The ambitious effort to piece together America’s fragmented health data

Curated on Posted on by Stefaan Verhulst

Nicole Wetsman at The Verge: “From the early days of the COVID-19 pandemic, epidemiologist Melissa Haendel knew that the United States was going to have a data problem. There didn’t seem to be a national strategy to control the virus, and cases were springing up in sporadic hotspots around the country. With such a patchwork response, nationwide information about the people who got sick would probably be hard to come by.

Other researchers around the country were pinpointing similar problems. In Seattle, Adam Wilcox, the chief analytics officer at UW Medicine, was reaching out to colleagues. The city was the first US COVID-19 hotspot. “We had 10 times the data, in terms of just raw testing, than other areas,” he says. He wanted to share that data with other hospitals, so they would have that information on hand before COVID-19 cases started to climb in their area. Everyone wanted to get as much data as possible in the hands of as many people as possible, so they could start to understand the virus.

Haendel was in a good position to help make that happen. She’s the chair of the National Center for Data to Health (CD2H), a National Institutes of Health program that works to improve collaboration and data sharing within the medical research community. So one week in March, just after she’d started working from home and pulled her 10th grader out of school, she started trying to figure out how to use existing data-sharing projects to help fight this new disease.

The solution Haendel and CD2H landed on sounds simple: a centralized, anonymous database of health records from people who tested positive for COVID-19. Researchers could use the data to figure out why some people get very sick and others don’t, how conditions like cancer and asthma interact with the disease, and which treatments end up being effective.

But in the United States, building that type of resource isn’t easy. “The US healthcare system is very fragmented,” Haendel says. “And because we have no centralized healthcare, that makes it also the case that we have no centralized healthcare data.” Hospitals, citing privacy concerns, don’t like to give out their patients’ health data. Even if hospitals agree to share, they all use different ways of storing information. At one institution, the classification “female” could go into a record as one, and “male” could go in as two — and at the next, they’d be reversed….(More)”.

Data Sharing 2.0: New Data Sharing, New Value Creation

Curated on Posted on by Stefaan Verhulst

MIT CISR research:”…has found that interorganizational data sharing is a top concern of companies; leaders often find data sharing costly, slow, and risky. Interorganizational data sharing, however, is requisite for new value creation in the digital economy. Digital opportunities require data sharing 2.0: cross-company sharing of complementary data assets and capabilities, which fills data gaps and allows companies, often collaboratively, to develop innovative solutions. This briefing introduces three sets of practices—curated content, designated channels, and repeatable controls—that help companies accelerate data sharing 2.0….(More)”.

Responsible group data for children

Curated on Posted on by Stefaan Verhulst

Issue Brief by Andrew Young: “Understanding how and why group data is collected and what can be done to protect children’s rights…While the data protection field largely focuses on individual data harms, it is a focus that obfuscates and exacerbates the risks of data that could put groups of people at risk, such as the residents of a particular village, rather than individuals.

Though not well-represented in the current responsible data literature and policy domains writ large, the challenges group data poses are immense. Moreover, the unique and amplified group data risks facing children are even less scrutinized and understood.

To achieve Responsible Data for Children (RD4C) and ensure effective and legitimate governance of children’s data, government policymakers, data practitioners, and institutional decision makers need to ensure children’s group data are a core consideration in all relevant policies, procedures, and practices….(More)”. (See also Responsible Data for Children).

From (Horizontal and Sectoral) Data Access Solutions Towards Data Governance Systems

Curated on Posted on by Stefaan Verhulst

Paper by Wolfgang Kerber: “Starting with the assumption that under certain conditions also mandatory solutions for access to privately held data can be necessary, this paper analyses the legal and regulatory instruments for the implementation of such data access solutions. After an analysis of advantages and problems of horizontal versus sectoral access solutions, the main thesis of this paper is that focusing only on data access solutions is often not enough for achieving the desired positive effects on competition and innovation. An analysis of the two examples access to bank account data (PSD2: Second Payment Service Directive) and access to data of the connected car shows that successful data access solutions might require an entire package of additional complementary regulatory solutions (e.g. regarding interoperability, standardisation, and safety and security), and therefore the analysis and regulatory design of entire data governance systems (based upon an economic market failure analysis). In the last part important instruments that can be used within data governance systems are discussed, like, e.g. data trustee solutions….(More)”.

Demystifying the Role of Data Interoperability in the Access and Sharing Debate

Curated on Posted on by Stefaan Verhulst

Paper by Jörg Hoffmann and Begoña Gonzalez Otero: “In the current data access and sharing debate, data interoperability is widely proclaimed as being key for efficiently reaping the economic welfare enhancing effects of further data re-use. Although, we agree, we found that the current law and policy framework pertaining data interoperability was missing a groundworks analysis. Without a clear understanding of the notions of interoperability, the role of data standards and application programming interfaces (APIs) to achieve this ambition, and the IP and trade secrets protection potentially hindering it, any regulatory analysis within the data access discussion will be incomplete. Any attempt at untangling the role of data interoperability in the access and sharing regimes requires a thorough understanding of the underlying technology and a common understanding of the different notions of data interoperability.

