  • Most importantly, responses should align with the OECD Privacy Guidelines and with the aforementioned Recommendation on Health Data Governance, particularly with respect to public transparency of data uses. The Recommendation is useful because it represents an international consensus about the framework conditions within which health data can be appropriately governed, so that health data processing can take place both domestically and transnationally in ways that can reduce risk and improve benefits for health systems and patients.
    • Ensuring a supervisory body or watchdog will monitor the implementation of surveillance technologies and inform the public of new surveillance technologies and of their rights is recommended.
  • Policy makers, in consultation with privacy enforcement authorities (PEAs), must assess the possible trade-offs in data utilisation during this crisis (reconciling the risks and benefits), but must ensure that any extraordinary measures are proportionate to the risks and are implemented with full transparency, accountability and a commitment to immediately cease or reverse exceptional uses of data when the crisis is over.
    • In practice, few countries have frameworks in place to support these extraordinary measures in ways that are fast, secure, trustworthy, scalable and in compliance with existing privacy and data protection regulations. For example, South Korea, Singapore, Israel already had extraordinary powers or could issue emergency measures to collect personal data, but others had to pass laws for data collection.
  • Privacy enforcement authorities (PEAs) have a key role to play in advising on proposed new government legislation and providing clarity regarding the application of existing privacy and data protection frameworks.
    • As of mid-April 2020, Privacy Enforcement Authorities (PEAs) in Argentina, Australia, Canada, Finland, France, Germany, Ireland, New Zealand, Poland, Slovakia, Switzerland and the United Kingdom have published general guidance for data controllers and processors about the application of their privacy and data protection laws in the crisis. The European Data Protection Board, GDPR and Convention 108 do not hinder measures taken in the fight against COVID but do require measures to be limited to emergency period.

Digital gender divide

  • Half of the world’s population still does not have access to the internet. Even worse, 250 million fewer women than men are online.
  • Actually, all the gender gaps as we know them (of representation, of distribution of unpaid work, on wage gap, on leadership gap) will pale with the trends we are seeing in the digital world.
  • There are few girls who opt for ICT disciplines.
    • At age 15, only 0.5% of girls in OECD countries want to become ICT professionals, compared to 5% of boys. Twice as many boys as girls expect to become engineers, scientists or architects.
  • Adults with a tertiary degree in engineering manufacturing and construction and natural sciences, mathematics and statistics earn over 60% more than adults with upper secondary education, women are not well represented in this field.
    • This is especially worrying for women who graduate at higher rates from tertiary education (58%) but are still underrepresented in STEM fields: only 24% of engineering graduates and 25% of ICT graduates were women
    • This plays into exclusion of women in innovative startups:
      • 90% of software development is done by male only teams
      • Women-owned start-ups receive 23% less funding and are 30% less likely to be bought up or issue an IPO than male-owned businesses.
  • Beyond re-thinking how to bridge these divides, we should also reframe the way we deal with the technology, not only to be prepare individuals to master it, but to be in charge of its development and impact. First, to use technology to find answers for the social and environmental challenges we face, but second to avoid the downsides of this technologies as we saw in Christchurch.
  • And, the digital divide is not just about women, but about children from disadvantaged background.
    • Let’s look at France for example. The OECD estimates that each week that a school closes represents on average 26 hours of face-to-face learning time (data available for colleague level, general education), which equals 2.8% of the time total instruction year.
    • The capacity and adaptability to compensate for the projected loss in learning varies according to socio-economic profiles of students.
    • And of course the ones that lost most are those from low-income and/or single-parent families.
    • Because… across the OECD, 22% of children from the lowest socio-economic status don’t have internet access and are left behind in this full digital learning environment.
    • Furthermore, on average across OECD, more than 30% of 15-year-old socio-economically disadvantaged students do not have a quiet place to study at home (as opposed to 10% of advantaged students).
    • During the Covid-19 epidemic, despite government efforts, online courses and classes have been difficult to access for disadvantaged students. Providing children with free or affordable devices and internet access could be one way of tackling the digital divide between students from different backgrounds to make up for the unequal starting conditions.

[1] https://theconversation.com/inquiry-into-coronavirus-nursing-home-deaths-needs-to-include-discussion-of-workers-and-race-139017

[2] https://oecdobserver.org/news/fullstory.php/aid/5780/Governing_data_for_better_health_and_health_care.html

[3] https://oecdobserver.org/news/fullstory.php/aid/5780/Governing_data_for_better_health_and_health_care.html

[4] http://www.oecd.org/coronavirus/policy-responses/beyond-containment-health-systems-responses-to-covid-19-in-the-oecd-6ab740c0/

[5] https://jamanetwork.com/journals/jama/fullarticle/2765252

[6] https://jamanetwork.com/journals/jama/fullarticle/2762689

[7] https://ainowinstitute.org/AI_Now_2019_Report.pdf

[8] https://nam.edu/artificial-intelligence-special-publication/

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s