Algorithms show potential in measuring diagnostic errors using big data

Curated on Posted on by Stefaan Verhulst

Greg Slabodkin at Information Management: “While the problem of diagnostic errors is widespread in medicine, with an estimated 12 million Americans affected annually, a new approach to quantifying and monitoring these errors has the potential to prevent serious patient injuries, including disability or death.

“The single biggest impediment to making progress is the lack of operational measures of diagnostic errors,” says David Newman-Toker, MD, director of the Johns Hopkins Armstrong Institute Center for Diagnostic Excellence. “It’s very difficult to measure because we haven’t had the tools to look for it in a systematic way. And most of the methods that look for diagnostics errors involve training people to do labor-intensive chart reviews.”

However, a new method—called the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE)—uncovers misdiagnosis-related harms using specific algorithms and big data. The automated approach could replace labor-intensive reviews of medical records by hospital staff, which researchers contend are limited by poor clinical documentation, low reliability and inherent bias.

According to Newman-Toker, SPADE utilizes statistical analyses to identify critical patterns that measure the rate of diagnostic error by analyzing large, existing clinical and claims datasets containing hundreds of thousands of patient visits. Specifically, algorithms are leveraged to look for common symptoms prompting a physician visit and then pairing them with one or more diseases that could be misdiagnosed in those clinical contexts….(More)”.

Can a reality TV show discourage corruption?

Curated on Posted on by Stefaan Verhulst

The Economist: “The timing could not have been better. In the same week as two civil servants in Nigeria appeared in court for embezzling funds earmarked for International Anti-Corruption Day, the finalists of “Integrity Idol” were announced. In this reality television show, honest civil servants working in corrupt countries compete for glory, fame and, occasionally, a live chicken. The show is a hit: over 10m people have watched it and more than 400,000 have cast their votes in favour of their Integrity Idols.

“Integrity Idol” started in Nepal in 2014 and has since spread to Pakistan, Mali, Liberia, Nigeria and South Africa. Five finalists, vetted by a panel of judges, are chosen to be interviewed. They explain why they deserve the prize. “I come to work late. My boss could ask ‘Why are you late?’ (…) I say I slept a little longer. Say it the way it is! Face the consequences!” one nominee exhorts.

It is not always easy to find good contestants. The Nigerian nomination period was extended because of the poor quality of entrants. “People were nominating their auntie because she gave them money,” says Odeh Friday, who runs the campaign. Others thought they qualified because they came to work on time. One policeman was surprised by his nomination because, he explained, he was involved in shady contracts. Another nominee resigned after he realised that background checks might dig up old dirt.

“Integrity Idol” claims to steer clear of politics. Elected officials may not be nominated. Nor, in some countries, may people in the army. Even so, the show delivers a punch in the face to crooked politicians and their cronies, sometimes just by its timing: in Liberia last year, it aired while presidential elections were embroiled in fraud investigations.

It is difficult to know what impact the show is having, though the Massachusetts Institute of Technology has begun to measure it. Change may be gradual. Gareth Newham at the Institute of Security Studies in South Africa thinks its greatest contribution will be in changing attitudes. “Too many young people believe that you can only get a job if you belong to the [ruling party]. What has been missing is a focus on the ordinary people who do good work.”…(More)”.

Handbook on Participatory Governance

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Book edited by Hubert Heinelt: “Can participatory governance really improve the quality of democracy? Concentrating on democracy beyond governmental structures, this Handbook argues that it is a political task to engage individuals at all levels of governance.

The Handbook on Participatory Governance reveals that transforming governance arrangements does in fact enhance democracy and that the democratic quality of participatory governance is crucial. The contributors reflect on the notion of democracy and participatory governance and how they relate to each other. Case studies are presented from regional, national and international levels, to identify how governance can be turned into a participatory form. With chapters reviewing participatory governance’s role alongside power, science and employment relations, innovative ideas for future progress in participatory governance are presented….(More)”.

2018 Edelman Trust Barometer

Curated on Posted on by Stefaan Verhulst

Executive Summary: “Volatility brews beneath a stagnant surface. If a single theme captures the state of the world’s trust in 2018, it is this. Even as people’s trust in business, government, NGOs and media across 28 countries remained largely unchanged, experiencing virtually no recovery from 2017 (Fig. 1), dramatic shifts are taking place at the country level and within the institution of media.