The paper firstly explains the technical complexity of interoperability and its enablers, namely data standards and application programming interfaces. It elaborates on the reasons data interoperability counts with different levels and puts emphasis on the fact that data interoperability is indirectly tangled to the data access right. Since data interoperability may be part of the legal obligations correlating to the access right, the scope of interoperability is and has already been subject to courts’ interpretation. While this may give some manoeuvre for balanced decision-making, it may not guarantee the ambition of efficient re-usability of data. This is why data governance market regulation under a public law approach is becoming more favourable. Yet, and this is elaborated in a second step, the paper builds on the assumption that interoperability should not become another policy on its own. This is followed by a competition economics assessment, taking into account that data interoperability is always a matter of degree and a lack of data interoperability does not necessarily lead to a market foreclosure of competitors and to causing harm to consumer welfare. Additionally, parts of application programming interfaces (APIs) may be protected under IP rights and trade secrets, which might conflict with data access rights. Instead of further solving the conflicting regimes within the respective legal regimes of the exclusive rights the paper concludes by suggesting that (sector-specific) data governance solutions should deal with this issue and align the different interests implied. This may provide for better, practical and well-balanced solutions instead of impractical and dysfunctional exceptions and limitations within the IP and trade secrets regimes….(More)”.

Leveraging Telecom Data to Aid Humanitarian Efforts

Curated on Posted on by Stefaan Verhulst

Data Collaborative Case Study by Michelle Winowatan, Andrew J. Zahuranec, Andrew Young, and Stefaan Verhulst: “Following the 2015 earthquake in Nepal, Flowminder, a data analytics nonprofit, and NCell, a mobile operator in Nepal, formed a data collaborative. Using call detail records (CDR, a type of mobile operator data) provided by NCell, Flowminder estimated the number of people displaced by the earthquake and their location. The result of the analysis was provided to various humanitarian agencies responding to the crisis in Nepal to make humanitarian aid delivery more efficient and targeted.

Data Collaboratives Model: Based on our typology of data collaborative practice areas, the initiative follows the trusted intermediary model of data collaboration, specifically a third-party analytics approach. Third-party analytics projects involve trusted intermediaries — such as Flowminder — who access private-sector data, conduct targeted analysis, and share insights with public or civil sector partners without sharing the underlying data. This approach enables public interest uses of private-sector data while retaining strict access control. It brings outside data expertise that would likely not be available otherwise using direct bilateral collaboration between data holders and users….(More)”.

If data is 21st century oil, could foundations be the right owners?

Curated on Posted on by Stefaan Verhulst

Felix Oldenburg at Alliance: “What are the best investments for a foundation? This important question is one many foundation professionals are revisiting in light of low interest rates, high market volatility, and fears of deep economic trouble ahead. While stories of success certainly exist and are worth learning from, even the notorious lack of data cannot obscure the inconvenient truth that the idea of traditional endowments is in trouble.

I would argue that in order to unleash the potential of foundations, we should turn the question around, perhaps back on its feet: For which assets are foundations the best owners?

In the still dawning digital age, one fascinating answer may stare you right in the face as you read this. How much is your personal data worth? Your social media information, search and purchase history, they are the source of much of the market value of the fastest growing sector of our time. A rough estimate of market valuation of the major social platforms divided by their active users arrives at more than $1,000 USD per user, not differentiating by location or other factors. This sum is more than the median per capita wealth in about half the world’s countries. And if the trend continues, this value may continue to grow – and with it the big question of how to put one of the most valuable resource of our time to use for the good of all.

Acting as guardians of digital commons, data-endowed foundations could negotiate conditions for the commercial use of its assets, and invest the income to create equal digital opportunities, power 21st century education, and fight climate change.

Foundation ownership in the data sector may sound like a wild idea at first. Yet foundations and their predecessors have played the role of purpose-driven owners of critical assets and infrastructures throughout history. Monasteries (called ‘Stifte’ in German, the root of the German word for foundations) have protected knowledge and education in libraries, and secured health care in hospitals. Trusts have created affordable much of the social housing in the exploding cities of the 19th century. The German Marshall Plan created an endowment for economic recovery that is still in existence today.

