Health Insurance Archives

Archives For Health Insurance

The Problem of Data Property Rights

Dirk Auer — 23 March 2021

Policy discussions about the use of personal data often have “less is more” as a background assumption; that data is overconsumed relative to some hypothetical optimal baseline. This overriding skepticism has been the backdrop for sweeping new privacy regulations, such as the California Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR).

More recently, as part of the broad pushback against data collection by online firms, some have begun to call for creating property rights in consumers’ personal data or for data to be treated as labor. Prominent backers of the idea include New York City mayoral candidate Andrew Yang and computer scientist Jaron Lanier.

The discussion has escaped the halls of academia and made its way into popular media. During a recent discussion with Tesla founder Elon Musk, comedian and podcast host Joe Rogan argued that Facebook is “one gigantic information-gathering business that’s decided to take all of the data that people didn’t know was valuable and sell it and make f***ing billions of dollars.” Musk appeared to agree.

The animosity exhibited toward data collection might come as a surprise to anyone who has taken Econ 101. Goods ideally end up with those who value them most. A firm finding profitable ways to repurpose unwanted scraps is just the efficient reallocation of resources. This applies as much to personal data as to literal trash.

Unfortunately, in the policy sphere, few are willing to recognize the inherent trade-off between the value of privacy, on the one hand, and the value of various goods and services that rely on consumer data, on the other. Ideally, policymakers would look to markets to find the right balance, which they often can. When the transfer of data is hardwired into an underlying transaction, parties have ample room to bargain.

But this is not always possible. In some cases, transaction costs will prevent parties from bargaining over the use of data. The question is whether such situations are so widespread as to justify the creation of data property rights, with all of the allocative inefficiencies they entail. Critics wrongly assume the solution is both to create data property rights and to allocate them to consumers. But there is no evidence to suggest that, at the margin, heightened user privacy necessarily outweighs the social benefits that new data-reliant goods and services would generate. Recent experience in the worlds of personalized medicine and the fight against COVID-19 help to illustrate this point.

Data Property Rights and Personalized Medicine

The world is on the cusp of a revolution in personalized medicine. Advances such as the improved identification of biomarkers, CRISPR genome editing, and machine learning, could usher a new wave of treatments to markedly improve health outcomes.

Personalized medicine uses information about a person’s own genes or proteins to prevent, diagnose, or treat disease. Genetic-testing companies like 23andMe or Family Tree DNA, with the large troves of genetic information they collect, could play a significant role in helping the scientific community to further medical progress in this area.

However, despite the obvious potential of personalized medicine, many of its real-world applications are still very much hypothetical. While governments could act in any number of ways to accelerate the movement’s progress, recent policy debates have instead focused more on whether to create a system of property rights covering personal genetic data.

Some raise concerns that it is pharmaceutical companies, not consumers, who will reap the monetary benefits of the personalized medicine revolution, and that advances are achieved at the expense of consumers’ and patients’ privacy. They contend that data property rights would ensure that patients earn their “fair” share of personalized medicine’s future profits.

But it’s worth examining the other side of the coin. There are few things people value more than their health. U.S. governmental agencies place the value of a single life at somewhere between $1 million and $10 million. The commonly used quality-adjusted life year metric offers valuations that range from $50,000 to upward of $300,000 per incremental year of life.

It therefore follows that the trivial sums users of genetic-testing kits might derive from a system of data property rights would likely be dwarfed by the value they would enjoy from improved medical treatments. A strong case can be made that policymakers should prioritize advancing the emergence of new treatments, rather than attempting to ensure that consumers share in the profits generated by those potential advances.

These debates drew increased attention last year, when 23andMe signed a strategic agreement with the pharmaceutical company Almirall to license the rights related to an antibody Almirall had developed. Critics pointed out that 23andMe’s customers, whose data had presumably been used to discover the potential treatment, received no monetary benefits from the deal. Journalist Laura Spinney wrote in The Guardian newspaper:

23andMe, for example, asks its customers to waive all claims to a share of the profits arising from such research. But given those profits could be substantial—as evidenced by the interest of big pharma—shouldn’t the company be paying us for our data, rather than charging us to be tested?

In the deal’s wake, some argued that personal health data should be covered by property rights. A cardiologist quoted in Fortune magazine opined: “I strongly believe that everyone should own their medical data—and they have a right to that.” But this strong belief, however widely shared, ignores important lessons that law and economics has to teach about property rights and the role of contractual freedom.

Why Do We Have Property Rights?

Among the many important features of property rights is that they create “excludability,” the ability of economic agents to prevent third parties from using a given item. In the words of law professor Richard Epstein:

[P]roperty is not an individual conception, but is at root a social conception. The social conception is fairly and accurately portrayed, not by what it is I can do with the thing in question, but by who it is that I am entitled to exclude by virtue of my right. Possession becomes exclusive possession against the rest of the world…

Excludability helps to facilitate the trade of goods, offers incentives to create those goods in the first place, and promotes specialization throughout the economy. In short, property rights create a system of exclusion that supports creating and maintaining valuable goods, services, and ideas.

But property rights are not without drawbacks. Physical or intellectual property can lead to a suboptimal allocation of resources, namely market power (though this effect is often outweighed by increased ex ante incentives to create and innovate). Similarly, property rights can give rise to thickets that significantly increase the cost of amassing complementary pieces of property. Often cited are the historic (but contested) examples of tolling on the Rhine River or the airplane patent thicket of the early 20^th century. Finally, strong property rights might also lead to holdout behavior, which can be addressed through top-down tools, like eminent domain, or private mechanisms, like contingent contracts.

In short, though property rights—whether they cover physical or information goods—can offer vast benefits, there are cases where they might be counterproductive. This is probably why, throughout history, property laws have evolved to achieve a reasonable balance between incentives to create goods and to ensure their efficient allocation and use.

Personal Health Data: What Are We Trying to Incentivize?

There are at least three critical questions we should ask about proposals to create property rights over personal health data.

What goods or behaviors would these rights incentivize or disincentivize that are currently over- or undersupplied by the market?
Are goods over- or undersupplied because of insufficient excludability?
Could these rights undermine the efficient use of personal health data?

Much of the current debate centers on data obtained from direct-to-consumer genetic-testing kits. In this context, almost by definition, firms only obtain consumers’ genetic data with their consent. In western democracies, the rights to bodily integrity and to privacy generally make it illegal to administer genetic tests against a consumer or patient’s will. This makes genetic information naturally excludable, so consumers already benefit from what is effectively a property right.

When consumers decide to use a genetic-testing kit, the terms set by the testing firm generally stipulate how their personal data will be used. 23andMe has a detailed policy to this effect, as does Family Tree DNA. In the case of 23andMe, consumers can decide whether their personal information can be used for the purpose of scientific research:

You have the choice to participate in 23andMe Research by providing your consent. … 23andMe Research may study a specific group or population, identify potential areas or targets for therapeutics development, conduct or support the development of drugs, diagnostics or devices to diagnose, predict or treat medical or other health conditions, work with public, private and/or nonprofit entities on genetic research initiatives, or otherwise create, commercialize, and apply this new knowledge to improve health care.

Because this transfer of personal information is hardwired into the provision of genetic-testing services, there is space for contractual bargaining over the allocation of this information. The right to use personal health data will go toward the party that values it most, especially if information asymmetries are weeded out by existing regulations or business practices.

Regardless of data property rights, consumers have a choice: they can purchase genetic-testing services and agree to the provider’s data policy, or they can forgo the services. The service provider cannot obtain the data without entering into an agreement with the consumer. While competition between providers will affect parties’ bargaining positions, and thus the price and terms on which these services are provided, data property rights likely will not.

So, why do consumers transfer control over their genetic data? The main reason is that genetic information is inaccessible and worthless without the addition of genetic-testing services. Consumers must pass through the bottleneck of genetic testing for their genetic data to be revealed and transformed into usable information. It therefore makes sense to transfer the information to the service provider, who is in a much stronger position to draw insights from it. From the consumer’s perspective, the data is not even truly “transferred,” as the consumer had no access to it before the genetic-testing service revealed it. The value of this genetic information is then netted out in the price consumers pay for testing kits.

If personal health data were undersupplied by consumers and patients, testing firms could sweeten the deal and offer them more in return for their data. U.S. copyright law covers original compilations of data, while EU law gives 15 years of exclusive protection to the creators of original databases. Legal protections for trade secrets could also play some role. Thus, firms have some incentives to amass valuable health datasets.

But some critics argue that health data is, in fact, oversupplied. Generally, such arguments assert that agents do not account for the negative privacy externalities suffered by third-parties, such as adverse-selection problems in insurance markets. For example, Jay Pil Choi, Doh Shin Jeon, and Byung Cheol Kim argue:

Genetic tests are another example of privacy concerns due to informational externalities. Researchers have found that some subjects’ genetic information can be used to make predictions of others’ genetic disposition among the same racial or ethnic category. … Because of practical concerns about privacy and/or invidious discrimination based on genetic information, the U.S. federal government has prohibited insurance companies and employers from any misuse of information from genetic tests under the Genetic Information Nondiscrimination Act (GINA).

But if these externalities exist (most of the examples cited by scholars are hypothetical), they are likely dwarfed by the tremendous benefits that could flow from the use of personal health data. Put differently, the assertion that “excessive” data collection may create privacy harms should be weighed against the possibility that the same collection may also lead to socially valuable goods and services that produce positive externalities.

In any case, data property rights would do little to limit these potential negative externalities. Consumers and patients are already free to agree to terms that allow or prevent their data from being resold to insurers. It is not clear how data property rights would alter the picture.

Proponents of data property rights often claim they should be associated with some form of collective bargaining. The idea is that consumers might otherwise fail to receive their “fair share” of genetic-testing firms’ revenue. But what critics portray as asymmetric bargaining power might simply be the market signaling that genetic-testing services are in high demand, with room for competitors to enter the market. Shifting rents from genetic-testing services to consumers would undermine this valuable price signal and, ultimately, diminish the quality of the services.

Perhaps more importantly, to the extent that they limit the supply of genetic information—for example, because firms are forced to pay higher prices for data and thus acquire less of it—data property rights might hinder the emergence of new treatments. If genetic data is a key input to develop personalized medicines, adopting policies that, in effect, ration the supply of that data is likely misguided.

Even if policymakers do not directly put their thumb on the scale, data property rights could still harm pharmaceutical innovation. If existing privacy regulations are any guide—notably, the previously mentioned GDPR and CCPA, as well as the federal Health Insurance Portability and Accountability Act (HIPAA)—such rights might increase red tape for pharmaceutical innovators. Privacy regulations routinely limit firms’ ability to put collected data to new and previously unforeseen uses. They also limit parties’ contractual freedom when it comes to gathering consumers’ consent.

At the margin, data property rights would make it more costly for firms to amass socially valuable datasets. This would effectively move the personalized medicine space further away from a world of permissionless innovation, thus slowing down medical progress.

In short, there is little reason to believe health-care data is misallocated. Proposals to reallocate rights to such data based on idiosyncratic distributional preferences threaten to stifle innovation in the name of privacy harms that remain mostly hypothetical.

Data Property Rights and COVID-19

The trade-off between users’ privacy and the efficient use of data also has important implications for the fight against COVID-19. Since the beginning of the pandemic, several promising initiatives have been thwarted by privacy regulations and concerns about the use of personal data. This has potentially prevented policymakers, firms, and consumers from putting information to its optimal social use. High-profile issues have included:

Privacy fears derailing contact-tracing applications;
Privacy activists militating against the creation of vaccine passports and/or green passes; and
Objections to the use of search data to detect and predict COVID-19 clusters.

Each of these cases may involve genuine privacy risks. But to the extent that they do, those risks must be balanced against the potential benefits to society. If privacy concerns prevent us from deploying contact tracing or green passes at scale, we should question whether the privacy benefits are worth the cost. The same is true for rules that prohibit amassing more data than is strictly necessary, as is required by data-minimization obligations included in regulations such as the GDPR.

If our initial question was instead whether the benefits of a given data-collection scheme outweighed its potential costs to privacy, incentives could be set such that competition between firms would reduce the amount of data collected—at least, where minimized data collection is, indeed, valuable to users. Yet these considerations are almost completely absent in the COVID-19-related privacy debates, as they are in the broader privacy debate. Against this backdrop, the case for personal data property rights is dubious.

Conclusion

The key question is whether policymakers should make it easier or harder for firms and public bodies to amass large sets of personal data. This requires asking whether personal data is currently under- or over-provided, and whether the additional excludability that would be created by data property rights would offset their detrimental effect on innovation.

Swaths of personal data currently lie untapped. With the proper incentive mechanisms in place, this idle data could be mobilized to develop personalized medicines and to fight the COVID-19 outbreak, among many other valuable uses. By making such data more onerous to acquire, property rights in personal data might stifle the assembly of novel datasets that could be used to build innovative products and services.

On the other hand, when dealing with diffuse and complementary data sources, transaction costs become a real issue and the initial allocation of rights can matter a great deal. In such cases, unlike the genetic-testing kits example, it is not certain that users will be able to bargain with firms, especially where their personal information is exchanged by third parties.

If optimal reallocation is unlikely, should property rights go to the person covered by the data or to the collectors (potentially subject to user opt-outs)? Proponents of data property rights assume the first option is superior. But if the goal is to produce groundbreaking new goods and services, granting rights to data collectors might be a superior solution. Ultimately, this is an empirical question.

As Richard Epstein puts it, the goal is to “minimize the sum of errors that arise from expropriation and undercompensation, where the two are inversely related.” Rather than approach the problem with the preconceived notion that initial rights should go to users, policymakers should ensure that data flows to those economic agents who can best extract information and knowledge from it.

As things stand, there is little to suggest that the trade-offs favor creating data property rights. This is not an argument for requisitioning personal information or preventing parties from transferring data as they see fit, but simply for letting markets function, unfettered by misguided public policies.

