public policy

Research reveals de-identified patient data can be re-identified

Curated on December 18, 2017August 3, 2018 by Stefaan Verhulst

Vanessa Teague, Chris Culnane and Ben Rubinstein in PhysOrg: “In August 2016, Australia’s federal Department of Health published medical billing records of about 2.9 million Australians online. These records came from the Medicare Benefits Scheme (MBS) and the Pharmaceutical Benefits Scheme (PBS) containing 1 billion lines of historical health data from the records of around 10 per cent of the population.

These longitudinal records were de-identified, a process intended to prevent a person’s identity from being connected with information, and were made public on the government’s open data website as part of its policy on accessible public data…

We found that patients can be re-identified, without decryption, through a process of linking the unencrypted parts of the record with known information about the individual.

Our findings replicate those of similar studies of other de-identified datasets:

A few mundane facts taken together often suffice to isolate an individual.
Some patients can be identified by name from publicly available information.
Decreasing the precision of the data, or perturbing it statistically, makes re-identification gradually harder at a substantial cost to utility.

The first step is examining a patient’s uniqueness according to medical procedures such as childbirth. Some individuals are unique given public information, and many patients are unique given a few basic facts, such as year of birth or the date a baby was delivered….

The second step is examining uniqueness according to the characteristics of commercial datasets we know of but cannot access directly. There are high uniqueness rates that would allow linking with a commercial pharmaceutical dataset, and with the billing data available to a bank. This means that ordinary people, not just the prominent ones, may be easily re-identifiable by their bank or insurance company…

These de-identification methods were bound to fail, because they were trying to achieve two inconsistent aims: the protection of individual privacy and publication of detailed individual records. De-identification is very unlikely to work for other rich datasets in the government’s care, like census data, tax records, mental health records, penal information and Centrelink data.

While the ambition of making more data more easily available to facilitate research, innovation and sound public policy is a good one, there is an important technical and procedural problem to solve: there is no good solution for publishing sensitive complex individual records that protects privacy without substantially degrading the usefulness of the data.

Some data can be safely published online, such as information about government, aggregations of large collections of material, or data that is differentially private. For sensitive, complex data about individuals, a much more controlled release in a secure research environment is a better solution. The Productivity Commission recommends a “trusted user” model, and techniques like dynamic consent also give patients greater control and visibility over their personal information….(More).

Better Data for Better Policy: Accessing New Data Sources for Statistics Through Data Collaboratives

Curated on October 26, 2017August 3, 2018 by Stefaan Verhulst

Medium Blog by Stefaan Verhulst: “We live in an increasingly quantified world, one where data is driving key business decisions. Data is claimed to be the new competitive advantage. Yet, paradoxically, even as our reliance on data increases and the call for agile, data-driven policy making becomes more pronounced, many Statistical Offices are confronted with shrinking budgets and an increased demand to adjust their practices to a data age. If Statistical Offices fail to find new ways to deliver “evidence of tomorrow”, by leveraging new data sources, this could mean that public policy may be formed without access to the full range of available and relevant intelligence — as most business leaders have. At worst, a thinning evidence base and lack of rigorous data foundation could lead to errors and more “fake news,” with possibly harmful public policy implications.

While my talk was focused on the key ways data can inform and ultimately transform the full policy cycle (see full presentation here), a key premise I examined was the need to access, utilize and find insight in the vast reams of data and data expertise that exist in private hands through the creation of new kinds of public and private partnerships or “data collaboratives” to establish more agile and data-driven policy making.

Applied to statistics, such approaches have already shown promise in a number of settings and countries. Eurostat itself has, for instance, experimented together with Statistics Belgium, with leveraging call detail records provided by Proximus to document population density. Statistics Netherlands (CBS) recently launched a Center for Big Data Statistics (CBDS)in partnership with companies like Dell-EMC and Microsoft. Other National Statistics Offices (NSOs) are considering using scanner data for monitoring consumer prices (Austria); leveraging smart meter data (Canada); or using telecom data for complementing transportation statistics (Belgium). We are now living undeniably in an era of data. Much of this data is held by private corporations. The key task is thus to find a way of utilizing this data for the greater public good.