Globally, 20 of 28 countries lie in distruster territory (Fig. 2), one more than in 2017. Trust among the informed public—those with higher levels of income and education— declined slightly on a global level, from 60 percent to 59 percent, thrusting this group into neutral territory from its once trusting status. A closer look, however, reveals a world moving apart (Fig. 3).

In 2018, two poles have emerged: a cluster of six nations where trust has dramatically increased, and six where trust has deeply declined. Whereas in previous years country-level trust has moved largely in lockstep, for the first time ever there is now a distinct split between extreme trust gainers and losers. No country saw steeper declines than the United States, with a 37-point aggregate drop in trust across all institutions.

The loss of trust was most severe among the informed public—a 23-point fall on the Trust Index—nearly erasing the “mass-class” divide that once stood between this segment of the U.S. population and the country’s farless-trusting mass population. At the opposite end of the spectrum, China experienced a 27-point gain, more than any other country. Following behind in the trust gainer category are the UAE (24 points) and South Korea (23 points)….(More)”.

Is Social Media Good or Bad for Democracy?

Curated on Posted on by Stefaan Verhulst

Essay by Cass R. Sunstein,  as  part of a series by Facebook on social media and democracy: “On balance, the question of whether social media platforms are good for democracy is easy. On balance, they are not merely good; they are terrific. For people to govern themselves, they need to have information. They also need to be able to convey it to others. Social media platforms make that tons easier.

There is a subtler point as well. When democracies are functioning properly, people’s sufferings and challenges are not entirely private matters. Social media platforms help us alert one another to a million and one different problems. In the process, the existence of social media can prod citizens to seek solutions.

Consider the remarkable finding, by the economist Amartya Sen, that in the history of the world, there has never been a famine in a system with a democratic press and free elections. A central reason is that famines are a product not only of a scarcity of food, but also a nation’s failure to provide solutions. When the press is free, and when leaders are elected, leaders have a strong incentive to help.

Mental illness, chronic pain, loss of employment, vulnerability to crime, drugs in the family – information about all these spread via social media, and they can be reduced with sensible policies. When people can talk to each other, and disclose what they know to public officials, the whole world might change in a hurry.

But celebrations can be awfully boring, so let’s hold the applause. Are automobiles good for transportation? Absolutely, but in the United States alone, over 35,000 people died in crashes in 2016.

Social media platforms are terrific for democracy in many ways, but pretty bad in others. And they remain a work-in-progress, not only because of new entrants, but also because the not-so-new ones (including Facebook) continue to evolve. What John Dewey said about my beloved country is true for social media as well: “The United States are not yet made; they are not a finished fact to be categorically assessed.”

For social media and democracy, the equivalents of car crashes include false reports (“fake news”) and the proliferation of information cocoons — and as a result, an increase in fragmentation, polarization and extremism. If you live in an information cocoon, you will believe many things that are false, and you will fail to learn countless things that are true. That’s awful for democracy. And as we have seen, those with specific interests — including politicians and nations, such as Russia, seeking to disrupt democratic processes — can use social media to promote those interests.

This problem is linked to the phenomenon of group polarization — which takes hold when like-minded people talk to one another and end up thinking a more extreme version of what they thought before they started to talk. In fact that’s a common outcome. At best, it’s a problem. At worst, it’s dangerous….(More)”.

How the Data That Internet Companies Collect Can Be Used for the Public Good

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst and Andrew Young at Harvard Business Review: “…In particular, the vast streams of data generated through social media platforms, when analyzed responsibly, can offer insights into societal patterns and behaviors. These types of behaviors are hard to generate with existing social science methods. All this information poses its own problems, of complexity and noise, of risks to privacy and security, but it also represents tremendous potential for mobilizing new forms of intelligence.

In a recent report, we examine ways to harness this potential while limiting and addressing the challenges. Developed in collaboration with Facebook, the report seeks to understand how public and private organizations can join forces to use social media data — through data collaboratives — to mitigate and perhaps solve some our most intractable policy dilemmas.

Data Collaboratives: Public-Private Partnerships for Our Data Age 

For all of data’s potential to address public challenges, most data generated today is collected by the private sector. Typically ensconced in corporate databases, and tightly held in order to maintain competitive advantage, this data contains tremendous possible insights and avenues for policy innovation. But because the analytical expertise brought to bear on it is narrow, and limited by private ownership and access restrictions, its vast potential often goes untapped.