The Antitrust Case Against Google’s Adtech Business, Explained

Manne, Bowman, and Fruits — 14 September 2020

This week the Senate will hold a hearing into potential anticompetitive conduct by Google in its display advertising business—the “stack” of products that it offers to advertisers seeking to place display ads on third-party websites. It is also widely reported that the Department of Justice is preparing a lawsuit against Google that will likely include allegations of anticompetitive behavior in this market, and is likely to be joined by a number of state attorneys general in that lawsuit. Meanwhile, several papers have been published detailing these allegations.

This aspect of digital advertising can be incredibly complex and difficult to understand. Here we explain how display advertising fits in the broader digital advertising market, describe how display advertising works, consider the main allegations against Google, and explain why Google’s critics are misguided to focus on antitrust as a solution to alleged problems in the market (even if those allegations turn out to be correct).

Display advertising in context

Over the past decade, the price of advertising has fallen steadily while output has risen. Spending on digital advertising in the US grew from $26 billion in 2010 to nearly $130 billion in 2019, an average increase of 20% a year. Over the same period the Producer Price Index for Internet advertising sales declined by nearly 40%. The rising spending in the face of falling prices indicates the number of ads bought and sold increased by approximately 27% a year. Since 2000, advertising spending has been falling as a share of GDP, with online advertising growing as a share of that. The combination of increasing quantity, decreasing cost, and increasing total revenues are consistent with a growing and increasingly competitive market.

Display advertising on third-party websites is only a small subsection of the digital advertising market, comprising approximately 15-20% of digital advertising spending in the US. The rest of the digital advertising market is made up of ads on search results pages on sites like Google, Amazon and Kayak, on people’s Instagram and Facebook feeds, listings on sites like Zillow (for houses) or Craigslist, referral fees paid to price comparison websites for things like health insurance, audio and visual ads on services like Spotify and Hulu, and sponsored content from influencers and bloggers who will promote products to their fans.

And digital advertising itself is only one of many channels through which companies can market their products. About 53% of total advertising spending in the United States goes on digital channels, with 30% going on TV advertising and the rest on things like radio ads, billboards and other more traditional forms of advertising. A few people still even read physical newspapers and the ads they contain, although physical newspapers’ bigger money makers have traditionally been classified ads, which have been replaced by less costly and more effective internet classifieds, such as those offered by Craigslist, or targeted ads on Google Maps or Facebook.

Indeed, it should be noted that advertising itself is only part of the larger marketing market of which non-advertising marketing communication—e.g., events, sales promotion, direct marketing, telemarketing, product placement—is as big a part as is advertising (each is roughly $500bn globally); it just hasn’t been as thoroughly disrupted by the Internet yet. But it is a mistake to assume that digital advertising is not a part of this broader market. And of that $1tr global market, Internet advertising in total occupies only about 18%—and thus display advertising only about 3%.

Ad placement is only one part of the cost of digital advertising. An advertiser trying to persuade people to buy its product must also do market research and analytics to find out who its target market is and what they want. Moreover, there are the costs of designing and managing a marketing campaign and additional costs to analyze and evaluate the effectiveness of the campaign.

Nevertheless, one of the most straightforward ways to earn money from a website is to show ads to readers alongside the publisher’s content. To satisfy publishers’ demand for advertising revenues, many services have arisen to automate and simplify the placement of and payment for ad space on publishers’ websites. Google plays a large role in providing these services—what is referred to as “open display” advertising. And it is Google’s substantial role in this space that has sparked speculation and concern among antitrust watchdogs and enforcement authorities.

Before delving into the open display advertising market, a quick note about terms. In these discussions, “advertisers” are businesses that are trying to sell people stuff. Advertisers include large firms such as Best Buy and Disney and small businesses like the local plumber or financial adviser. “Publishers” are websites that carry those ads, and publish content that users want to read. Note that the term “publisher” refers to all websites regardless of the things they’re carrying: a blog about the best way to clean stains out of household appliances is a “publisher” just as much as the New York Times is.

Under this broad definition, Facebook, Instagram, and YouTube are also considered publishers. In their role as publishers, they have a common goal: to provide content that attracts users to their pages who will act on the advertising displayed. “Users” are you and me—the people who want to read publishers’ content, and to whom advertisers want to show ads. Finally, “intermediaries” are the digital businesses, like Google, that sit in between the advertisers and the publishers, allowing them to do business with each other without ever meeting or speaking.

The display advertising market

If you’re an advertiser, display advertising works like this: your company—one that sells shoes, let’s say—wants to reach a certain kind of person and tell her about the company’s shoes. These shoes are comfortable, stylish, and inexpensive. You use a tool like Google Ads (or, if it’s a big company and you want a more expansive campaign over which you have more control, Google Marketing Platform) to design and upload an ad, and tell Google about the people you want to read—their age and location, say, and/or characterizations of their past browsing and searching habits (“interested in sports”).

Using that information, Google finds ad space on websites whose audiences match the people you want to target. This ad space is auctioned off to the highest bidder among the range of companies vying, with your shoe company, to reach users matching the characteristics of the website’s users. Thanks to tracking data, it doesn’t just have to be sports-relevant websites: as a user browses sports-related sites on the web, her browser picks up files (cookies) that will tag her as someone potentially interested in sports apparel for targeting later.

So a user might look at a sports website and then later go to a recipe blog, and there receive the shoes ad on the basis of her earlier browsing. You, the shoe seller, hope that she will either click through and buy (or at least consider buying) the shoes when she sees those ads, but one of the benefits of display advertising over search advertising is that—as with TV ads or billboard ads—just seeing the ad will make her aware of the product and potentially more likely to buy it later. Advertisers thus sometimes pay on the basis of clicks, sometimes on the basis of views, and sometimes on the basis of conversion (when a consumer takes an action of some sort, such as making a purchase or filling out a form).

That’s the advertiser’s perspective. From the publisher’s perspective—the owner of that recipe blog, let’s say—you want to auction ad space off to advertisers like that shoe company. In that case, you go to an ad server—Google’s product is called AdSense—give them a little bit of information about your site, and add some html code to your website. These ad servers gather information about your content (e.g., by looking at keywords you use) and your readers (e.g., by looking at what websites they’ve used in the past to make guesses about what they’ll be interested in) and places relevant ads next to and among your content. If they click, lucky you—you’ll get paid a few cents or dollars.

Apart from privacy concerns about the tracking of users, the really tricky and controversial part here concerns the way scarce advertising space is allocated. Most of the time, it’s done through auctions that happen in real time: each time a user loads a website, an auction is held in a fraction of a second to decide which advertiser gets to display an ad. The longer this process takes, the slower pages load and the more likely users are to get frustrated and go somewhere else.

As well as the service hosting the auction, there are lots of little functions that different companies perform that make the auction and placement process smoother. Some fear that by offering a very popular product integrated end to end, Google’s “stack” of advertising products can bias auctions in favour of its own products. There’s also speculation that Google’s product is so tightly integrated and so effective at using data to match users and advertisers that it is not viable for smaller rivals to compete.

We’ll discuss this speculation and fear in more detail below. But it’s worth bearing in mind that this kind of real-time bidding for ad placement was not always the norm, and is not the only way that websites display ads to their users even today. Big advertisers and websites often deal with each other directly. As with, say, TV advertising, large companies advertising often have a good idea about the people they want to reach. And big publishers (like popular news websites) often have a good idea about who their readers are. For example, big brands often want to push a message to a large number of people across different customer types as part of a broader ad campaign.

Of these kinds of direct sales, sometimes the space is bought outright, in advance, and reserved for those advertisers. In most cases, direct sales are run through limited, intermediated auction services that are not open to the general market. Put together, these kinds of direct ad buys account for close to 70% of total US display advertising spending. The remainder—the stuff that’s left over after these kinds of sales have been done—is typically sold through the real-time, open display auctions described above.

Different adtech products compete on their ability to target customers effectively, to serve ads quickly (since any delay in the auction and ad placement process slows down page load times for users), and to do so inexpensively. All else equal (including the effectiveness of the ad placement), advertisers want to pay the lowest possible price to place an ad. Similarly, publishers want to receive the highest possible price to display an ad. As a result, both advertisers and publishers have a keen interest in reducing the intermediary’s “take” of the ad spending.

This is all a simplification of how the market works. There is not one single auction house for ad space—in practice, many advertisers and publishers end up having to use lots of different auctions to find the best price. As the market evolved to reach this state from the early days of direct ad buys, new functions that added efficiency to the market emerged.

In the early years of ad display auctions, individual processes in the stack were performed by numerous competing companies. Through a process of “vertical integration” some companies, such as Google, brought these different processes under the same roof, with the expectation that integration would streamline the stack and make the selling and placement of ads more efficient and effective. The process of vertical integration in pursuit of efficiency has led to a more consolidated market in which Google is the largest player, offering simple, integrated ad buying products to advertisers and ad selling products to publishers.

Google is by no means the only integrated adtech service provider, however: Facebook, Amazon, Verizon, AT&T/Xandr, theTradeDesk, LumenAd, Taboola and others also provide end-to-end adtech services. But, in the market for open auction placement on third-party websites, Google is the biggest.

The cases against Google

The UK’s Competition and Markets Authority (CMA) carried out a formal study into the digital advertising market between 2019 and 2020, issuing its final report in July of this year. Although also encompassing Google’s Search advertising business and Facebook’s display advertising business (both of which relate to ads on those companies “owned and operated” websites and apps), the CMA study involved the most detailed independent review of Google’s open display advertising business to date.

That study did not lead to any competition enforcement proceedings, but it did conclude that Google’s vertically integrated products led to conflicts of interest that could lead it to behaving in ways that did not benefit the advertisers and publishers that use it. One example was Google’s withholding of certain data from publishers that would make it easier for them to use other ad selling products; another was the practice of setting price floors that allegedly led advertisers to pay more than they would otherwise.

Instead the CMA recommended the setting up of a “Digital Markets Unit” (DMU) that could regulate digital markets in general, and a code of conduct for Google and Facebook (and perhaps other large tech platforms) intended to govern their dealings with smaller customers.

The CMA’s analysis is flawed, however. For instance, it makes big assumptions about the dependency of advertisers on display advertising, largely assuming that they would not switch to other forms of advertising if prices rose, and it is light on economics. But factually it is the most comprehensively researched investigation into digital advertising yet published.

Piggybacking on the CMA’s research, and mounting perhaps the strongest attack on Google’s adtech offerings to date, was a paper released just prior to the CMA’s final report called “Roadmap for a Digital Advertising Monopolization Case Against Google”, by Yale economist Fiona Scott Morton and Omidyar Network lawyer David Dinielli. Dinielli will testify before the Senate committee.

While the Scott Morton and Dinielli paper is extremely broad, it also suffers from a number of problems.

One, because it was released before the CMA’s final report, it is largely based on the interim report released months earlier by the CMA, halfway through the market study in December 2019. This means that several of its claims are out of date. For example, it makes much of the possibility raised by the CMA in its interim report that Google may take a larger cut of advertising spending than its competitors, and claims made in another report that Google introduces “hidden” fees that increases the overall cut it takes from ad auctions.

But in the final report, after further investigation, the CMA concludes that this is not the case. In the final report, the CMA describes its analysis of all Google Ad Manager open auctions related to UK web traffic during the period between 8–14 March 2020 (involving billions of auctions). This, according to the CMA, allowed it to observe any possible “hidden” fees as well. The CMA concludes:

Our analysis found that, in transactions where both Google Ads and Ad Manager (AdX) are used, Google’s overall take rate is approximately 30% of advertisers’ spend. This is broadly in line with (or slightly lower than) our aggregate market-wide fee estimate outlined above. We also calculated the margin between the winning bid and the second highest bid in AdX for Google and non-Google DSPs, to test whether Google was systematically able to win with a lower margin over the second highest bid (which might have indicated that they were able to use their data advantage to extract additional hidden fees). We found that Google’s average winning margin was similar to that of non-Google DSPs. Overall, this evidence does not indicate that Google is currently extracting significant hidden fees. As noted below, however, it retains the ability and incentive to do so. (p. 275, emphasis added)

Scott Morton and Dinielli also misquote and/or misunderstand important sections of the CMA interim report as relating to display advertising when, in fact, they relate to search. For example, Scott Morton and Dinielli write that the “CMA concluded that Google has nearly insurmountable advantages in access to location data, due to the location information [uniquely available to it from other sources].” (p. 15). The CMA never makes any claim of “insurmountable advantage,” however. Rather, to support the claim, Scott Morton and Dinielli cite to a portion of the CMA interim report recounting a suggestion made by Microsoft regarding the “critical” value of location data in providing relevant advertising.

But that portion of the report, as well as the suggestion made by Microsoft, is about search advertising. While location data may also be valuable for display advertising, it is not clear that the GPS-level data that is so valuable in providing mobile search ad listings (for a nearby cafe or restaurant, say) is particularly useful for display advertising, which may be just as well-targeted by less granular, city- or county-level location data, which is readily available from a number of sources. In any case, Scott Morton and Dinielli are simply wrong to use a suggestion offered by Microsoft relating to search advertising to demonstrate the veracity of an assertion about a conclusion drawn by the CMA regarding display advertising.

Scott Morton and Dinielli also confusingly word their own judgements about Google’s conduct in ways that could be misinterpreted as conclusions by the CMA:

The CMA reports that Google has implemented an anticompetitive sales strategy on the publisher ad server end of the intermediation chain. Specifically, after purchasing DoubleClick, which became its publisher ad server, Google apparently lowered its prices to publishers by a factor of ten, at least according to one publisher’s account related to the CMA. (p. 20)

In fact, the CMA does not conclude that Google lowering its prices was an “anticompetitive sales strategy”—it does not use these words at all—and what Scott Morton and Dinielli are referring to is a claim by a rival ad server business, Smart, that Google cutting its prices after acquiring Doubleclick led to Google expanding its market share. Apart from the misleading wording, it is unclear why a competition authority should consider it to be “anticompetitive” when prices are falling and kept low, and—as Smart reported to the CMA—its competitor’s response is to enhance its own offering.

The case that remains

Stripping away the elements of Scott Morton and Dinielli’s case that seem unsubstantiated by a more careful reading of the CMA reports, and with the benefit of the findings in the CMA’s final report, we are left with a case that argues that Google self-preferences to an unreasonable extent, giving itself a product that is as successful as it is in display advertising only because of Google’s unique ability to gain advantage from its other products that have little to do with display advertising. Because of this self-preferencing, they might argue, innovative new entrants cannot compete on an equal footing, so the market loses out on incremental competition because of the advantages Google gets from being the world’s biggest search company, owning YouTube, running Google Maps and Google Cloud, and so on.

The most significant examples of this are Google’s use of data from other products—like location data from Maps or viewing history from YouTube—to target ads more effectively; its ability to enable advertisers placing search ads to easily place display ads through the same interface; its introduction of faster and more efficient auction processes that sidestep the existing tools developed by other third-party ad exchanges; and its design of its own tool (“open bidding”) for aggregating auction bids for advertising space to compete with (rather than incorporate) an alternative tool (“header bidding”) that is arguably faster, but costs more money to use.

These allegations require detailed consideration, and in a future paper we will attempt to assess them in detail. But in thinking about them now it may be useful to consider the remedies that could be imposed to address them, assuming they do diminish the ability of rivals to compete with Google: what possible interventions we could make in order to make the market work better for advertisers, publishers, and users.

We can think of remedies as falling into two broad buckets: remedies that stop Google from doing things that improve the quality of its own offerings, thus making it harder for others to keep up; and remedies that require it to help rivals improve their products in ways otherwise accessible only to Google (e.g., by making Google’s products interoperable with third-party services) without inherently diminishing the quality of Google’s own products.

The first camp of these, what we might call “status quo minus,” includes rules banning Google from using data from its other products or offering single order forms for advertisers, or, in the extreme, a structural remedy that “breaks up” Google by either forcing it to sell off its display ad business altogether or to sell off elements of it.

What is striking about these kinds of interventions is that all of them “work” by making Google worse for those that use it. Restrictions on Google’s ability to use data from other products, for example, will make its service more expensive and less effective for those who use it. Ads will be less well-targeted and therefore less effective. This will lead to lower bids from advertisers. Lower ad prices will be transmitted through the auction process to produce lower payments for publishers. Reduced publisher revenues will mean some content providers exit. Users will thus be confronted with less available content and ads that are less relevant to them and thus, presumably, more annoying. In other words: No one will be better off, and most likely everyone will be worse off.

The reason a “single order form” helps Google is that it is useful to advertisers, the same way it’s useful to be able to buy all your groceries at one store instead of lots of different ones. Similarly, vertical integration in the “ad stack” allows for a faster, cheaper, and simpler product for users on all sides of the market. A different kind of integration that has been criticized by others, where third-party intermediaries can bid more quickly if they host on Google Cloud, benefits publishers and users because it speeds up auction time, allowing websites to load faster. So does Google’s unified alternative to “header bidding,” giving a speed boost that is apparently valuable enough to publishers that they will pay for it.

So who would benefit from stopping Google from doing these things, or even forcing Google to sell its operations in this area? Not advertisers or publishers. Maybe Google’s rival ad intermediaries would; presumably, artificially hamstringing Google’s products would make it easier for them to compete with Google. But if so, it’s difficult to see how this would be an overall improvement. It is even harder to see how this would improve the competitive process—the very goal of antitrust. Rather, any increase in the competitiveness of rivals would result not from making their products better, but from making Google’s product worse. That is a weakening of competition, not its promotion.

On the other hand, interventions that aim to make Google’s products more interoperable at least do not fall prey to this problem. Such “status quo plus” interventions would aim to take the benefits of Google’s products and innovations and allow more companies to use them to improve their own competing products. Not surprisingly, such interventions would be more in line with the conclusions the CMA came to than the divestitures and operating restrictions proposed by Scott Morton and Dinielli, as well as (reportedly) state attorneys general considering a case against Google.

But mandated interoperability raises a host of different concerns: extensive and uncertain rulemaking, ongoing regulatory oversight, and, likely, price controls, all of which would limit Google’s ability to experiment with and improve its products. The history of such mandated duties to deal or compulsory licenses is a troubled one, at best. But even if, for the sake of argument, we concluded that these kinds of remedies were desirable, they are difficult to impose via an antitrust lawsuit of the kind that the Department of Justice is expected to launch. Most importantly, if the conclusion of Google’s critics is that Google’s main offense is offering a product that is just too good to compete with without regulating it like a utility, with all the costs to innovation that that would entail, maybe we ought to think twice about whether an antitrust intervention is really worth it at all.

Privacy in the Time of Covid-19

Christine Wilson — 15 April 2020

[TOTM: The following is part of a blog series by TOTM guests and authors on the law, economics, and policy of the ongoing COVID-19 pandemic. The entire series of posts is available here.

This post is authored by Christine S. Wilson (Commissioner of the U.S. Federal Trade Commission).^[1] The views expressed here are the author’s and do not necessarily reflect those of the Federal Trade Commission or any other Commissioner.]

I type these words while subject to a stay-at-home order issued by West Virginia Governor James C. Justice II. “To preserve public health and safety, and to ensure the healthcare system in West Virginia is capable of serving all citizens in need,” I am permitted to leave my home only for a limited and precisely enumerated set of reasons. Billions of citizens around the globe are now operating under similar shelter-in-place directives as governments grapple with how to stem the tide of infection, illness and death inflicted by the global Covid-19 pandemic. Indeed, the first response of many governments has been to impose severe limitations on physical movement to contain the spread of the novel coronavirus. The second response contemplated by many, and the one on which this blog post focuses, involves the extensive collection and analysis of data in connection with people’s movements and health. Some governments are using that data to conduct sophisticated contact tracing, while others are using the power of the state to enforce orders for quarantines and against gatherings.

The desire to use modern technology on a broad scale for the sake of public safety is not unique to this moment. Technology is intended to improve the quality of our lives, in part by enabling us to help ourselves and one another. For example, cell towers broadcast wireless emergency alerts to all mobile devices in the area to warn us of extreme weather and other threats to safety in our vicinity. One well-known type of broadcast is the Amber Alert, which enables community members to assist in recovering an abducted child by providing descriptions of the abductor, the abductee and the abductor’s vehicle. Citizens who spot individuals and vehicles that meet these descriptions can then provide leads to law enforcement authorities. A private nonprofit organization, the National Center for Missing and Exploited Children, coordinates with state and local public safety officials to send out Amber Alerts through privately owned wireless carriers.

The robust civil society and free market in the U.S. make partnerships between the private sector and government agencies commonplace. But some of these arrangements involve a much more extensive sharing of Americans’ personal information with law enforcement than the emergency alert system does.

For example, Amazon’s home security product Ring advertises itself not only as a way to see when a package has been left at your door, but also as a way to make communities safer by turning over video footage to local police departments. In 2018, the company’s pilot program in Newark, New Jersey, donated more than 500 devices to homeowners to install at their homes in two neighborhoods, with a big caveat. Ring recipients were encouraged to share video with police.According to Ring, home burglaries in those neighborhoods fell by more than 50% from April through July 2018 relative to the same time period a year earlier.

Yet members of Congress and privacy experts have raised concerns about these partnerships, which now number in the hundreds. After receiving Amazon’s response to his inquiry, Senator Edward Markey highlighted Ring’s failure to prevent police from sharing video footage with third parties and from keeping the video permanently, and Ring’s lack of precautions to ensure that users collect footage only of adults and of users’ own property. The House of Representatives Subcommittee on Economic and Consumer Policy continues to investigate Ring’s police partnerships and data policies. The Electronic Frontier Foundation has called Ring “a perfect storm of privacy threats,” while the UK surveillance camera commissioner has warned against “a very real power to understand, to surveil you in a way you’ve never been surveilled before.”

Ring demonstrates clearly that it is not new for potential breaches of privacy to be encouraged in the name of public safety; police departments urge citizens to use Ring and share the videos with police to fight crime. But emerging developments indicate that, in the fight against Covid-19, we can expect to see more and more private companies placed in the difficult position of becoming complicit in government overreach.

At least mobile phone users can opt out of receiving Amber Alerts, and residents can refuse to put Ring surveillance systems on their property. The Covid-19 pandemic has made some other technological intrusions effectively impossible to refuse. For example, online proctors who monitor students over webcams to ensure they do not cheat on exams taken at home were once something that students could choose to accept if they did not want to take an exam where and when they could be proctored face to face. With public schools and universities across the U.S. closed for the rest of the semester, students who refuse to give private online proctors access to their webcams – and, consequently, the ability to view their surroundings – cannot take exams at all.

Existing technology and data practices already have made the Federal Trade Commission sensitive to potential consumer privacy and data security abuses. For decades, this independent, bipartisan agency has been enforcing companies’ privacy policies through its authority to police unfair and deceptive trade practices. It brought its first privacy and data security cases nearly 20 years ago, while I was Chief of Staff to then-Chairman Timothy J. Muris. The FTC took on Eli Lilly for disclosing the e-mail addresses of 669 subscribers to its Prozac reminder service – many of whom were government officials, and at a time of greater stigma for mental health issues – and Microsoft for (among other things) falsely claiming that its Passport website sign-in service did not collect any personally identifiable information other than that described in its privacy policy.

The privacy and data security practices of healthcare and software companies are likely to impact billions of people during the current coronavirus pandemic. The U.S. already has many laws on the books that are relevant to practices in these areas. One notable example is the Health Insurance Portability and Accountability Act, which set national standards for the protection of individually identifiable health information by health plans, health care clearinghouses and health care providers who accept non-cash payments. While the FTC does not enforce HIPAA, it does enforce the Health Breach Notification Rule, as well as the provisions in the FTC Act used to challenge the privacy missteps of Eli Lilly and many other companies.

But technological developments have created gaps in HIPAA enforcement. For example, HIPAA applies to doctors’ offices, hospitals and insurance companies, but it may not apply to wearables, smartphone apps or websites. Yet sensitive medical information is now commonly stored in places other than health care practitioners’ offices. Your phone and watch now collect information about your blood sugar, exercise habits, fertility and heart health.

Observers have pointed to these emerging gaps in coverage as evidence of the growing need for federal privacy legislation. I, too, have called on the U.S. Congress to enact comprehensive federal privacy legislation – not only to address these emerging gaps, but for two other reasons. First, consumers need clarity regarding the types of data collected from them, and how those data are used and shared. I believe consumers can make informed decisions about which goods and services to patronize when they have the information they need to evaluate the costs and benefits of using those goods. Second, businesses need predictability and certainty regarding the rules of the road, given the emerging patchwork of regimes both at home and abroad.

Rules of the road regarding privacy practices will prove particularly instructive during this global pandemic, as governments lean on the private sector for data on the grounds that the collection and analysis of data can help avert (or at least diminish to some extent) a public health catastrophe. With legal lines in place, companies would be better equipped to determine when they are being asked to cross the line for the public good, and whether they should require a subpoena or inform customers before turning over data. It is regrettable that Congress has been unable to enact federal privacy legislation to guide this discussion.

Understandably, Congress does not have privacy at the top of its agenda at the moment, as the U.S. faces a public health crisis. As I write, more than 579,000 Americans have been diagnosed with Covid-19, and more than 22,000 have perished. Sadly, those numbers will only increase. And the U.S. is not alone in confronting this crisis: governments globally have confronted more than 1.77 million cases and more than 111,000 deaths. For a short time, health and safety issues may take precedence over privacy protections. But some of the initiatives to combat the coronavirus pandemic are worrisome. We are learning more every day about how governments are responding in a rapidly developing situation; what I describe in the next section constitutes merely the tip of the iceberg. These initiatives are worth highlighting here, as are potential safeguards for privacy and civil liberties that societies around the world would be wise to embrace.

Some observers view public/private partnerships based on an extensive use of technology and data as key to fighting the spread of Covid-19. For example, Professor Jane Bambauer calls for contact tracing and alerts “to be done in an automated way with the help of mobile service providers’ geolocation data.” She argues that privacy is merely “an instrumental right” that “is meant to achieve certain social goals in fairness, safety and autonomy. It is not an end in itself.” Given the “more vital” interests in health and the liberty to leave one’s house, Bambauer sees “a moral imperative” for the private sector “to ignore even express lack of consent” by an individual to the sharing of information about him.

This proposition troubles me because the extensive data sharing that has been proposed in some countries, and that is already occurring in many others, is not mundane. In the name of advertising and product improvements, private companies have been hoovering up personal data for years. What this pandemic lays bare, though, is that while this trove of information was collected under the guise of cataloguing your coffee preferences and transportation habits, it can be reprocessed in an instant to restrict your movements, impinge on your freedom of association, and silence your freedom of speech. Bambauer is calling for detailed information about an individual’s every movement to be shared with the government when, in the United States under normal circumstances, a warrant would be required to access this information.

Indeed, with our mobile devices acting as the “invisible policeman” described by Justice William O. Douglas in Berger v. New York, we may face “a bald invasion of privacy, far worse than the general warrants prohibited by the Fourth Amendment.” Backward-looking searches and data hoards pose new questions of what constitutes a “reasonable” search. The stakes are high – both here and abroad, citizens are being asked to allow warrantless searches by the government on an astronomical scale, all in the name of public health.

Abroad

The first country to confront the coronavirus was China. The World Health Organization has touted the measures taken by China as “the only measures that are currently proven to interrupt or minimize transmission chains in humans.” Among these measures are the “rigorous tracking and quarantine of close contacts,” as well as “the use of big data and artificial intelligence (AI) to strengthen contact tracing and the management of priority populations.” An ambassador for China has said his government “optimized the protocol of case discovery and management in multiple ways like backtracking the cell phone positioning.” Much as the Communist Party’s control over China enabled it to suppress early reports of a novel coronavirus, this regime vigorously ensured its people’s compliance with the “stark” containment measures described by the World Health Organization.

Before the Covid-19 pandemic, Hong Kong already had been testing the use of “smart wristbands” to track the movements of prisoners. The Special Administrative Region now monitors people quarantined inside their homes by requiring them to wear wristbands that send information to the quarantined individuals’ smartphones and alert the Department of Health and Police if people leave their homes, break their wristbands or disconnect them from their smartphones. When first announced in early February, the wristbands were required only for people who had been to Wuhan in the past 14 days, but the program rapidly expanded to encompass every person entering Hong Kong. The government denied any privacy concerns about the electronic wristbands, saying the Privacy Commissioner for Personal Data had been consulted about the technology and agreed it could be used to ensure that quarantined individuals remain at home.

Elsewhere in Asia, Taiwan’s Chunghwa Telecom has developed a system that the local CDC calls an “electronic fence.” Specifically, the government obtains the SIM card identifiers for the mobile devices of quarantined individuals and passes those identifiers to mobile network operators, which use phone signals to their cell towers to alert public health and law enforcement agencies when the phone of a quarantined individual leaves a certain geographic range. In response to privacy concerns, the National Communications Commission said the system was authorized by special laws to prevent the coronavirus, and that it “does not violate personal data or privacy protection.” In Singapore, travelers and others issued Stay-Home Notices to remain in their residency 24 hours a day for 14 days must respond within an hour if contacted by government agencies by phone, text message or WhatsApp. And to assist with contact tracing, the government has encouraged everyone in the country to download TraceTogether, an app that uses Bluetooth to identify other nearby phones with the app and tracks when phones are in close proximity.

Israel’s Ministry of Health has launched an app for mobile devices called HaMagen (the shield) to prevent the spread of coronavirus by identifying contacts between diagnosed patients and people who came into contact with them in the 14 days prior to diagnosis. In March, the prime minister’s cabinet initially bypassed the legislative body to approve emergency regulations for obtaining without a warrant the cellphone location data and additional personal information of those diagnosed with or suspected of coronavirus infection. The government will send text messages to people who came into contact with potentially infected individuals, and will monitor the potentially infected person’s compliance with quarantine. The Ministry of Health will not hold this information; instead, it can make data requests to the police and Shin Bet, the Israel Security Agency. The police will enforce quarantine measures and Shin Bet will track down those who came into contact with the potentially infected.

Multiple Eastern European nations with constitutional protections for citizens’ rights of movement and privacy have superseded them by declaring a state of emergency. For example, in Hungary the declaration of a “state of danger” has enabled Prime Minister Viktor Orbán’s government to engage in “extraordinary emergency measures” without parliamentary consent. His ministers have cited the possibility that coronavirus will prevent a gathering of a sufficient quorum of members of Parliament as making it necessary for the government to be able to act in the absence of legislative approval.

Member States of the European Union must protect personal data pursuant to the General Data Protection Regulation, and communications data, such as mobile location, pursuant to the ePrivacy Directive. The chair of the European Data Protection Board has observed that the ePrivacy Directive enables Member States to introduce legislative measures to safeguard public security. But if those measures allow for the processing of non-anonymized location data from mobile devices, individuals must have safeguards such as a right to a judicial remedy. “Invasive measures, such as the ‘tracking’ of individuals (i.e. processing of historical non-anonymized location data) could be considered proportional under exceptional circumstances and depending on the concrete modalities of the processing.” The EDPB has announced it will prioritize guidance on these issues.

EU Member States are already implementing such public security measures. For example, the government of Poland has by statute required everyone under a quarantine order due to suspected infection to download the “Home Quarantine” smartphone app. Those who do not install and use the app are subject to a fine. The app verifies users’ compliance with quarantine through selfies and GPS data. Users’ personal data will be administered by the Minister of Digitization, who has appointed a data protection officer. Each user’s identification, name, telephone number, quarantine location and quarantine end date can be shared with police and other government agencies. After two weeks, if the user does not report symptoms of Covid-19, the account will be deactivated — but the data will be stored for six years. The Ministry of Digitization claims that it must store the data for six years in case users pursue claims against the government. However, local privacy expert and Panoptykon Foundation cofounder Katarzyna Szymielewicz has questioned this rationale.

Even other countries that are part of the Anglo-American legal tradition are ramping up their use of data and working with the private sector to do so. The UK’s National Health Service is developing a data store that will include online/call center data from NHS Digital and Covid-19 test result data from the public health agency. While the NHS is working with private partner organizations and companies including Microsoft, Palantir Technologies, Amazon Web Services and Google, it has promised to keep all the data under its control, and to require those partners to destroy or return the data “once the public health emergency situation has ended.” The NHS also has committed to meet the requirements of data protection legislation by ensuring that individuals cannot be re-identified from the data in the data store.

Notably, each of the companies partnering with the NHS at one time or another has been subjected to scrutiny for its privacy practices. Some observers have noted that tech companies, which have been roundly criticized for a variety of reasons in recent years, may seek to use this pandemic for “reputation laundering.” As one observer cautioned: “Reputations matter, and there’s no reason the government or citizens should cast bad reputations aside when choosing who to work with or what to share” during this public health crisis.

At home

In the U.S., the federal government last enforced large-scale isolation and quarantine measures during the influenza (“Spanish Flu”) pandemic a century ago. But the Centers for Disease Control and Prevention track diseases on a daily basis by receiving case notifications from every state. The states mandate that healthcare providers and laboratories report certain diseases to the local public health authorities using personal identifiers. In other words, if you test positive for coronavirus, the government will know. Every state has laws authorizing quarantine and isolation, usually through the state’s health authority, while the CDC has authority through the federal Public Health Service Act and a series of presidential executive orders to exercise quarantine and isolation powers for specific diseases, including severe acute respiratory syndromes (a category into which the novel coronavirus falls).

Now local governments are issuing orders that empower law enforcement to fine and jail Americans for failing to practice social distancing. State and local governments have begun arresting and charging people who violate orders against congregating in groups. Rhode Island is requiring every non-resident who enters the state to be quarantined for two weeks, with police checks at the state’s transportation hubs and borders.

How governments discover violations of quarantine and social distancing orders will raise privacy concerns. Police have long been able to enforce based on direct observation of violations. But if law enforcement authorities identify violations of such orders based on data collection rather than direct observation, the Fourth Amendment may be implicated. In Jones and Carpenter, the Supreme Court has limited the warrantless tracking of Americans through GPS devices placed on their cars and through cellphone data. But building on the longstanding practice of contact tracing in fighting infectious diseases such as tuberculosis, GPS data has proven helpful in fighting the spread of Covid-19. This same data, though, also could be used to piece together evidence of violations of stay-at-home orders. As Chief Justice John Roberts wrote in Carpenter, “With access to [cell-site location information], the government can now travel back in time to retrace a person’s whereabouts… Whoever the suspect turns out to be, he has effectively been tailed every moment of every day for five years.”

The Fourth Amendment protects American citizens from government action, but the “reasonable expectation of privacy” test applied in Fourth Amendment cases connects the arenas of government action and commercial data collection. As Professor Paul Ohm of the Georgetown University Law Center notes, “the dramatic expansion of technologically-fueled corporate surveillance of our private lives automatically expands police surveillance too, thanks to the way the Supreme Court has construed the reasonable expectation of privacy test and the third-party doctrine.”

For example, the COVID-19 Mobility Data Network – infectious disease epidemiologists working with Facebook, Camber Systems and Cubiq – uses mobile device data to inform state and local governments about whether social distancing orders are effective. The tech companies give the researchers aggregated data sets; the researchers give daily situation reports to departments of health, but say they do not share the underlying data sets with governments. The researchers have justified this model based on users of the private companies’ apps having consented to the collection and sharing of data.

However, the assumption that consumers have given informed consent to the collection of their data (particularly for the purpose of monitoring their compliance with social isolation measures during a pandemic) is undermined by studies showing the average consumer does not understand all the different types of data that are collected and how their information is analyzed and shared with third parties – including governments. Technology and telecommunications companies have neither asked me to opt into tracking for public health nor made clear how they are partnering with federal, state and local governments. This practice highlights that data will be divulged in ways consumers cannot imagine – because no one assumed a pandemic when agreeing to a company’s privacy policy. This information asymmetry is part of why we need federal privacy legislation.

On Friday afternoon, Apple and Google announced their opt-in Covid-19 contact tracing technology. The owners of the two most common mobile phone operating systems in the U.S. said that in May they would release application programming interfaces that enable interoperability between iOS and Android devices using official contact tracing apps from public health authorities. At an unspecified date, Bluetooth-based contact tracing will be built directly into the operating systems. “Privacy, transparency, and consent are of utmost importance in this effort,” the companies said in their press release.

At this early stage, we do not yet know exactly how the proposed Google/Apple contact tracing system will operate. It sounds similar to Singapore’s TraceTogether, which is already available in the iOS and Android mobile app stores (it has a 3.3 out of 5 average rating in the former and a 4.0 out of 5 in the latter). TraceTogether is also described as a voluntary, Bluetooth-based system that avoids GPS location data, does not upload information without the user’s consent, and uses changing, encrypted identifiers to maintain user anonymity. Perhaps the most striking difference, at least to a non-technical observer, is that TraceTogether was developed and is run by the Singaporean government, which has been a point of concern for some observers. The U.S. version – like finding abducted children through Amber Alerts and fighting crime via Amazon Ring – will be a partnership between the public and private sectors.

Recommendations

The global pandemic we now face is driving data usage in ways not contemplated by consumers. Entities in the private and public sector are confronting new and complex choices about data collection, usage and sharing. Organizations with Chief Privacy Officers, Chief Information Security Officers, and other personnel tasked with managing privacy programs are, relatively speaking, well-equipped to address these issues. Despite the extraordinary circumstances, senior management should continue to rely on the expertise and sound counsel of their CPOs and CISOs, who should continue to make decisions based on their established privacy and data security programs. Although developments are unfolding at warp speed, it is important – arguably now, more than ever – to be intentional about privacy decisions.

For organizations that lack experience with privacy and data security programs (and individuals tasked with oversight for these areas), now is a great time to pause, do some research and exercise care. It is essential to think about the longer-term ramifications of choices made about data collection, use and sharing during the pandemic. The FTC offers easily accessible resources, including Protecting Personal Information: A Guide for Business, Start with Security: A Guide for Business, and Stick with Security: A Business Blog Series. While the Gramm-Leach-Bliley Act (GLB) applies only to financial institutions, the FTC’s GLB compliance blog outlines some data security best practices that apply more broadly. The National Institute for Standards and Technology (NIST) also offers security and privacy resources, including a privacy framework to help organizations identify and manage privacy risks. Private organizations such as the Center for Information Policy Leadership, the International Association of Privacy Professionals and the App Association also offer helpful resources, as do trade associations. While it may seem like a suboptimal time to take a step back and focus on these strategic issues, remember that privacy and data security missteps can cause irrevocable harm. Counterintuitively, now is actually the best time to be intentional about choices in these areas.

Best practices like accountability, risk assessment and risk management will be key to navigating today’s challenges. Companies should take the time to assess and document the new and/or expanded risks from the data collection, use and sharing of personal information. It is appropriate for these risk assessments to incorporate potential benefits and harms not only to the individual and the company, but for society as a whole. Upfront assessments can help companies establish controls and incentives to facilitate responsible behavior, as well as help organizations demonstrate that they are fully aware of the impact of their choices (risk assessment) and in control of their impact on people and programs (risk mitigation). Written assessments can also facilitate transparency with stakeholders, raise awareness internally about policy choices and assist companies with ongoing monitoring and enforcement. Moreover, these assessments will facilitate a return to “normal” data practices when the crisis has passed.

In a similar vein, companies must engage in comprehensive vendor management with respect to the entities that are proposing to use and analyze their data. In addition to vetting proposed data recipients thoroughly, companies must be selective concerning the categories of information shared. The benefits of the proposed research must be balanced against individual protections, and companies should share only those data necessary to achieve the stated goals. To the extent feasible, data should be shared in de-identified and aggregated formats and data recipients should be subject to contractual obligations prohibiting them from re-identification. Moreover, companies must have policies in place to ensure compliance with research contracts, including data deletion obligations and prohibitions on data re-identification, where appropriate. Finally, companies must implement mechanisms to monitor third party compliance with contractual obligations.

Similar principles of necessity and proportionality should guide governments as they make demands or requests for information from the private sector. Governments must recognize the weight with which they speak during this crisis and carefully balance data collection and usage with civil liberties. In addition, governments also have special obligations to ensure that any data collection done by them or at their behest is driven by the science of Covid-19; to be transparent with citizens about the use of data; and to provide due process for those who wish to challenge limitations on their rights. Finally, government actors should apply good data hygiene, including regularly reassessing the breadth of their data collection initiatives and incorporating data retention and deletion policies.

In theory, government’s role could be reduced as market-driven responses emerge. For example, assuming the existence of universally accessible daily coronavirus testing with accurate results even during the incubation period, Hal Singer’s proposal for self-certification of non-infection among private actors is intriguing. Thom Lambert identified the inability to know who is infected as a “lemon problem;” Singer seeks a way for strangers to verify each other’s “quality” in the form of non-infection.

Whatever solutions we may accept in a pandemic, it is imperative to monitor the coronavirus situation as it improves, to know when to lift the more dire measures. Former Food and Drug Administration Commissioner Scott Gottlieb and other observers have called for maintaining surveillance because of concerns about a resurgence of the virus later this year. For any measures that conflict with Americans’ constitutional rights to privacy and freedom of movement, there should be metrics set in advance for the conditions that will indicate when such measures are no longer justified. In the absence of pre-determined metrics, governments may feel the same temptation as Hungary’s prime minister to keep renewing a “state of danger” that overrides citizens’ rights. As Slovak lawmaker Tomas Valasek has said, “It doesn’t just take the despots and the illiberals of this world, like Orbán, to wreak damage.” But privacy is not merely instrumental to other interests, and we do not have to sacrifice our right to it indefinitely in exchange for safety.

I recognize that halting the spread of the virus will require extensive and sustained effort, and I credit many governments with good intentions in attempting to save the lives of their citizens. But I refuse to accept that we must sacrifice privacy to reopen the economy. It seems a false choice to say that I must sacrifice my Constitutional rights to privacy, freedom of association and free exercise of religion for another’s freedom of movement. Society should demand that equity, fairness and autonomy be respected in data uses, even in a pandemic. To quote Valasek again: “We need to make sure that we don’t go a single inch further than absolutely necessary in curtailing civil liberties in the name of fighting for public health.” History has taught us repeatedly that sweeping security powers granted to governments during an emergency persist long after the crisis has abated. To resist the gathering momentum toward this outcome, I will continue to emphasize the FTC’s learning on appropriate data collection and use. But my remit as an FTC Commissioner is even broader – when I was sworn in on Sept. 26, 2018, I took an oath to “support and defend the Constitution of the United States” – and so I shall.

^[1] Many thanks to my Attorney Advisors Pallavi Guniganti and Nina Frant for their invaluable assistance in preparing this article.

The DOJ’s Approval of the CVS/Aetna Merger and Vertical Innovation by Incumbents

Geoffrey Manne — 19 October 2018

Last week, the DOJ cleared the merger of CVS Health and Aetna (conditional on Aetna’s divesting its Medicare Part D business), a merger that, as I previously noted at a House Judiciary hearing, “presents a creative effort by two of the most well-informed and successful industry participants to try something new to reform a troubled system.” (My full testimony is available here).

Of course it’s always possible that the experiment will fail — that the merger won’t “revolutioniz[e] the consumer health care experience” in the way that CVS and Aetna are hoping. But it’s a low (antitrust) risk effort to address some of the challenges confronting the healthcare industry — and apparently the DOJ agrees.

I discuss the weakness of the antitrust arguments against the merger at length in my testimony. What I particularly want to draw attention to here is how this merger — like many vertical mergers — represents business model innovation by incumbents.

The CVS/Aetna merger is just one part of a growing private-sector movement in the healthcare industry to adopt new (mostly) vertical arrangements that seek to move beyond some of the structural inefficiencies that have plagued healthcare in the United States since World War II. Indeed, ambitious and interesting as it is, the merger arises amidst a veritable wave of innovative, vertical healthcare mergers and other efforts to integrate the healthcare services supply chain in novel ways.

These sorts of efforts (and the current DOJ’s apparent support for them) should be applauded and encouraged. I need not rehash the economic literature on vertical restraints here (see, e.g., Lafontaine & Slade, etc.). But especially where government interventions have already impaired the efficient workings of a market (as they surely have, in spades, in healthcare), it is important not to compound the error by trying to micromanage private efforts to restructure around those constraints.

Current trends in private-sector-driven healthcare reform

In the past, the most significant healthcare industry mergers have largely been horizontal (i.e., between two insurance providers, or two hospitals) or “traditional” business model mergers for the industry (i.e., vertical mergers aimed at building out managed care organizations). This pattern suggests a sort of fealty to the status quo, with insurers interested primarily in expanding their insurance business or providers interested in expanding their capacity to provide medical services.

Today’s health industry mergers and ventures seem more frequently to be different in character, and they portend an industry-wide experiment in the provision of vertically integrated healthcare that we should enthusiastically welcome.

Drug pricing and distribution innovations

To begin with, the CVS/Aetna deal, along with the also recently approved Cigna-Express Scripts deal, solidifies the vertical integration of pharmacy benefit managers (PBMs) with insurers.

But a number of other recent arrangements and business models center around relationships among drug manufacturers, pharmacies, and PBMs, and these tend to minimize the role of insurers. While not a “vertical” arrangement, per se, Walmart’s generic drug program, for example, offers $4 prescriptions to customers regardless of insurance (the typical generic drug copay for patients covered by employer-provided health insurance is $11), and Walmart does not seek or receive reimbursement from health plans for these drugs. It’s been offering this program since 2006, but in 2016 it entered into a joint buying arrangement with McKesson, a pharmaceutical wholesaler (itself vertically integrated with Rexall pharmacies), to negotiate lower prices. The idea, presumably, is that Walmart will entice consumers to its stores with the lure of low-priced generic prescriptions in the hope that they will buy other items while they’re there. That prospect presumably makes it worthwhile to route around insurers and PBMs, and their reimbursements.

Meanwhile, both Express Scripts and CVS Health (two of the country’s largest PBMs) have made moves toward direct-to-consumer sales themselves, establishing pricing for a small number of drugs independently of health plans and often in partnership with drug makers directly.

Also apparently focused on disrupting traditional drug distribution arrangements, Amazon has recently purchased online pharmacy PillPack (out from under Walmart, as it happens), and with it received pharmacy licenses in 49 states. The move introduces a significant new integrated distributor/retailer, and puts competitive pressure on other retailers and distributors and potentially insurers and PBMs, as well.

Whatever its role in driving the CVS/Aetna merger (and I believe it is smaller than many reports like to suggest), Amazon’s moves in this area demonstrate the fluid nature of the market, and the opportunities for a wide range of firms to create efficiencies in the market and to lower prices.

At the same time, the differences between Amazon and CVS/Aetna highlight the scope of product and service differentiation that should contribute to the ongoing competitiveness of these markets following mergers like this one.

While Amazon inarguably excels at logistics and the routinizing of “back office” functions, it seems unlikely for the foreseeable future to be able to offer (or to be interested in offering) a patient interface that can rival the service offerings of a brick-and-mortar CVS pharmacy combined with an outpatient clinic and its staff and bolstered by the capabilities of an insurer like Aetna. To be sure, online sales and fulfillment may put price pressure on important, largely mechanical functions, but, like much technology, it is first and foremost a complement to services offered by humans, rather than a substitute. (In this regard it is worth noting that McKesson has long been offering Amazon-like logistics support for both online and brick-and-mortar pharmacies. “‘To some extent, we were Amazon before it was cool to be Amazon,’ McKesson CEO John Hammergren said” on a recent earnings call).

Treatment innovations

Other efforts focus on integrating insurance and treatment functions or on bringing together other, disparate pieces of the healthcare industry in interesting ways — all seemingly aimed at finding innovative, private solutions to solve some of the costly complexities that plague the healthcare market.

Walmart, for example, announced a deal with Quest Diagnostics last year to experiment with offering diagnostic testing services and potentially other basic healthcare services inside of some Walmart stores. While such an arrangement may simply be a means of making doctor-prescribed diagnostic tests more convenient, it may also suggest an effort to expand the availability of direct-to-consumer (patient-initiated) testing (currently offered by Quest in Missouri and Colorado) in states that allow it. A partnership with Walmart to market and oversee such services has the potential to dramatically expand their use.

Capping off (for now) a buying frenzy in recent years that included the purchase of PBM, CatamaranRx, UnitedHealth is seeking approval from the FTC for the proposed merger of its Optum unit with the DaVita Medical Group — a move that would significantly expand UnitedHealth’s ability to offer medical services (including urgent care, outpatient surgeries, and health clinic services), give it a significant group of doctors’ clinics throughout the U.S., and turn UnitedHealth into the largest employer of doctors in the country. But of course this isn’t a traditional managed care merger — it represents a significant bet on the decentralized, ambulatory care model that has been slowly replacing significant parts of the traditional, hospital-centric care model for some time now.

And, perhaps most interestingly, some recent moves are bringing together drug manufacturers and diagnostic and care providers in innovative ways. Swiss pharmaceutical company, Roche, announced recently that “it would buy the rest of U.S. cancer data company Flatiron Health for $1.9 billion to speed development of cancer medicines and support its efforts to price them based on how well they work.” Not only is the deal intended to improve Roche’s drug development process by integrating patient data, it is also aimed at accommodating efforts to shift the pricing of drugs, like the pricing of medical services generally, toward an outcome-based model.

Similarly interesting, and in a related vein, early this year a group of hospital systems including Intermountain Health, Ascension, and Trinity Health announced plans to begin manufacturing generic prescription drugs. This development further reflects the perceived benefits of vertical integration in healthcare markets, and the move toward creative solutions to the unique complexity of coordinating the many interrelated layers of healthcare provision. In this case,

[t]he nascent venture proposes a private solution to ensure contestability in the generic drug market and consequently overcome the failures of contracting [in the supply and distribution of generics]…. The nascent venture, however it solves these challenges and resolves other choices, will have important implications for the prices and availability of generic drugs in the US.

More enforcement decisions like CVS/Aetna and Bayer/Monsanto; fewer like AT&T/Time Warner

In the face of all this disruption, it’s difficult to credit anticompetitive fears like those expressed by the AMA in opposing the CVS-Aetna merger and a recent CEA report on pharmaceutical pricing, both of which are premised on the assumption that drug distribution is unavoidably dominated by a few PBMs in a well-defined, highly concentrated market. Creative arrangements like the CVS-Aetna merger and the initiatives described above (among a host of others) indicate an ease of entry, the fluidity of traditional markets, and a degree of business model innovation that suggest a great deal more competitiveness than static PBM market numbers would suggest.

This kind of incumbent innovation through vertical restructuring is an increasingly important theme in antitrust, and efforts to tar such transactions with purported evidence of static market dominance is simply misguided.

While the current DOJ’s misguided (and, remarkably, continuing) attempt to stop the AT&T/Time Warner merger is an aberrant step in the wrong direction, the leadership at the Antitrust Division generally seems to get it. Indeed, in spite of strident calls for stepped-up enforcement in the always-controversial ag-biotech industry, the DOJ recently approved three vertical ag-biotech mergers in fairly rapid succession.

As I noted in a discussion of those ag-biotech mergers, but equally applicable here, regulatory humility should continue to carry the day when it comes to structural innovation by incumbent firms:

But it is also important to remember that innovation comes from within incumbent firms, as well, and, often, that the overall level of innovation in an industry may be increased by the presence of large firms with economies of scope and scale.

In sum, and to paraphrase Olympia Dukakis’ character in Moonstruck: “what [we] don’t know about [the relationship between innovation and market structure] is a lot.”

What we do know, however, is that superficial, concentration-based approaches to antitrust analysis will likely overweight presumed foreclosure effects and underweight innovation effects.

We shouldn’t fetishize entry, or access, or head-to-head competition over innovation, especially where consumer welfare may be significantly improved by a reduction in the former in order to get more of the latter.

E-cigarette taxation: Lessons from “sin taxes”

Eric Fruits — 3 August 2018

The Economist takes on “sin taxes” in a recent article, “‘Sin’ taxes—eg, on tobacco—are less efficient than they look.” The article has several lessons for policy makers eyeing taxes on e-cigarettes and other vapor products.

Historically, taxes had the key purpose of raising revenues. The “best” taxes would be on goods with few substitutes (i.e., inelastic demand) and on goods deemed to be luxuries. In Wealth of Nations Adam Smith notes:

Sugar, rum, and tobacco are commodities which are nowhere necessaries of life, which are become objects of almost universal consumption, and which are therefore extremely proper subjects of taxation.

The Economist notes in 1764, a fiscal crisis driven by wars in North America led Britain’s parliament began enforcing tariffs on sugar and molasses imported from outside the empire. In the U.S., from 1868 until 1913, 90 percent of all federal revenue came from taxes on liquor, beer, wine and tobacco.

Over time, the rationale for these taxes has shifted toward “sin taxes” designed to nudge consumers away from harmful or distasteful consumption. The Temperance movement in the U.S. argued for higher taxes to discourage alcohol consumption. Since the Surgeon General’s warning on the dangers of smoking, tobacco tax increases have been justified as a way to get smokers to quit. More recently, a perceived obesity epidemic has led several American cities as well as Thailand, Britain, Ireland, South Africa to impose taxes on sugar-sweetened beverages to reduce sugar consumption.

Because demand curves slope down, “sin taxes” do change behavior by reducing the quantity demanded. However, for many products subject to such taxes, demand is not especially responsive. For example, as shown in the figure below, a one percent increase in the price of tobacco is associated with a one-half of one percent decrease in sales.

Substitutability is another consideration for tax policy. An increase in the tax on spirits will result in an increase in beer and wine purchases. A high toll on a road will divert traffic to untolled streets that may not be designed for increased traffic volumes. A spike in tobacco taxes in one state will result in a spike in sales in bordering states as well as increase illegal interstate sales or smuggling. The Economist reports:

After Berkeley introduced its tax, sales of sugary drinks rose by 6.9% in neighbouring cities. Denmark, which instituted a tax on fat-laden foods in 2011, ran into similar problems. The government got rid of the tax a year later when it discovered that many shoppers were buying butter in neighbouring Germany and Sweden.

Advocates of “sin” taxes on tobacco, alcohol, and sugar argue their use impose negative externalities on the public, since governments have to spend more to take care of sick people. With approximately one-third of the U.S. population covered by some form of government funded health insurance, such as Medicare or Medicaid, what were once private costs of healthcare have been transformed into a public cost.

According to Centers for Disease Control and Prevention in U.S., smoking-related illness in the U.S. costs more than $300 billion each year, including; (1) nearly $170 billion for direct medical care for adults and (2) more than $156 billion in lost productivity, including $5.6 billion in lost productivity due to secondhand smoke exposure.

On the other hand, The Economist points out:

Smoking, in contrast, probably saves taxpayers money. Lifelong smoking will bring forward a person’s death by about ten years, which means that smokers tend to die just as they would start drawing from state pensions. In a study published in 2002 Kip Viscusi, an economist at Vanderbilt University who has served as an expert witness on behalf of tobacco companies, estimated that even if tobacco were untaxed, Americans could still expect to save the government an average of 32 cents for every pack of cigarettes they smoke.

The CDC’s cost estimates raise important questions regarding who bears the burden of smoking related illness. For example, much of the direct cost is borne by private insurance, which charge steeper premiums for customers who smoke. In addition, the CDC estimates reflect costs imposed by people who have smoked for decades—many of whom have now quit. A proper accounting of the costs vis-à-vis tax policy should evaluate the discounted costs imposed by today’s smokers.