Value Proposition — and Challenges

There are several reasons to believe that public policy making and official statistics could indeed benefit from access to privately collected and held data. Among the value propositions:

Using private data can increase the scope and breadth and thus insights offered by available evidence for policymakers;
Using private data can increase the quality and credibility of existing data sets (for instance, by complementing or validating them);
Private data can increase the timeliness and thus relevance of often-outdated information held by statistical agencies (social media streams, for example, can provide real-time insights into public behavior); and
Private data can lower costs and increase other efficiencies (for example, through more sophisticated analytical methods) for statistical organizations….(More)”.

The role of policy entrepreneurs in open government data policy innovation diffusion: An analysis of Australian Federal and State Governments

Curated on October 24, 2017November 10, 2018 by Stefaan Verhulst

Paper by Akemi TakeokaChatfield and Christopher G.Reddick: “Open government data (OGD) policy differs substantially from the existing Freedom of Information policies. Consequently OGD can be viewed as a policy innovation. Drawing on both innovation diffusion theory and its application to public policy innovation research, we examine Australia’s OGD policy diffusion patterns at both the federal and state government levels based on the policy adoption timing and CKAN portal “Organization” and “Category” statistics. We found that state governments that had adopted OGD policies earlier had active policy entrepreneurs (or lead departments/agencies) responsible for the policy innovation diffusion across the different government departments. We also found that their efficacy ranking was relatively high in terms of OGD portal openness when openness is measured by the greater number of datasets proactively and systematically published through their OGD portals. These findings have important implications for the role played by OGD policy entrepreneurs in openly sharing the government-owned datasets with the public….(More)”.

The Challenges of Prediction: Lessons from Criminal Justice

Curated on October 18, 2017August 3, 2018 by Stefaan Verhulst

Paper by David G. Robinson: “Government authorities at all levels increasingly rely on automated predictions, grounded in statistical patterns, to shape people’s lives. Software that wields government power deserves special attention, particularly when it uses historical data to decide automatically what ought to happen next.

In this article, I draw examples primarily from the domain of criminal justice — and in particular, the intersection of civil rights and criminal justice — to illustrate three structural challenges that can arise whenever law or public policy contemplates adopting predictive analytics as a tool:

1) What matters versus what the data measure;
2) Current goals versus historical patterns; and
3) Public authority versus private expertise.

After explaining each of these challenges and illustrating each with concrete examples, I describe feasible ways to avoid these problems and to do prediction more successfully…(More)”

Policy Analytics, Modelling, and Informatics

Curated on October 11, 2017October 24, 2018 by Stefaan Verhulst

Book edited by J. Ramon Gil-Garcia, Theresa A. Pardo and Luis F. Luna-Reyes: “This book provides a comprehensive approach to the study of policy analytics, modelling and informatics. It includes theories and concepts for understanding tools and techniques used by governments seeking to improve decision making through the use of technology, data, modelling, and other analytics, and provides relevant case studies and practical recommendations. Governments around the world face policy issues that require strategies and solutions using new technologies, new access to data and new analytical tools and techniques such as computer simulation, geographic information systems, and social network analysis for the successful implementation of public policy and government programs. Chapters include cases, concepts, methodologies, theories, experiences, and practical recommendations on data analytics and modelling for public policy and practice, and addresses a diversity of data tools, applied to different policy stages in several contexts, and levels and branches of government. This book will be of interest of researchers, students, and practitioners in e-government, public policy, public administration, policy analytics and policy informatics….(More)”.