Data collaboratives offer a way around this limitation. They represent an emerging public-private partnership model, in which participants from different areas , including the private sector, government, and civil society , can come together to exchange data and pool analytical expertise in order to create new public value. While still an emerging practice, examples of such partnerships now exist around the world, across sectors and public policy domains….

Professionalizing the Responsible Use of Private Data for Public Good

For all its promise, the practice of data collaboratives remains ad hoc and limited. In part, this is a result of the lack of a well-defined, professionalized concept of data stewardship within corporations. Today, each attempt to establish a cross-sector partnership built on the analysis of social media data requires significant and time-consuming efforts, and businesses rarely have personnel tasked with undertaking such efforts and making relevant decisions.

As a consequence, the process of establishing data collaboratives and leveraging privately held data for evidence-based policy making and service delivery is onerous, generally one-off, not informed by best practices or any shared knowledge base, and prone to dissolution when the champions involved move on to other functions.

By establishing data stewardship as a corporate function, recognized within corporations as a valued responsibility, and by creating the methods and tools needed for responsible data-sharing, the practice of data collaboratives can become regularized, predictable, and de-risked.

If early efforts toward this end — from initiatives such as Facebook’s Data for Good efforts in the social media space and MasterCard’s Data Philanthropy approach around finance data — are meaningfully scaled and expanded, data stewards across the private sector can act as change agents responsible for determining what data to share and when, how to protect data, and how to act on insights gathered from the data.

Still, many companies (and others) continue to balk at the prospect of sharing “their” data, which is an understandable response given the reflex to guard corporate interests. But our research has indicated that many benefits can accrue not only to data recipients but also to those who share it. Data collaboration is not a zero-sum game.

With support from the Hewlett Foundation, we are embarking on a two-year project toward professionalizing data stewardship (and the use of data collaboratives) and establishing well-defined data responsibility approaches. We invite others to join us in working to transform this practice into a widespread, impactful means of leveraging private-sector assets, including social media data, to create positive public-sector outcomes around the world….(More)”.

 

Open Data Risk Assessment

Curated on Posted on by Stefaan Verhulst

Report by the Future of Privacy Forum: “The transparency goals of the open data movement serve important social, economic, and democratic functions in cities like Seattle. At the same time, some municipal datasets about the city and its citizens’ activities carry inherent risks to individual privacy when shared publicly. In 2016, the City of Seattle declared in its Open Data Policy that the city’s data would be “open by preference,” except when doing so may affect individual privacy. To ensure its Open Data Program effectively protects individuals, Seattle committed to performing an annual risk assessment and tasked the Future of Privacy Forum (FPF) with creating and deploying an initial privacy risk assessment methodology for open data.

This Report provides tools and guidance to the City of Seattle and other municipalities navigating the complex policy, operational, technical, organizational, and ethical standards that support privacyprotective open data programs. Although there is a growing body of research regarding open data privacy, open data managers and departmental data owners need to be able to employ a standardized methodology for assessing the privacy risks and benefits of particular datasets internally, without access to a bevy of expert statisticians, privacy lawyers, or philosophers. By optimizing its internal processes and procedures, developing and investing in advanced statistical disclosure control strategies, and following a flexible, risk-based assessment process, the City of Seattle – and other municipalities – can build mature open data programs that maximize the utility and openness of civic data while minimizing privacy risks to individuals and addressing community concerns about ethical challenges, fairness, and equity.

This Report first describes inherent privacy risks in an open data landscape, with an emphasis on potential harms related to re-identification, data quality, and fairness. To address these risks, the Report includes a Model Open Data Benefit-Risk Analysis (“Model Analysis”). The Model Analysis evaluates the types of data contained in a proposed open dataset, the potential benefits – and concomitant risks – of releasing the dataset publicly, and strategies for effective de-identification and risk mitigation. This holistic assessment guides city officials to determine whether to release the dataset openly, in a limited access environment, or to withhold it from publication (absent countervailing public policy considerations). …(More)”.

Is There Something Wrong with Democracy?

Curated on Posted on by Stefaan Verhulst

Max Fisher and Amanda Taub at The New York Times: “After 200 years of expansion, democracy’s growth in the world has stalled. A handful of democracies like Venezuela and Hungary are backsliding into authoritarianism. And even in established Western democracies, voters are losing faith in democratic institutions and norms.

That has left us and scholars who study democracy obsessed with a set of questions. Is this all just a blip, or is democracy in real trouble? Are the oldest and sturdiest democracies, like those of Europe and the United States, really as safe as they seem? And why would people voluntarily dismantle their own democracy from within?

No one knows the answers for sure. But we’re starting to figure them out and it’s not all good news. Here, in the first of what will become a regular series of videos exploring big questions and ideas about the world, we explain what we know about democracy’s troubles, what’s causing them and where it leads….(See VIDEO)”.

After Big Data: The Coming Age of “Big Indicators”

Curated on Posted on by Stefaan Verhulst

Andrew Zolli at the Stanford Social Innovation Review: “Consider, for a moment, some of the most pernicious challenges facing humanity today: the increasing prevalence of natural disasters; the systemic overfishing of the world’s oceans; the clear-cutting of primeval forests; the maddening persistence of poverty; and above all, the accelerating effects of global climate change.

Each item in this dark litany inflicts suffering on the world in its own, awful way. Yet as a group, they share some common characteristics. Each problem is messy, with lots of moving parts. Each is riddled with perverse incentives, which can lead local actors to behave in a way that is not in the common interest. Each is opaque, with dynamics that are only partially understood, even by experts; each can, as a result, often be made worse by seemingly rational and well-intentioned interventions. When things do go wrong, each has consequences that diverge dramatically from our day-to-day experiences, making their full effects hard to imagine, predict, and rehearse. And each is global in scale, raising questions about who has the legal obligation to act—and creating incentives for leaders to disavow responsibility (and sometimes even question the legitimacy of the problem itself).

With dynamics like these, it’s little wonder systems theorists label these kinds of problems “wicked” or even “super wicked.” It’s even less surprising that these challenges remain, by and large, externalities to the global system—inadequately measured, perennially underinvested in, and poorly accounted for—until their consequences spill disastrously and expensively into view.

For real progress to occur, we’ve got to move these externalities into the global system, so that we can fully assess their costs, and so that we can sufficiently incentivize and reward stakeholders for addressing them and penalize them if they don’t. And that’s going to require a revolution in measurement, reporting, and financial instrumentation—the mechanisms by which we connect global problems with the resources required to address them at scale.

Thankfully, just such a revolution is under way.

It’s a complex story with several moving parts, but it begins with important new technical developments in three critical areas of technology: remote sensing and big data, artificial intelligence, and cloud computing.

Remote sensing and big data allow us to collect unprecedented streams of observations about our planet and our impacts upon it, and dramatic advances in AI enable us to extract the deeper meaning and patterns contained in those vast data streams. The rise of the cloud empowers anyone with an Internet connection to access and interact with these insights, at a fraction of the traditional cost.

In the years to come, these technologies will shift much of the current conversation focused on big data to one focused on “big indicators”—highly detailed, continuously produced, global indicators that track change in the health of the Earth’s most important systems, in real time. Big indicators will form an important mechanism for guiding human action, allow us to track the impact of our collective actions and interventions as never before, enable better and more timely decisions, transform reporting, and empower new kinds of policy and financing instruments. In short, they will reshape how we tackle a number of global problems, and everyone—especially nonprofits, NGOs, and actors within the social and environmental sectors—will play a role in shaping and using them….(More)”.

Making Credit Ratings Data Publicly Available

Curated on Posted on by Stefaan Verhulst

Paper by Marc D. Joffe and Frank Partnoy: “In the aftermath of the 2007-08 global financial crisis, regulators and policy makers recognized the importance of making bond ratings publicly available. Although rating agencies have made some dataavailable, obtaining this information in bulk can be difficult or impossible. At some times, the data is costly; at other times, it is simply unavailable. Some rating agencies have provided data only on a subscription basis for tens or even hundreds of thousands of dollars annually.

The cost and lack of availability of ratings data are particularly striking given the regulatory requirement that rating agencies publish such data. We describe the relevant Securities and Exchange Commission publication rules and requirements. Unfortunately, the ways in which the major credit rating agencies have responded to these rules have not made data available in an easily accessed or comprehensive way and have instead hindered academic and think-tank research into credit ratings. Financial researchers who lack the funds required to purchase bulk ratings must use a variety of ad hoc methods to obtain rating data or limit their studies of credit ratings.

This brief paper describes our recent initiative to make credit ratings data publicly available. We provide links to a software tool written in Python that crawls credit rating agency websites, downloads the XRBL files, and converts them to Comma Separated Value (CSV) format. We also provide a link to the most recently processed ratings data, separated by agency and asset category, as well as the entire universe of ratings actions, including more than eight million assignments, upgrades, downgrades, and withdrawals…(More)”.