State and local governments in the U.S. collect more than $18 billion a year in tobacco taxes. While some jurisdictions earmark a portion of tobacco taxes for prevention and cessation efforts, in practice most tobacco taxes are treated by policymakers as general revenues to be spent in whatever way the legislative body determines. Thus, in practice, there is no clear nexus between taxes levied on tobacco and government’s use of the tax revenues on smoking related costs.

Most of the harm from smoking is caused by the inhalation of toxicants released through the combustion of tobacco. Public Health England and the American Cancer Society have concluded non-combustible tobacco products, such as e-cigarettes, “heat-not-burn” products, smokeless tobacco, are considerably less harmful than combustible products.

Many experts believe that the best option for smokers who are unable or unwilling to quit smoking is to switch to a less harmful alternative activity that has similar attributes, such as using non-combustible nicotine delivery products. Policies that encourage smokers to switch from more harmful combustible tobacco products to less harmful non-combustible products would be considered a form of “harm reduction.”

Nine U.S. states now have taxes on vapor products. In addition, several local jurisdictions have enacted taxes. Their methods and levels of taxation vary widely. Policy makers considering a tax on vapor products should account for the following factors.

The current market for e-cigarettes as well as heat-not-burn products in the range of 0-10 percent of the cigarette market. Given the relatively small size of the e-cigarette and heated tobacco product market, it is unlikely any level of taxation of e-cigarettes and heated tobacco products would generate significant tax revenues to the taxing jurisdiction. Moreover much of the current research likely represents early adopters and higher income consumer groups. As such, the current empirical data based on total market size and price/tax levels are likely to be far from indicative of the “actual” market for these products.
The demand for e-cigarettes is much more responsive to a change in price than the demand for combustible cigarettes. My review of the published research to date finds the median estimated own-price elasticity is -1.096, meaning something close to a 1-to-1 relationship: a tax resulting in a one percent increase in e-cigarette prices would be associated with one percent decline in e-cigarette sales. Many of those lost sales would be shifted to purchases of combustible cigarettes.
Research on the price responsiveness of vapor products is relatively new and sparse. There are fewer than a dozen published articles, and the first article was published in 2014. As a result, the literature reports a wide range of estimated elasticities that calls into question the reliability of published estimates, as shown in the figure below. As a relatively unformed area of research, the policy debate would benefit from additional research that involves larger samples with better statistical power, reflects the dynamic nature of this new product category, and accounts for the wide variety of vapor products.

With respect to taxation and pricing, policymakers would benefit from reliable information regarding the size of the vapor product market and the degree to which vapor products are substitutes for combustible tobacco products. It may turn out that a tax on vapor products may be, as The Economist notes, less efficient than they look.

In Health Care, Health Insurance, International, Regulation, Taxes, Truth on the Market alcohol, behavioral economics, e-cigarettes, harm reduction, Ireland, non-combustible tobacco products

An Apollo 13 approach to Obamacare

Eric Fruits — 7 July 2017

“Houston, we have a problem.” It’s the most famous line from Apollo 13 and perhaps how most Republicans are feeling about their plans to repeal and replace Obamacare.

As repeal and replace has given way to tinker and punt, Congress should take a lesson from one of my favorite scenes from Apollo 13.

“We gotta find a way to make this, fit into the hole for this, using nothing but that.”

Let’s look at a way Congress can get rid of the individual mandate, lower prices, cover pre-existing conditions, and provide universal coverage, using the box of tools that we already have on the table.

Some ground rules

First ground rule: (Near) universal access to health insurance. It’s pretty clear that many, if not most Americans, believe that everyone should have health insurance. Some go so far as to call it a “basic human right.” This may be one of the biggest shifts in U.S. public opinion over time.

Second ground rule: Everything has a price, there’s no free lunch. If you want to add another essential benefit, premiums will go up. If you want community rating, young healthy people are going to subsidize older sicker people. If you want a lower deductible, you’ll pay a higher premium, as shown in the figure below all the plans available on Oregon’s ACA exchange in 2017. It shows that a $1,000 decrease in deductible is associated with almost $500 a year in additional premium payments. There’s no free lunch.

Third ground rule: No new programs, no radical departures. Maybe Singapore has a better health insurance system. Maybe Canada’s is better. Switching to either system would be a radical departure from the tools we have to work with. This is America. This is Apollo 13. We gotta find a way to make this, fit into the hole for this, using nothing but that.

Private insurance

Employer and individual mandates: Gone. This would be a substantial change from the ACA, but is written into the Senate health insurance bill. The individual mandate is perhaps the most hated part of the ACA, but it was also the most important part Obamacare. Without the coverage mandate, much of the ACA falls apart, as we are seeing now.

Community rating, mandated benefits (aka “minimum essential benefit”), and pre-existing conditions. Sen. Ted Cruz has a brilliantly simple idea: As long as a health plan offers at least one ACA-compliant plan in a state, the plan would also be allowed to offer non-Obamacare-compliant plans in that state. In other words, every state would have at least one plan that checks all the Obamacare boxes of community rating, minimum essential benefits, and pre-existing conditions. If you like Obamacare, you can keep Obamacare. In addition, there could be hundreds of other plans for which consumers can pick each person’s unique situation of age, health status, and ability/willingness to pay. A single healthy 27-year-old would likely choose a plan that’s very different from a plan chosen by a family of four with 40-something parents and school aged children.

Allow—but don’t require—insurance to be bought and sold across state lines. I don’t know if this a big deal or not. Some folks on the right think this could be a panacea. Some folks on the left think this is terrible and would never work. Let’s find out. Some say insurance companies don’t want to sell policies across state lines. Some will, some won’t. Let’s find out, but it shouldn’t be illegal. No one is worse off by loosening a constraint.

Tax deduction for insurance premiums. Keep insurance premiums as a deductible expense for business: No change from current law. In addition, make insurance premiums deductible on individual taxes. This is a not-so-radical change from current law that allows deductions for medical expenses. If someone has employer-provided insurance, the business would be able deduct the share the company pays and the worker would be able to deduct the employee share of the premium from his or her personal taxes. Sure the deduction will reduce tax revenues, but the increase in private insurance coverage would reduce the costs of Medicaid and charity care.

These straightforward changes would preserve one or more ACA-compliant plan for those who want to pay Obamacare’s “silver prices,” allow for consumer choice across other plans, and result in premiums that more closely aligned with benefits chosen by consumers. Allowing individuals to deduct health insurance premiums is also a crucial step in fostering insurance portability.

Medicaid

Even with the changes in the private market, some consumers will find that they can’t afford or don’t want to pay the market price for private insurance. These people would automatically get moved into Medicaid. Those in poverty (or some X% of the poverty rate) would pay nothing and everyone else would be charged a “premium” based on ability to pay. A single mother in poverty would pay nothing for Medicaid coverage, but Elon Musk (if he chose this option) would pay the full price. A middle class family would pay something in between free and full-price. Yes, this is a pretty wide divergence from the original intent of Medicaid, but it’s a relatively modest change from the ACA’s expansion.

While the individual mandate goes away, anyone who does not buy insurance in the private market or is not covered by Medicare will be “mandated” to have Medicaid coverage. At the same time, it preserves consumer choice. That is, consumers have a choice of buying an ACA compliant plan, one of the hundreds of other private plans offered throughout the states, or enrolling in Medicaid.

Would the Medicaid rolls explode? Who knows?

The Census Bureau reports that 15 percent of adults and 40 percent of children currently are enrolled in Medicaid. Research published in the New England Journal of Medicine finds that 44 percent of people who were enrolled in the Medicaid under Obamacare qualified for Medicaid before the ACA.

With low cost private insurance alternatives to Medicaid, some consumers would likely choose the private plans over Medicaid coverage. Also, if Medicaid premiums increased with incomes, able-bodied and working adults would likely shift out of Medicaid to private coverage as the government plan loses its cost-competitiveness.

The cost sharing of income-based premiums means that Medicaid would become partially self supporting.

Opponents of Medicaid expansion claim that the program provides inferior service: fewer providers, lower quality, worse outcomes. If that’s true, then that’s a feature, not a bug. If consumers have to pay for their government insurance and that coverage is inferior, then consumers have an incentive to exit the Medicaid market and enter the private market. Medicaid becomes the insurer of last resort that it was intended to be.

A win-win

The coverage problem is solved. Every American would have health insurance.

Consumer choice is expanded. By allowing non-ACA-compliant plans, consumers can choose the insurance that fits their unique situation.

The individual mandate penalty is gone. Those who choose not to buy insurance would get placed into Medicaid. Higher income individuals would pay a portion of the Medicaid costs, but this isn’t a penalty for having no insurance, it’s the price of having insurance.

The pre-existing conditions problem is solved. Americans with pre-existing conditions would have a choice of at least two insurance options: At least one ACA-compliant plan in the private market and Medicaid.

This isn’t a perfect solution, it may not even be a good solution, but it’s a solution that’s better than what we’ve got and better than what Congress has come up with so far. And, it works with the box of tools that’s already been dumped on the table.

In Health Care, Health Insurance, Taxes Affordable Care Act, health care reform debate, Labor Law, New England Journal of Medicine

When Past Is Not Prologue: The Weakness of the Economic Evidence Against Health Insurance Mergers

Geoffrey Manne — 6 December 2016

I just posted a new ICLE white paper, co-authored with former ICLE Associate Director, Ben Sperry:

When Past Is Not Prologue: The Weakness of the Economic Evidence Against Health Insurance Mergers.

Yesterday the hearing in the DOJ’s challenge to stop the Aetna-Humana merger got underway, and last week phase 1 of the Cigna-Anthem merger trial came to a close.

The DOJ’s challenge in both cases is fundamentally rooted in a timeworn structural analysis: More consolidation in the market (where “the market” is a hotly-contested issue, of course) means less competition and higher premiums for consumers.

Following the traditional structural playbook, the DOJ argues that the Aetna-Humana merger (to pick one) would result in presumptively anticompetitive levels of concentration, and that neither new entry not divestiture would suffice to introduce sufficient competition. It does not (in its pretrial brief, at least) consider other market dynamics (including especially the complex and evolving regulatory environment) that would constrain the firm’s ability to charge supracompetitive prices.

Aetna & Humana, for their part, contend that things are a bit more complicated than the government suggests, that the government defines the relevant market incorrectly, and that

the evidence will show that there is no correlation between the number of [Medicare Advantage organizations] in a county (or their shares) and Medicare Advantage pricing—a fundamental fact that the Government’s theories of harm cannot overcome.

The trial will, of course, feature expert economic evidence from both sides. But until we see that evidence, or read the inevitable papers derived from it, we are stuck evaluating the basic outlines of the economic arguments based on the existing literature.

A host of antitrust commentators, politicians, and other interested parties have determined that the literature condemns the mergers, based largely on a small set of papers purporting to demonstrate that an increase of premiums, without corresponding benefit, inexorably follows health insurance “consolidation.” In fact, virtually all of these critics base their claims on a 2012 case study of a 1999 merger (between Aetna and Prudential) by economists Leemore Dafny, Mark Duggan, and Subramaniam Ramanarayanan, Paying a Premium on Your Premium? Consolidation in the U.S. Health Insurance Industry, as well as associated testimony by Prof. Dafny, along with a small number of other papers by her (and a couple others).

Our paper challenges these claims. As we summarize:

This white paper counsels extreme caution in the use of past statistical studies of the purported effects of health insurance company mergers to infer that today’s proposed mergers—between Aetna/Humana and Anthem/Cigna—will likely have similar effects. Focusing on one influential study—Paying a Premium on Your Premium…—as a jumping off point, we highlight some of the many reasons that past is not prologue.

In short: extrapolated, long-term, cumulative, average effects drawn from 17-year-old data may grab headlines, but they really don’t tell us much of anything about the likely effects of a particular merger today, or about the effects of increased concentration in any particular product or geographic market.

While our analysis doesn’t necessarily undermine the paper’s limited, historical conclusions, it does counsel extreme caution for inferring the study’s applicability to today’s proposed mergers.

By way of reference, Dafny, et al. found average premium price increases from the 1999 Aetna/Prudential merger of only 0.25 percent per year for two years following the merger in the geographic markets they studied. “Health Insurance Mergers May Lead to 0.25 Percent Price Increases!” isn’t quite as compelling a claim as what critics have been saying, but it’s arguably more accurate (and more relevant) than the 7 percent price increase purportedly based on the paper that merger critics like to throw around.

Moreover, different markets and a changed regulatory environment alone aren’t the only things suggesting that past is not prologue. When we delve into the paper more closely we find even more significant limitations on the paper’s support for the claims made in its name, and its relevance to the current proposed mergers.

The full paper is available here.

Critics of health insurance mergers misapply the evidence and misinterpret the market

Geoffrey Manne — 30 June 2016

As regulatory review of the merger between Aetna and Humana hits the homestretch, merger critics have become increasingly vocal in their opposition to the deal. This is particularly true of a subset of healthcare providers concerned about losing bargaining power over insurers.

Fortunately for consumers, the merger appears to be well on its way to approval. California recently became the 16th of 20 state insurance commissions that will eventually review the merger to approve it. The U.S. Department of Justice is currently reviewing the merger and may issue its determination as early as July.

Only Missouri has issued a preliminary opinion that the merger might lead to competitive harm. But Missouri is almost certain to remain an outlier, and its analysis simply doesn’t hold up to scrutiny.

The Missouri opinion echoed the Missouri Hospital Association’s (MHA) concerns about the effect of the merger on Medicare Advantage (MA) plans. It’s important to remember, however, that hospital associations like the MHA are not consumer advocacy groups. They are trade organizations whose primary function is to protect the interests of their member hospitals.

In fact, the American Hospital Association (AHA) has mounted continuous opposition to the deal. This is itself a good indication that the merger will benefit consumers, in part by reducing hospital reimbursement costs under MA plans.

More generally, critics have argued that history proves that health insurance mergers lead to higher premiums, without any countervailing benefits. Merger opponents place great stock in a study by economist Leemore Dafny and co-authors that purports to show that insurance mergers have historically led to seven percent higher premiums.

But that study, which looked at a pre-Affordable Care Act (ACA) deal and assessed its effects only on premiums for traditional employer-provided plans, has little relevance today.

The Dafny study first performed a straightforward statistical analysis of overall changes in concentration (that is, the number of insurers in a given market) and price, and concluded that “there is no significant association between concentration levels and premium growth.” Critics never mention this finding.

The study’s secondary, more speculative, analysis took the observed effects of a single merger — the 1999 merger between Prudential and Aetna — and extrapolated for all changes in concentration (i.e., the number of insurers in a given market) and price over an eight-year period. It concluded that, on average, seven percent of the cumulative increase in premium prices between 1998 and 2006 was the result of a reduction in the number of insurers.

But what critics fail to mention is that when the authors looked at the actual consequences of the 1999 Prudential/Aetna merger, they found effects lasting only two years — and an average price increase of only one half of one percent. And these negligible effects were restricted to premiums paid under plans purchased by large employers, a critical limitation of the studies’ relevance to today’s proposed mergers.

Moreover, as the study notes in passing, over the same eight-year period, average premium prices increased in total by 54 percent. Yet the study offers no insights into what was driving the vast bulk of premium price increases — or whether those factors are still present today.

Few sectors of the economy have changed more radically in the past few decades than healthcare has. While extrapolated effects drawn from 17-year-old data may grab headlines, they really don’t tell us much of anything about the likely effects of a particular merger today.

Indeed, the ACA and current trends in healthcare policy have dramatically altered the way health insurance markets work. Among other things, the advent of new technologies and the move to “value-based” care are redefining the relationship between insurers and healthcare providers. Nowhere is this more evident than in the Medicare and Medicare Advantage market at the heart of the Aetna/Humana merger.

In an effort to stop the merger on antitrust grounds, critics claim that Medicare and MA are distinct products, in distinct markets. But it is simply incorrect to claim that Medicare Advantage and traditional Medicare aren’t “genuine alternatives.”

In fact, as the Office of Insurance Regulation in Florida — a bellwether state for healthcare policy — concluded in approving the merger: “Medicare Advantage, the private market product, competes directly with Traditional Medicare.”

Consumers who search for plans at Medicare.gov are presented with a direct comparison between traditional Medicare and available MA plans. And the evidence suggests that they regularly switch between the two. Today, almost a third of eligible Medicare recipients choose MA plans, and the majority of current MA enrollees switched to MA from traditional Medicare.

True, Medicare and MA plans are not identical. But for antitrust purposes, substitutes need not be perfect to exert pricing discipline on each other. Take HMOs and PPOs, for example. No one disputes that they are substitutes, and that prices for one constrain prices for the other. But as anyone who has considered switching between an HMO and a PPO knows, price is not the only variable that influences consumers’ decisions.

The same is true for MA and traditional Medicare. For many consumers, Medicare’s standard benefits, more-expensive supplemental benefits, plus a wider range of provider options present a viable alternative to MA’s lower-cost expanded benefits and narrower, managed provider network.

The move away from a traditional fee-for-service model changes how insurers do business. It requires larger investments in technology, better tracking of preventive care and health outcomes, and more-holistic supervision of patient care by insurers. Arguably, all of this may be accomplished most efficiently by larger insurers with more resources and a greater ability to work with larger, more integrated providers.

This is exactly why many hospitals, which continue to profit from traditional, fee-for-service systems, are opposed to a merger that promises to expand these value-based plans. Significantly, healthcare providers like Encompass Medical Group, which have done the most to transition their services to the value-based care model, have offered letters of support for the merger.

Regardless of their rhetoric — whether about market definition or historic precedent — the most vocal merger critics are opposed to the deal for a very simple reason: They stand to lose money if the merger is approved. That may be a good reason for some hospitals to wish the merger would go away, but it is a terrible reason to actually stop it.

[This post was first published on June 27, 2016 in The Hill as “Don’t believe the critics, Aetna-Humana merger a good deal for consumers“]

More proposed market interventions to control drug costs

Joanna Shepherd — 2 May 2016

Last week, the Campaign for Sustainable Rx Pricing (CSRxP)—whose membership includes health insurance companies and other health payors, health providers, and consumers—proposed various reforms aimed at addressing the high costs of prescription drugs. CSRxP declares that their proposals will improve the functioning of the pharmaceutical market by increasing pricing transparency, promoting competition, and enhancing value. Although there are some good ideas in their list of proposals, others will negatively affect the pharmaceutical market, and ultimately, consumers.

The first set of proposals is aimed at increasing transparency in drug pricing. I’ve previously commented on the likely negative effects of transparency reforms: they impose extensive legal and regulatory costs on businesses and risk harming competition if competitively-sensitive information gets into the wrong hands. CSRxP proposes that manufacturers disclose the price they intend to charge for a drug as part of the FDA approval process and, after approval, report price changes to the Department of Health and Human Services (HHS). Requiring manufacturers to report expected pricing as a condition of FDA approval suggests that the FDA’s role in assessing the risks and efficacy of drugs will merge with a central planner’s job of determining how products should be priced in the market. Will a drug not be approved if the price is too high? Shouldn’t consumers and payors, not a government agency, determine the market demand for a drug? And what will HHS do with the price change information—just condemn the “blameworthy” manufacturers or institute some sort of price control with its ensuing harms?

The second set of proposals purports to promote competition in the market for drugs. Many of these proposals are good ideas, and will help bring more and cheaper drugs to the market. However, policy makers should tread carefully with other proposals, such as a call to prohibit product-hopping, because an overeager adoption or imprecise application of these reforms could curb pharmaceutical innovation and worsen patient health outcomes. Lawmakers must ensure that adopted reforms balance incentives to innovate with the fostering of competition and lower prices.

The third set of proposals target the so-called “value” of drugs. Here, CSRxP proposes that manufacturers perform comparison studies to demonstrate that their drug is superior to existing drugs. While, in theory, knowing the relative effectiveness of drugs sounds great, there are two critical problems with this approach. First, are we really going to require more testing by drug manufacturers? It is estimated that testing and development costs already reach an average of $2.6 billion for each new drug brought to market; this is one of the explanations for the already high price of drugs. Why would we want to add more expensive testing? Also, I’m skeptical that comparison studies can offer the necessary insight into what drug works best for an individual patient. Drugs that perform extremely well for a small group of people may appear to have only average effectiveness in aggregate studies. And we certainly don’t want the expense of separate comparison studies on countless small groups of patients.

CSRxP also proposes that the government adopt value-based purchasing (VBP) arrangements that link payment for medications to patient outcomes and cost-effectiveness rather than just the quantity of treatments. Although CSRxP doesn’t detail the specific form of VBP they prefer, some of the possibilities could produce harmful consequences. Namely, VBP arrangements that set a standard payment rate for a group of similar drug products, such as reference pricing, will effectively act like a price control because the only way certain drugs will be available is if drug companies agree to offer them at that set rate. Price controls—whether direct or indirect—are a bad idea for prescription drugs for several reasons. Evidence shows that price controls lead to higher initial launch prices for drugs, increased drug prices for consumers with private insurance coverage, drug shortages in certain markets, and reduced incentives for innovation.

In sum, while CSRxP has some good ideas in their list, many of the proposals would ultimately harm the very patients the proposals are designed to benefit. Policymakers should steer clear of any reform that could act as a direct or indirect price control, increase the already high costs of developing drugs, or reduce incentives for innovation.

In Antitrust & Competition, Health Care, Health Insurance, Pharmaceuticals, Truth on the Market FDA, market intervention, pharmaceuticals, price controls

Politicians Call for More Price Controls on Pharmaceuticals

Joanna Shepherd — 1 February 2016

Politicians have recently called for price controls to address the high costs of pharmaceuticals. Price controls are government-mandated limits on prices, or government-required discounts on prices. On the campaign trail, Hillary Clinton has called for price controls for lower-income Medicare patients while Donald Trump has recently joined Clinton, Bernie Sanders, and President Obama in calling for more government intervention in the Medicare Part D program. Before embarking upon additional price controls for the drug industry, policymakers and presidential candidates would do well to understand the impacts and problems arising from existing controls.

Unbeknownst to many, a vast array of price controls are already in place in the pharmaceutical market. Over 40 percent of outpatient drug spending is spent in public programs that use price controls. In order to sell drugs to consumers covered by these public programs, manufacturers must agree to offer certain rebates or discounts on drug prices. The calculations are generally based on the Average Manufacturer Price (AMP–the average price wholesalers pay manufacturers for drugs that are sold to retail pharmacies) or the Best Price (the lowest price the manufacturer offers the drug to any purchaser including all rebates and discounts). The most significant public programs using some form of price control are described below.

Medicaid

The Medicaid program provides health insurance for low-income and medically needy individuals. The legally-required rebate depends on the specific category of drug; for example, brand manufacturers are required to sell drugs for the lesser of 23.1% off AMP or the best price offered to any purchaser.

The Affordable Care Act significantly expanded Medicaid eligibility so that in 2014, the program covered approximately 64.9 million individuals, or 20 percent of the U.S. population. State Medicaid data indicates that manufacturers paid an enormous sum — in excess of $16.7 billion — in Medicaid rebates in 2012.

340B Program

The “340B Program”, created by Congress in 1992, requires drug manufacturers to provide outpatient drugs at significantly reduced prices to 340B-eligible entities—entities that serve a high proportion of low-income or uninsured patients. Like Medicaid, the 340B discount must be at least 23.1 percent off AMP. However, the statutory formula calculates different discounts for different products and is estimated to produce discounts that average 45 percent off average prices. Surprisingly, the formulas can even result in a negative 340B selling price for a drug, in which case manufacturers are instructed to set the drug price at a penny.

The Affordable Care Act broadened the definition of qualified buyers to include many additional types of hospitals. As a result, both the number of 340B-eligible hospitals and the money spent on 340B drugs tripled between 2005 and 2014. By 2014, there were over 14,000 hospitals and affiliated sites in the 340B program, representing about one-third of all U.S. hospitals.

The 340B program has a glaring flaw that punishes the pharmaceutical industry without any offsetting benefits for low-income patients. The 340B statute does NOT require that providers only dispense 340B drugs to needy patients. In what amounts to merely shifting profits from pharmaceutical companies to other health care providers, providers may also sell drugs purchased at the steep 340B discount to non-qualified patients and pocket the difference between the 340B discounted price and the reimbursement of the non-qualified patients’ private insurance companies. About half of the 340B entities generate significant revenues from private insurer reimbursements that exceed 340B prices.

Departments of Defense and Veterans Affairs Drug Programs

In order to sell drugs through the Medicaid program, drug manufacturers must also provide drugs to four government agencies—the VA, Department of Defense, Public Health Service and Coast Guard—at statutorily-imposed discounts. The required discounted price is the lesser of 24% off AMP or the lowest price manufacturers charge their most-favored nonfederal customers under comparable terms. Because of additional contracts that generate pricing concessions from specific vendors, studies indicate that VA and DOD pricing for brand pharmaceuticals was approximately 41-42% of the average wholesale price.

Medicare Part D

An optional Medicare prescription drug benefit (Medicare Part D) was enacted in 2005 to offer coverage to many of the nation’s retirees and disabled persons. Unlike Medicaid and the 340B program, there is no statutory rebate level on prescription drugs covered under the program. Instead, private Medicare Part D plans, acting on behalf of the Medicare program, negotiate prices with pharmaceutical manufacturers and may obtain price concessions in the form of rebates. Manufacturers are willing to offer significant rebates and discounts in order to provide drugs to the millions of covered participants. The rebates often amount to as much as a 20-30 percent discount on brand medicines. CMS reported that manufacturers paid in excess of $10.3 billion in Part D rebates in 2012.

The Medicare Part D program does include direct price controls on drugs sold in the coverage gap. The coverage gap (or “donut hole”) is a spending level in which enrollees are responsible for a larger share of their total drug costs. For 2016, the coverage gap begins when the individual and the plan have spent $3,310 on covered drugs and ends when $7,515 has been spent. Medicare Part D requires brand drug manufacturers to offer 50 percent discounts on drugs sold during the coverage gap. These required discounts will cost drug manufacturers approximately $41 billion between 2012-2021.

While existing price controls do produce lower prices for some consumers, they may also result in increased prices for others, and in the long-term may drive up prices for all. Many of the required rebates under Medicaid, the 340B program, and VA and DOD programs are based on drugs’ AMP. Calculating rebates from average drug prices gives manufactures an incentive to charge higher prices to wholesalers and pharmacies in order to offset discounts. Moreover, with at least 40% of drugs sold under price controls, and some programs even requiring drugs to be sold for a penny, manufacturers are forced to sell many drugs at significant discounts. This creates incentives to charge higher prices to other non-covered patients to offset the discounts. Further price controls will only amplify these incentives and create inefficient market imbalances.

In Antitrust & Competition, Health Care, Health Insurance, Pharmaceuticals, Truth on the Market 340B, Affordable Care Act, anticompetitive market distortions, medicaid, medicare, pharmaceuticals, price controls

Sharing the Wealth: Gig Economy Moves Toward a Portable Safety Net

Kristian Stout — 10 November 2015

Today, thirty-nine different companies and policy experts from a wide swath of the political spectrum signed a letter urging lawmakers to create a “portable benefits” platform that will enable sharing economy companies to continue innovating while simultaneously providing desirable social safety net benefits to workers. This is well timed, as there is a growing consensus among lawmakers (such as Senator Warner) that “something must be done” to provide benefits to workers in the so-called “gig economy.”

In total, the thirty-nine signatories to the letter are pushing for changes to existing law based on a set of principles holding that benefits should be:

Independent;
Flexible and pro-rated;
Portable;
Universal; and
Supportive of innovation

In a nutshell, this would effectively mean that there is some form of benefits available to gig economy workers that follows them around and is accessible regardless of who employs them (or, ostensibly, whether they are employed at all).

Looking past the text of the letter, this would likely entail a package of changes to existing law that would allow individual workers to utilize some form of privately created platform for managing the benefits that are normally obtained in a traditional employee-employer relationship. Such benefits would include, for instance, workers’ compensation, unemployment, disability, professional development, and retirement. A chief advantage of a portable benefits platform is that–much as in an underlying justification of the ACA–workers would no longer be tied to particular companies in order to enjoy these traditionally employer-based benefits.

Although platform-based work facilitated by smartphone apps is cutting edge, there is historical precedent for this approach to the provision of benefits. Unions have long relied upon multi-employer plans for providing benefits, and the healthcare industry developed portable health savings accounts as a means to free individuals from employer-bound health insurance plans. And the industry has been seeking fully private solutions to these sorts of problems for some time. For instance, Uber recently partnered with Stride Health to provide health insurance benefits to verified drivers.

There will, of course, be some necessary legislative changes in order to make these portable benefits platforms a reality. First, there probably needs to be a provision in the tax code that allows for workers’ contributions to their own plans to receive the same tax-favored treatment that traditional employer-based benefits receive (or, even better, the political give-away would need to be removed from employer-based benefits). Additionally, companies would need to be able to make optional matching contributions with a similar tax treatment. And lurking in the background of all of this is the specter of a large number of employer obligations. Thus, a necessary quid pro quo to get sharing economy companies to pay into these platforms will be some form of safe harbor shielding them from further obligations.

This is a win for both companies and workers. The truth is that our labor market is very fractured–labor force participation rates are at a low, and those who are working remain chronically underemployed. Coupled with this reality, the technology that enables work is becoming ever more flexible and, as shown by their expressed preferences, individuals are clearly interested in the gig economy as a means of easily obtaining work as needed. A portable benefits platform could provide the sort of support to make flexible work a viable alternative to employee status.

And for many employers–sharing economy and non-sharing economy alike–removing antiquated legal strictures from the employment relationship promises a number of increased efficiencies. Particularly in the context of sharing economy companies, this will include the ability to exert some form of control over platform workers without being sucked into an onerous employer-employee relationship.

For instance, Instacart recently moved a number of its platform workers to part-time employee status. Although the decision was very likely multi-faceted, a big part of it had to be Instacart’s desire to give training and guidance to the shoppers who provided services to the platform’s consumers (for instance, instructing them on the best sequence in which to pick groceries in order to ensure maximum freshness). However, to provide any modest degree of oversight would likely mean that Instacart would move from empowering contractors to directing employees, and thereby run into a thicket of labor laws.

Yet why should this particular employee classification be necessary? Platform-based work is a revolutionary way to defeat the traditional transaction costs that justified large, centrally-organized firms. Companies like Uber and Instacart enable what otherwise would have been fallow resources–spare labor, unused cars, and the like–to be fitted to consumer demand.

Moreover, forcing rigid employee classifications upon sharing economy workers will only reintroduce inefficiency into the worker-company relationship. Instead of allowing workers to sign on just for the amount of work they are willing to do, and allowing consumers just to purchase the amount of work they desire, an employee classification essentially requires companies to purchase labor in blocks of hours. At scale, this necessarily introduces allocation and pricing errors into the system. If a smart safe harbor is included in any legislative push for a portable benefits platform, companies could have much more flexibility in directing platform workers.

I am excited to see this development emerging from the industry and from policy makers, and I look forward to the response of our lawmakers (although, this being election season, I don’t expect too much from that response — at least not yet). There is understably a lot of concern about the welfare of workers in the new economy. But it’s important not to lose the innovative new ways of working, producing, and consuming that the modern digital economy affords by resorting to ill-fitted legal regimes from the past.

In Health Care, Health Insurance, Platforms, Regulation gig economy, Instacart, Labor Law, Ronald Coase, Sharing Economy

The competitive implications of the Affordable Care Act for health insurance merger review

Geoffrey Manne & Ben Sperry — 5 October 2015

Last week concluded round 3 of Congressional hearings on mergers in the healthcare provider and health insurance markets. Much like the previous rounds, the hearing saw predictable representatives, of predictable constituencies, saying predictable things.

The pattern is pretty clear: The American Hospital Association (AHA) makes the case that mergers in the provider market are good for consumers, while mergers in the health insurance market are bad. A scholar or two decries all consolidation in both markets. Another interested group, like maybe the American Medical Association (AMA), also criticizes the mergers. And it’s usually left to a representative of the insurance industry, typically one or more of the merging parties themselves, or perhaps a scholar from a free market think tank, to defend the merger.

Lurking behind the public and politicized airings of these mergers, and especially the pending Anthem/Cigna and Aetna/Humana health insurance mergers, is the Affordable Care Act (ACA). Unfortunately, the partisan politics surrounding the ACA, particularly during this election season, may be trumping the sensible economic analysis of the competitive effects of these mergers.

In particular, the partisan assessments of the ACA’s effect on the marketplace have greatly colored the Congressional (mis-)understandings of the competitive consequences of the mergers.

Witness testimony and questions from members of Congress at the hearings suggest that there is widespread agreement that the ACA is encouraging increased consolidation in healthcare provider markets, for example, but there is nothing approaching unanimity of opinion in Congress or among interested parties regarding what, if anything, to do about it. Congressional Democrats, for their part, have insisted that stepped up vigilance, particularly of health insurance mergers, is required to ensure that continued competition in health insurance markets isn’t undermined, and that the realization of the ACA’s objectives in the provider market aren’t undermined by insurance companies engaging in anticompetitive conduct. Meanwhile, Congressional Republicans have generally been inclined to imply (or outright state) that increased concentration is bad, so that they can blame increasing concentration and any lack of competition on the increased regulatory costs or other effects of the ACA. Both sides appear to be missing the greater complexities of the story, however.

While the ACA may be creating certain impediments in the health insurance market, it’s also creating some opportunities for increased health insurance competition, and implementing provisions that should serve to hold down prices. Furthermore, even if the ACA is encouraging more concentration, those increases in concentration can’t be assumed to be anticompetitive. Mergers may very well be the best way for insurers to provide benefits to consumers in a post-ACA world — that is, the world we live in. The ACA may have plenty of negative outcomes, and there may be reasons to attack the ACA itself, but there is no reason to assume that any increased concentration it may bring about is a bad thing.

Asking the right questions about the ACA

We don’t need more self-serving and/or politicized testimony We need instead to apply an economic framework to the competition issues arising from these mergers in order to understand their actual, likely effects on the health insurance marketplace we have. This framework has to answer questions like:

How do we understand the effects of the ACA on the marketplace?
- In what ways does the ACA require us to alter our understanding of the competitive environment in which health insurance and healthcare are offered?
- Does the ACA promote concentration in health insurance markets?
- If so, is that a bad thing?
Do efficiencies arise from increased integration in the healthcare provider market?
Do efficiencies arise from increased integration in the health insurance market?
How do state regulatory regimes affect the understanding of what markets are at issue, and what competitive effects are likely, for antitrust analysis?
What are the potential competitive effects of increased concentration in the health care markets?
Does increased health insurance market concentration exacerbate or counteract those effects?

Beginning with this post, at least a few of us here at TOTM will take on some of these issues, as part of a blog series aimed at better understanding the antitrust law and economics of the pending health insurance mergers.

Today, we will focus on the ambiguous competitive implications of the ACA. Although not a comprehensive analysis, in this post we will discuss some key insights into how the ACA’s regulations and subsidies should inform our assessment of the competitiveness of the healthcare industry as a whole, and the antitrust review of health insurance mergers in particular.

The ambiguous effects of the ACA

It’s an understatement to say that the ACA is an issue of great political controversy. While many Democrats argue that it has been nothing but a boon to consumers, Republicans usually have nothing good to say about the law’s effects. But both sides miss important but ambiguous effects of the law on the healthcare industry. And because they miss (or disregard) this ambiguity for political reasons, they risk seriously misunderstanding the legal and economic implications of the ACA for healthcare industry mergers.

To begin with, there are substantial negative effects, of course. Requiring insurance companies to accept patients with pre-existing conditions reduces the ability of insurance companies to manage risk. This has led to upward pricing pressure for premiums. While the mandate to buy insurance was supposed to help bring more young, healthy people into the risk pool, so far the projected signups haven’t been realized.

The ACA’s redefinition of what is an acceptable insurance policy has also caused many consumers to lose the policy of their choice. And the ACA’s many regulations, such as the Minimum Loss Ratio requiring insurance companies to spend 80% of premiums on healthcare, have squeezed the profit margins of many insurance companies, leading, in some cases, to exit from the marketplace altogether and, in others, to a reduction of new marketplace entry or competition in other submarkets.

On the other hand, there may be benefits from the ACA. While many insurers participated in private exchanges even before the ACA-mandated health insurance exchanges, the increased consumer education from the government’s efforts may have helped enrollment even in private exchanges, and may also have helped to keep premiums from increasing as much as they would have otherwise. At the same time, the increased subsidies for individuals have helped lower-income people afford those premiums. Some have even argued that increased participation in the on-demand economy can be linked to the ability of individuals to buy health insurance directly. On top of that, there has been some entry into certain health insurance submarkets due to lower barriers to entry (because there is less need for agents to sell in a new market with the online exchanges). And the changes in how Medicare pays, with a greater focus on outcomes rather than services provided, has led to the adoption of value-based pricing from both health care providers and health insurance companies.

Further, some of the ACA’s effects have decidedly ambiguous consequences for healthcare and health insurance markets. On the one hand, for example, the ACA’s compensation rules have encouraged consolidation among healthcare providers, as noted. One reason for this is that the government gives higher payments for Medicare services delivered by a hospital versus an independent doctor. Similarly, increased regulatory burdens have led to higher compliance costs and more consolidation as providers attempt to economize on those costs. All of this has happened perhaps to the detriment of doctors (and/or patients) who wanted to remain independent from hospitals and larger health network systems, and, as a result, has generally raised costs for payors like insurers and governments.

But much of this consolidation has also arguably led to increased efficiency and greater benefits for consumers. For instance, the integration of healthcare networks leads to increased sharing of health information and better analytics, better care for patients, reduced overhead costs, and other efficiencies. Ultimately these should translate into higher quality care for patients. And to the extent that they do, they should also translate into lower costs for insurers and lower premiums — provided health insurers are not prevented from obtaining sufficient bargaining power to impose pricing discipline on healthcare providers.

In other words, both the AHA and AMA could be right as to different aspects of the ACA’s effects.

Understanding mergers within the regulatory environment

But what they can’t say is that increased consolidation per se is clearly problematic, nor that, even if it is correlated with sub-optimal outcomes, it is consolidation causing those outcomes, rather than something else (like the ACA) that is causing both the sub-optimal outcomes as well as consolidation.

In fact, it may well be the case that increased consolidation improves overall outcomes in healthcare provider and health insurance markets relative to what would happen under the ACA absent consolidation. For Congressional Democrats and others interested in bolstering the ACA and offering the best possible outcomes for consumers, reflexively challenging health insurance mergers because consolidation is “bad,” may be undermining both of these objectives.

Meanwhile, and for the same reasons, Congressional Republicans who decry Obamacare should be careful that they do not likewise condemn mergers under what amounts to a “big is bad” theory that is inconsistent with the rigorous law and economics approach that they otherwise generally support. To the extent that the true target is not health insurance industry consolidation, but rather underlying regulatory changes that have encouraged that consolidation, scoring political points by impugning mergers threatens both health insurance consumers in the short run, as well as consumers throughout the economy in the long run (by undermining the well-established economic critiques of a reflexive “big is bad” response).

It is simply not clear that ACA-induced health insurance mergers are likely to be anticompetitive. In fact, because the ACA builds on state regulation of insurance providers, requiring greater transparency and regulatory review of pricing and coverage terms, it seems unlikely that health insurers would be free to engage in anticompetitive price increases or reduced coverage that could harm consumers.

On the contrary, the managerial and transactional efficiencies from the proposed mergers, combined with greater bargaining power against now-larger providers are likely to lead to both better quality care and cost savings passed-on to consumers. Increased entry, at least in part due to the ACA in most of the markets in which the merging companies will compete, along with integrated health networks themselves entering and threatening entry into insurance markets, will almost certainly lead to more consumer cost savings. In the current regulatory environment created by the ACA, in other words, insurance mergers have considerable upside potential, with little downside risk.

Conclusion

In sum, regardless of what one thinks about the ACA and its likely effects on consumers, it is not clear that health insurance mergers, especially in a post-ACA world, will be harmful.

Rather, assessing the likely competitive effects of health insurance mergers entails consideration of many complicated (and, unfortunately, politicized) issues. In future blog posts we will discuss (among other things): the proper treatment of efficiencies arising from health insurance mergers, the appropriate geographic and product markets for health insurance merger reviews, the role of state regulations in assessing likely competitive effects, and the strengths and weaknesses of arguments for potential competitive harms arising from the mergers.

Archives For Health Insurance

Data Property Rights and Personalized Medicine

Why Do We Have Property Rights?

Personal Health Data: What Are We Trying to Incentivize?

Data Property Rights and COVID-19

Conclusion

Share this:

Like this:

Display advertising in context

The display advertising market

The cases against Google

The case that remains

Share this:

Like this:

Abroad

At home

Recommendations

Share this:

Like this:

Current trends in private-sector-driven healthcare reform

Drug pricing and distribution innovations

Treatment innovations

More enforcement decisions like CVS/Aetna and Bayer/Monsanto; fewer like AT&T/Time Warner

Share this:

Like this:

Share this:

Like this:

Some ground rules

Private insurance

Medicaid

Would the Medicaid rolls explode? Who knows?

A win-win

Share this:

Like this:

Share this:

Like this:

Share this:

Like this:

Share this:

Like this:

Share this:

Like this:

Share this:

Like this:

Asking the right questions about the ACA

The ambiguous effects of the ACA

Understanding mergers within the regulatory environment

Conclusion

Share this:

Like this:

Search TOTM

A Top 100 Economics Blog

Recent Posts

Authors

Posts by Author

Bloggers Emeriti

Posts by Past Authors & Guests

Categories

TOTM Archives

Subscribe by Email

Subscribe by RSS

Follow Us