Artificial Intelligence and Public Policy

Curated on September 13, 2017August 3, 2018 by Stefaan Verhulst

Paper by Adam D. Thierer, Andrea Castillo and Raymond Russell: “There is growing interest in the market potential of artificial intelligence (AI) technologies and applications as well as in the potential risks that these technologies might pose. As a result, questions are being raised about the legal and regulatory governance of AI, machine learning, “autonomous” systems, and related robotic and data technologies. Fearing concerns about labor market effects, social inequality, and even physical harm, some have called for precautionary regulations that could have the effect of limiting AI development and deployment. In this paper, we recommend a different policy framework for AI technologies. At this nascent stage of AI technology development, we think a better case can be made for prudence, patience, and a continuing embrace of “permissionless innovation” as it pertains to modern digital technologies. Unless a compelling case can be made that a new invention will bring serious harm to society, innovation should be allowed to continue unabated, and problems, if they develop at all, can be addressed later…(More)”.

The Death of Public Knowledge? How Free Markets Destroy the General Intellect

Curated on September 11, 2017August 3, 2018 by Stefaan Verhulst

Book edited by Aeron Davis: “...argues for the value and importance of shared, publicly accessible knowledge, and suggests that the erosion of its most visible forms, including public service broadcasting, education, and the network of public libraries, has worrying outcomes for democracy.

With contributions from both activists and academics, this collection of short, sharp essays focuses on different aspects of public knowledge, from libraries and education to news media and public policy. Together, the contributors record the stresses and strains placed upon public knowledge by funding cuts and austerity, the new digital economy, quantification and target-setting, neoliberal politics, and inequality. These pressures, the authors contend, not only hinder democracies, but also undermine markets, economies, and social institutions and spaces everywhere.

Covering areas of international public concern, these polemical, accessible texts include reflections on the fate of schools and education, the takeover of public institutions by private interests, and the corruption of news and information in the financial sector. They cover the compromised Greek media during recent EU negotiations, the role played by media and political elites in the Irish property bubble, the compromising of government policy by corporate interests in the United States and Korea, and the squeeze on public service media in the United Kingdom, New Zealand, and the United States.

Individually and collectively, these pieces spell out the importance of maintaining public, shared knowledge in all its forms, and offer a rallying cry for doing so, asserting the need for strong public, financial, and regulatory support….(More)”

Intragovernmental Collaborations: Pipedreams or the Future of the Public Sector?

Curated on September 10, 2017August 20, 2018 by Stefaan Verhulst

Sarah Worthing at the Stanford Social Innovation Review: “Despite the need for concerted, joint efforts among public sector leaders, those working with or in government know too well that such collaborations are rare. The motivation and ability to collaborate in government is usually lacking. So how did these leaders—some with competing agendas—manage to do it?

A new tool for collaboration

Policy labs are units embedded within the public sector—“owned” by one or several ministries—that anchor systematic public sector innovation efforts by facilitating creative approaches to policymaking. Since the inception of the first labs over a decade ago, many innovation experts and academics have touted labs as the leading-edge of public policy innovation. They can generate novel, citizen-centric, effective policies and service provisions, because they include a wide range of governmental and, in many cases, non-governmental actors in tackling complex public policy issues like social inequality, mass migration, and terrorism. MindLab in Denmark, for example, brought together government decision makers from across five ministries in December 2007 to co-create policy strategies on tackling climate change while also propelling new business growth. The collaboration resulted in a range of business strategies for climate change that were adopted during the 2009 UN COP15 Summit in Copenhagen. Under normal circumstances, these government leaders often push conflicting agendas, compete over resources, and are highly risk-adverse in undertaking intragovermental partnerships—all “poison pills” for the kind of collaboration successful public sector innovation needs. However, policy labs like MindLab, Policy Lab UK, and almost 100 similar cross-governmental units are finding ways to overcome these barriers and drive public sector innovation.

Five ways policy labs facilitate successful intragovermental collaboration

To examine how labs do this, we conducted a multiple-case analysis of policy labs in the European Union and United States.