The proposition is simple: Independent ownership for the good of all, beyond the commercial or national interests of individual corporations of governments, in perpetuity. Acting as guardians of digital commons, data-endowed foundations could negotiate conditions for the commercial use of its assets, and invest the income to create equal digital opportunities, power 21st century education, and fight climate change. An ideal model of ownership would also include a form of governance exercised by the users themselves through digital participation and elections. A foundation really only relies on one thing, a stable frame of rights in its legal home country. This is far from a trivial condition, but again history shows how many foundations have survived depressions, wars, and revolutions….(More)”

How to fix the GDPR’s frustration of global biomedical research

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Jasper Bovenberg, David Peloquin, Barbara Bierer, Mark Barnes, and Bartha Maria Knoppers at Science: “Since the advent of the European Union (EU) General Data Protection Regulation (GDPR) in 2018, the biomedical research community has struggled to share data with colleagues and consortia outside the EU, as the GDPR limits international transfers of personal data. A July 2020 ruling of the Court of Justice of the European Union (CJEU) reinforced obstacles to sharing, and even data transfer to enable essential research into coronavirus disease 2019 (COVID-19) has been restricted in a recent Guidance of the European Data Protection Board (EDPB). We acknowledge the valid concerns that gave rise to the GDPR, but we are concerned that the GDPR’s limitations on data transfers will hamper science globally in general and biomedical science in particular (see the text box) (1)—even though one stated objective of the GDPR is that processing of personal data should serve humankind, and even though the GDPR explicitly acknowledges that the right to the protection of personal data is not absolute and must be considered in relation to its function in society and be balanced against other fundamental rights. We examine whether there is room under the GDPR for EU biomedical researchers to share data from the EU with the rest of the world to facilitate biomedical research. We then propose solutions for consideration by either the EU legislature, the EU Commission, or the EDPB in its planned Guidance on the processing of health data for scientific research. Finally, we urge the EDPB to revisit its recent Guidance on COVID-19 research….(More)“.

Essential Requirements for Establishing and Operating Data Trusts

Curated on Posted on by Stefaan Verhulst

Paper by P Alison Paprica et al: “Increasingly, the label “data trust” is being applied to repeatable mechanisms or approaches to sharing data in a timely, fair, safe and equitable way. However, there is a gap in terms of practical guidance about how to establish and operate a data trust.

In December 2019, the Canadian Institute for Health Information and the Vector Institute for Artificial Intelligence convened a working meeting of 19 people representing 15 Canadian organizations/initiatives involved in data sharing, most of which focus on public sector health data. The objective was to identify essential requirements for the establishment and operation of data trusts. Preliminary findings were presented during the meeting then refined as participants and co-authors identified relevant literature and contributed to this manuscript.

Twelve (12) minimum specification requirements (“min specs”) for data trusts were identified. The foundational min spec is that data trusts must meet all legal requirements, including legal authority to collect, hold or share data. In addition, there was agreement that data trusts must have (i) an accountable governing body which ensures the data trust advances its stated purpose and is transparent, (ii) comprehensive data management including responsible parties and clear processes for the collection, storage, access, disclosure and use of data, (iii) training and accountability requirements for all data users and (iv) ongoing public and stakeholder engagement.

Based on a review of the literature and advice from participants from 15 Canadian organizations/initiatives, practical guidance in the form of twelve min specs for data trusts were agreed on. Public engagement and continued exchange of insights and experience is recommended on this evolving topic…(More)”.

Private Sector Data for Humanitarian Response: Closing the Gaps

Curated on Posted on by Stefaan Verhulst

Jos Berens at Bloomberg New Economy Forum: “…Despite these and other examples, data sharing between the private sector and humanitarian agencies is still limited. Out of 281 contributing organizations on HDX, only a handful come from the private sector. 

So why don’t we see more use of private sector data in humanitarian response? One obvious set of challenges concerns privacy, data protection and ethics. Companies and their customers are often wary of data being used in ways not related to the original purpose of data collection. Such concerns are understandable, especially given the potential legal and reputational consequences of personal data breaches and leaks.

Figuring out how to use this type of sensitive data in an already volatile setting seems problematic, and it is — negotiations between public and private partners in the middle of a crisis often get hung up on a lack of mutual understanding. Data sharing partnerships negotiated during emergencies often fail to mature beyond the design phase. This dynamic creates a loop of inaction due to a lack of urgency in between crises, followed by slow and halfway efforts when action is needed most.

To ensure that private sector data is accessible in an emergency, humanitarian organizations and private sector companies need to work together to build partnerships before a crisis. They can do this by taking the following actions: 

  • Invest in relationships and build trust. Both humanitarian organizations and private sector organizations should designate focal points who can quickly identify potentially useful data during a humanitarian emergency. A data stewards network which identifies and connects data responsibility leaders across organizations, as proposed by the NYU Govlab, is a great example of how such relations could look. Efforts to build trust with the general public regarding private sector data use for humanitarian response should also be strengthened, primarily through transparency about the means and purpose of such collaborations. This is particularly important in the context of COVID-19, as noted in the UN Comprehensive Response to COVID-19 and the World Economic Forum’s ‘Great Reset’ initiative…(More)”.