1. Reducing potential future conflict through experiential on-boarding processes. Policy labs conduct extensive screening and induction activities to provide policymakers with both knowledge of and faith in the policy lab’s approach to policymaking. …

2. Utilization of spatial cues to flatten hierarchical and departmental differences. Policy labs strategically use non-traditional spatial elements such as moveable whiteboards, tactile and colorful prototyping materials, and sitting cubes, along with the absence of expected elements such as conference tables and chairs, to indicate that unconventional norms—non-hierarchical and relational norms—govern lab spaces….

3. Reframing policy issues to focus on affected citizens. Policy labs highlight individual citizens’ stories to help reconstruct policymakers’ perceptions toward a more common and human-centered understanding of a policy issue…

4. Politically neutral, process-focused facilitation. Lab practitioners employ design methods that can help bring together divided policymakers and break scripted behavior patterns. Many policy labs use variations of design thinking and foresight methods, with a focus on iterative prototyping and testing, stressing the need for skilled but politically neutral facilitation to work through points of conflict and reach consensus on solutions. …

5. Mitigating risk through policy lab branding….(More)”.

We need a safe space for policy failure

Curated on August 14, 2017August 3, 2018 by Stefaan Verhulst

Catherine Althaus & David Threlfall in The Mandarin: “Who remembers Google Schemer, the Apple Pippin, or Microsoft Zune? No one — and yet such no-go ideas didn’t hold back these prominent companies. In IT, such high profile failures are simply steps on the path to future success. When a start-up or major corporate puts a product onto the market they identify the kinks in their invention immediately, design a fix, and release a new version. If the whole idea falls flat — and who ever listened to music on a Zune instead of an iPod? — the next big thing is just around the corner. Learning from failure is celebrated as a key feature of innovation.

But in the world of public policy, this approach is only now creeping into our collective consciousness. We tread ever so lightly.

Drug policy, childcare reform, or information technology initiatives are areas where innovation could provide policy improvements, but who is going to be a first-mover innovator in this policy area without fearing potential retribution should anything go wrong?…

Public servants don’t have the luxury of ‘making a new version’ without fear of blame or retribution. Critically, their process often lacks the ability to test assumptions before delivery….

The most persuasive or entertaining narrative often trumps the painstaking work — and potential missteps — required to build an evidence base to support political and policy decisions. American academics Elizabeth Shanahan, Mark McBeth and Paul Hathaway make a remarkable claim regarding the power of narrative in the policy world: “Research in the field of psychology shows that narratives have a stronger ability to persuade individuals and influence their beliefs than scientific evidence does.” If narrative and stories overtake what we normally accept as evidence, then surely we ought to be taking more notice of what the narratives are, which we choose and how we use them…

Failing the right way

Essential policy spheres such as health, education and social services should benefit from innovative thinking and theory testing. What is necessary in these areas is even more robust attention to carefully calibrated and well-thought through experimentation. Rewards need to outweigh risks, and risks need to be properly managed. This has always been the case in clinical trials in medicine. Incredible breakthroughs in medical practice made throughout the 20^th century speak to the success of this model. Why should policymaking suffer from a timid inertia given the potential for similar success?

An innovative approach, focused on learning while failing right, will certainly require a shift in thinking. Every new initiative will need to be designed in a holistic way, to not just solve an issue but learn from every stage of the design and delivery process. Evaluation doesn’t follow implementation but instead becomes part of the entire cycle. A small-scale, iterative approach can then lead to bigger successes down the track….(More)”.

Innovation for the Sustainable Development Goals

Curated on July 12, 2017August 3, 2018 by Stefaan Verhulst

UNDP: “In 2014, UNDP, with the generous support of the Government of Denmark, established an Innovation Facility to improve service delivery and support national governments and citizens to tackle complex challenges.

The report ‘Spark, Scale, Sustain’ shares UNDP’s approach to innovation, over 40 case studies of innovation for the Sustainable Development Goals in practice and Features on Alternative Finance, Behavioral Insights, Data Innovation and Public Policy Labs.

Download the report to find out more about the innovation initiatives that are testing and scaling solutions to address challenges across five areas: