Uber Cuts Ambulance Usage And Health Care Costs Across 766 US Cities

In recent months, it seems like there’s been nothing but bad news for Uber, like having its operating licence revoked in London (“not fit and proper”), concealing a massive cyber-attack, price gauging a passenger $14,000 for a 5-mile ride and reporting a quarterly loss of $1.5 billion. Indeed, the company is becoming almost synonymous with problems. A Bloomberg story three days ago about Airbnb began “With Uber"s problems grabbing all the headlines, it"s easy to overlook the fact that the other great "sharing economy" company, Airbnb, is also having issues caused by an overaggressive expansion and a tendency to ignore rules”.

For once, a slightly more positive story about Uber has emerged, although there is even an “Uber” downside to this. In brief, researchers have found that when Uber is launched in a city, ambulance usage declines significantly. From The Mercury News.

In what is believed to be the first study to measure the impact of Uber and other ride-booking services on the U.S. ambulance business, two researchers have concluded that ambulance usage is dropping across the country. A research paper released Wednesday examined ambulance usage rates in 766 U.S. cities in 43 states as Uber entered their markets from 2013 to 2015.

Co-authors David Slusky, an assistant professor of economics at the University of Kansas, and Dr. Leon Moskatel, an internist at Scripps Mercy Hospital in San Diego, said they believe their study is the first to explain a trend that until now has only been discussed anecdotally. Comparing ambulance volumes before and after Uber became available in each city, the two men found that the ambulance usage rate dipped significantly. Slusky said after using different methodologies to obtain the “most conservative” decline in ambulance usage, the researchers calculated the drop to be “at least” 7 percent. “My guess is it will go up a little bit and stabilize at 10 to 15 percent as Uber continues to expand as an alternative for people,’’ Moskatel said.

Slusky and Moskatel are submitting their paper to academic journals for peer review. The research was completed independently of Uber. The authors used the company’s public statements to discover when the company entered each market and obtained ambulance usage from the National Emergency Medical Services Information System, or NEMSIS, a national repository for emergency medical services data.

The reason behind the “Uber-effect” is economics. In the US, the Department of Health and Human Services estimates that the price of an ambulance ride to hospital is typically between $600-$1,000. As the Daily Mail noted in “The rise of the Uber ambulance” in April 2017.

Meanwhile, charges for ride-hailing apps charge rarely hit three figures - and customers know the approximate price when they request their ride. Ambulances, by contrast, send bills long after they are used, and often the final amount is unknown until the bill is received.

This chart is from HealthCare.com.

With health care costs having risen so much in recent years, even when people think they need emergency treatment, they increasingly have to weigh-up cost factors before phoning an ambulance. As Slusky told The Mercury News.

“If we want to reduce (health care) spending, we have to find ways to do things cheaper — and that’s in all kinds of situations where you don’t need the most expensive resource. We don’t all need to fly first-class all the time.”

Despite the obvious revenue benefit to Uber, the company was, not surprisingly, keen to distance itself from the idea that calling an Uber driver is a substitute for calling an ambulance.

“We’re grateful our service has helped people get to where they’re going when they need it the most,” said company spokesman Andrew Hasbun. “However, it’s important to note that Uber is not a substitute for law enforcement or medical professionals. In the event of any medical emergency, we always encourage people to call 911.”

While we have some sympathy with Moskatel’s contention that most patients are “pretty good” at assessing how sick they are and how quickly they need to get to hospital. However, there is obviously a risk for patients who suddenly need medical treatment on their way to hospital. Not surprisingly, The Mercury News was able to find an emergency room physician who was strongly against substituting ambulances with Uber rides.

Paul Kivela, president of the 37,000-member American College of Emergency Physicians, said he believes that for those low-risk patients who can’t drive themselves to the emergency room, Uber is a good service. But many people, he said, may not be able to differentiate between a life-threatening emergency and an innocuous medical issue. So, he said, calling 911 is always the safest bet. “A paramedic has the training and the ability to deliver life-saving care en route,” Kivela said. “Where I really have a hard time is believing an Uber driver is going to attend to you.”

Despite the risks, even officialdom sees benefits from the rise of “Uber ambulances”. In April, STAT, a health and medicine news site reported.

Last summer, Washington, D.C., city officials began studying the use of ride-hailing to respond to what they describe as “non-emergency, low-acuity” calls, which accounted for nearly half the city’s 911 calls in 2015, according to a report released in February. “In our research, we found that many of these calls did not require an ambulance,” said District of Columbia Fire and Emergency Medical Services Department spokesperson Doug Buchanan. In fact, he added, it would be better if more people used ride-hailing services instead of an ambulance. “We would love our residents to take that initiative,” he said.

The question of whether to transport someone who is ill to the hospital is a frequent source of debate amongst Uber drivers on forums like uberpeople.net. Many Uber drivers are firmly against it, citing issues like insurance cover, the risk that the person gets worse during the journey, or this.

No way in hell..I am not a medical professional and do not play one on TV
 

Mediocre, Tailing 7 Year Auction Following Yesterday's Short Squeeze

After two surprisingly strong auctions earlier in the week, when the Treasury sold both 2 and 5 Year paper to unexpectedly brisk demand ahead of the FOMC meeting, which bounced despite a record high short interest in 2Y futs, moments ago the last auction of the week closed when $28 billion in 7 Year paper was sold at a high yield of 2.126%, tailing the When Issued 2.122%, and the highest yield since 2.215% in March.

The internals were mediocre, with the bid-to-cover of 2.54 better than last month"s 2.461%, if right on top of the six auction average of 2.54%.  Indirect bidders took down 67.7%, also better than last month"s 67.4%  and above the 6MMA of 69.3%, as direct bidders were awarded 11.6%, more than the 9.4% taken down in June and the 6 auction average of 10.4%. Finally, Dealers were left with 20.6%, the lowest since April"s record low 8.8% and below the 6MMA 20.2%.

While the auction was not nearly as exciting as the last two, perhaps much of that has to do with the post-Fed rally observed yesterday, which forced short covering, mostly on the short end, but also broadly across the curve. And with less shorts to squeeze, the result was a rather mediocre auction.

Tailing, Mediocre 30Y Auction Caps Week's Treasury Offerings

One day after a mediocre, tailing 10Y reopening, the Treasury held its last Treasury auction for the week, selling $12 billion in 30Y bonds at a yield of 2.936%, above May"s 2.87% and the highest since 3.050% in May, tailing the When Issued of 2.926% by 1 basis point. This was the 4th tailing 30Y auction in the past 5.

The internals were unremarkable: the bid-to-cover of 2.31 was virtually unchanged from last month"s 2.32, but above the 6 month average of 2.27%. Total bids of $27.9b for $12.3b in bonds sold vs $27.8b in bids for $12.0b in bonds sold at the previous auction

The buyside demand was stable with indirect bidders awarded 61.7% vs previous auction’s 63.7%, and modestly below the MMA of 63.6%. Direct bidders were awarded 6.4% vs 6.7% in June, leaving Primary Dealers with 31.9% of the final aware, just higher than last auction’s 29.6%.

In retrospect, considering the recent volatility in the TSY market coupled with today"s surprise Jackson Hole, end-of-QE "trial balloon" by the ECB, it is perhaps more notable that this week"s three auctions were not more disappointing.

How Much Do People Actually Make From "Gigs" Like Uber And Airbnb

Via Priceonomics.com,

Coined shortly after the financial crisis in 2009, the so-called “gig economy” or “sharing economy” refers to the growing cadre of companies like Airbnb, Lyft, and TaskRabbit—platforms that employ temporary workers who provide a wide variety of services: delivery, ridesharing, rentals, and odd jobs. A recent Pew study estimated that nearly a quarter of all Americans earn some money through these platforms.

But how much money are the service providers in the sharing economy actually making from their "side-gigs"?

We analyzed anonymized data from Priceonomics customer Earnest, a loan provider, and examined tens of thousands of loan applicants to see how much people are earning on side-gig platforms and how these platforms stack up against each other.

We looked at a span of data accounting for just over two years, and for each worker, we analyzed a pay period of between one and 27 months. We do not know how many hours of work the income represents for each platform, as each one has a unique pricing and commission structure. 

Furthermore, this data is just reflective of the Earnest user base, who are typically refinancing college loans and therefore may be more likely to be treating these services as a “side-gig” than the typical service provider who may be more likely to treat it as a fulltime job and have different earning levels.

We found that 85% of side-gig workers make less than $500 a month. And of all the side-gig platforms we examined, Airbnb hosts earn the most by far.

In our data, on all but Lyft and Uber, we excluded any worker who made a total $10 or less from a platform to eliminate data points that could simply represent a refund from the company. For Lyft and Uber, we excluded anyone with a total income of $50 or less. Then we tallied the average monthly incomes made by workers at each company.

Data source: Earnest

Making an average of $924 off their platform each month, Airbnb hosts make nearly three times as much as other workers. Workers at the general task-service platform, TaskRabbit, rank second at $380 per month. Overall, Lyft and Uber drivers make roughly the same average per month at $377 and $364 respectively. We also observed that nearly a quarter of Lyft drivers also earned income from Uber—and of that subset, we saw that the average income was actually higher for Uber ($481 vs $396.)

Of course, on all of these platforms, there is a wide range of earners. Several Airbnb hosts in our records, for instance, made over $10,000 per month, while others made less than $200.

To really understand these averages above, we took a deeper look at these ranges. Below, we’ve charted out the income distribution for each company. The figures represent the percentage of workers who fall into each month income bracket.

Data source: Earnest

Airbnb hosts enjoy the highest average monthly earnings because there is a much wider range of income distribution on that platform than at other companies: Nearly half of all hosts make more than $500 per month.

Conversely, the majority of workers at some other companies (Etsy, Uber, Fiverr) fall into the $100 or under per month bracket.

Tallying all of these companies up, the overall distribution tilts strongly toward the lower end.

Data source: Earnest

Some 84% of all gig economy workers make less than $500 per month—but in particular, workers at Getaround (98.3% under $500 per month), Fiverr (96.3%), and Etsy (95%) have especially high percentages of low-earners.

Reasons for the low income could vary—some workers may be simply trying the platform, or put in very few hours.

Lyft, Taskrabbit, and Airbnb seem to beat this “84% under $500” average.

Data source: Earnest

It might be easy to look at this data and assume that gig economy workers are working at below market rates. After all, $500 per month is hardly a livable wage. For the industry, the key question is how many of these workers are utilizing these platforms to make a little extra cash as a side-gig versus trying to forage a full-time living.

Feudalism And The "Algorithmic Economy"

Authored by Thaddeus Howze via Medium.com,

For the sake of this essay, feudal economic models imply the idea that a very tiny segment of the society is fantastically rich while the bulk of society works hard, has few choices about the work they do, and tend to be poorly compensated for their efforts.

feu·dal·ism: noun, historical

the dominant social system in medieval Europe, in which the nobility held lands from the Crown in exchange for military service, and vassals were in turn tenants of the nobles, while the peasants (villeins or serfs) were obliged to live on their lord’s land and give him homage, labor, and a share of the produce, notionally in exchange for military protection.

Welcome to the Algorithmic Economy, a future which uses machines to determine how effective you can be and how little they can pay you in the process.

There are no unions in this economy. There are no bosses to complain to. There are no people you can ask for redress. Because in this economy, the people doing the labor are considered the least important part of the machine and it’s best if they never communicate with someone living if it can be helped.

This is just like something out of a dark and dystopian science fiction novel, except its likely happening to you, right now. If it isn’t, unless you are very fortunate, it will be, soon. I write about the near-future in my speculative fiction. Often these are my most unpopular stories because they paint technology in a less-than-ideal light.

In a world in desperate need of positive imagery, a number of famed science fiction writers such as David Brin are recommending writers look at creating more beneficial, beneficent and Utopia-oriented stories, where people see the future as something to look forward to rather than promoting the more popular (and definitely easier to write) dystopias.

I have heard David Brin and know this work does need to be done, but having the extensive background in computer technology that I do, I still feel compelled to point out just how powerful and how much effect technology can have on our society now and in the near-future.

In “Dark Harvest” I point out the future of human trafficking improving its capacity to provide “slaves to order” using social media habits to gather intelligence on users making it possible to predict their behaviors and habits. Such technologies which I see being furthered by companies like Facebook, Instagram, and now Match.com are making it even easier to find, isolate and extract people from their lives without warning and without recourse.

In “We Now Return You to Our Scheduled Advertising” I posit a world overrun by “push” information technology being used to ensure advertising cannot be stopped from being heard by potential customers.

In our current world, television advertising is diminishing due to the power of DVR technology. As a result, smartphones (because they are harder to secure) are becoming a means of forcing users to endure advertising they don’t want in order to get content.

Companies are also learning how to hack your smartphone to send you content you did not ask for, by forcing your browsers to accept cookies, they can target you with specific advertising based on your search requests. Stores can, with the right software installed, direct information to your phone in order to influence your shopping decisions.

How long before such technology becomes part of the shopping experience you cannot opt out of? Recently it became possible to push an ad to speakers at remote locations using software technology. While it was immediately repudiated, it did not stop someone from discovering it could be done.

With recent laws being created, it will be possible to extract your data from an ISP and create profiles allowing advertisers to send information directly to you, no matter where you are.

THIS WEEK, THE House of Representatives followed the Senate in voting for a resolution that throws out Obama-era regulations that would have banned your internet service provider from selling your web browsing history to advertisers. What possible reason could Congress have for repealing such a consumer-friendly policy? The refrain on the House floor yesterday was “consistency.”

“What America needs is one standard across the internet ecosystem,” said representative Greg Walden (R-OR). If services like Google and Facebook can turn data into profit, the logic goes why can’t the cable companies?

But the House’s resolution doesn’t actually apply a single, consistent standard to the internet. It maintains the broken status quo, one in which internet service providers aren’t actually at a disadvantage to websites and apps. If anything, they’re held to a lower standard. (Wired.com)

I have also written about the nature of technology in a non-fiction format discussing the future of employment, opportunities for work and the eventual need for some kind of subsidy to offset the lack of employment opportunities in the future in an essay called: “Humans Need Not Apply.”

*  *  *

In this essay, I posit something I call the “Algorithmic Economy” though it is often called the “Sharing Economy” or the “On-Demand Economy” by economists and other writers on this subject.

I prefer the “Algorithmic Economy” because it speaks to the creeping effects on decisions being made by companies and organizations, which not only include automation used in factories, but the development of apps and programs which use algorithms to direct, control and manage Human behavior.

As programmers using design-thinking engage computers to map, monitor and control Human endeavors, it is becoming more prevalent that computers are effectively in charge of Human behaviors utilizing a number of algorithms (programmed behaviors and decisions made by programmers to elicit a desired response from Humans or there programs) to enrich corporations using such technology such as Lyft, Uber, TaskRabbit and many other such “on-demand” driven businesses.

The continued existence and economic support of such companies has created companies whose values seem far greater than the benefits such corporations provide to their workers. The company is perceived to have a fantastic value which benefits investors, disrupts previous businesses or services, often unfavorably, and enriches only those at the very top of the workforce in those companies, usually executives and senior developers.

At Uber, for example, depending on the city, drivers who are, in essence the bulk of the workforce for the company can make as little as $9-$11 an hour as their only compensation for working with the company. While they are promised upwards of $30 per hour in advertising, such rates vary widely depending on the number of drivers, the time of day, the density of calls and the optimization of algorithms designed to reduce wait time for customers and to provide customers with reductions in costs per mile.

None of these reductions, however improve the amount of money made by drivers and passengers weren’t until recently even able to use the Uber app to leave tips for employees through the service because Uber decided they paid well enough that tipping wasn’t a requirement.

In fact, one of Uber’s more successful passenger programs, Uber-Pool, reduces the earning capacity of drivers by at least one third since, it cuts the cost of long trips to a third of their value under the expectation the driver will be able to make up those costs by moving multiple passengers, simultaneously.

A driver is expected to upon receipt of an Uber-Pool passenger expect at any time, their trip may be interrupted by a call to another passenger. They are expected to navigate to this new location, find the next passenger, assure the current passenger of no serious delay and get back on the road depositing the two (or three) of them in order to nearby destinations.

Unfortunately, this multi-passenger event rarely happens, in essence, reducing the cost of long trips to one third of their value since pooling occurs far less often than Uber is willing to admit. A $20 trip becomes a $7 trip of which become $5.25 after Uber gets its cut.

Adding insult to injury, Uber does not treat its drivers as employees, thus they are not compensated for the use of their vehicles, their repairs, wear and tear, their gasoline, their healthcare, or any other such requirements of normal companies for their employees.

Instead, the drivers must bear the entirety of the expense of their “economic opportunity” while turning over one-quarter of what they earn in every transaction.

If Uber were honest, they would reveal to most drivers, that under the majority of circumstances, drivers lose more money than they earn (due to the costs of incurred during their driving and vehicle operation), depending on how the algorithms are structured where someone is working. I suspect more than Uber is at fault here. I would suspect the entire workforce development of the future is heading toward this path.

More workers are doing part-time work, on-call work, unscheduled work, without significant healthcare, sick leave, or vacation pay than ever before. Corporations have grown to the point they are unable to cut any more costs during their operations and continue to pay out to investors and executives their incredible levels of profitability without cutting corners on the only remaining element of running a business: their workforce.

Rather than restructuring pay or expectations for investors, these business engines will continue to impoverish their workers, using gamification to extend their hours, while reducing their pay and opportunities for healthy lifestyles.

The New York Times reports:

The secretive ride-hailing giant Uber rarely discusses internal matters in public. But in March, facing crises on multiple fronts, top officials convened a call for reporters to insist that Uber was changing its culture and would no longer tolerate “brilliant jerks.”

Notably, the company also announced that it would fix its troubled relationship with drivers, who have complained for years about falling pay and arbitrary treatment.

“We’ve underinvested in the driver experience,” a senior official said. “We are now re-examining everything we do in order to rebuild that love.”

And yet even as Uber talks up its determination to treat drivers more humanely, it is engaged in an extraordinary behind-the-scenes experiment in behavioral science to manipulate them in the service of its corporate growth?—?an effort whose dimensions became evident in interviews with several dozen current and former Uber officials, drivers and social scientists, as well as a review of behavioral research.

Uber’s innovations reflect the changing ways companies are managing workers amid the rise of the freelance-based “gig economy.” Its drivers are officially independent business owners rather than traditional employees with set schedules. This allows Uber to minimize labor costs, but means it cannot compel drivers to show up at a specific place and time. And this lack of control can wreak havoc on a service whose goal is to seamlessly transport passengers whenever and wherever they want.

The Algorithmic Economy isn’t only going to stay in disruptive companies like the On-Demand workforce, it will make its way into other workforces, slowly, insidiously removing time, opportunities for growth, limiting costs by reducing perks except for the elite, in order to create the second age of feudal endeavor.

Their goal is to create a workforce bound by their economic debt to the system, forced to take whatever work they can find, while being paid as little for that work as possible, understanding ultimately, the creation of an indentured workforce is not only the result but an expected one, keeping society enfeebled and unable to create opportunities for further development.

Since all new creativity is held hostage in the hands of insensitive investors who promote the development of White business leaders to the exclusion of any other forms of creativity. Seventy five percent of all investment dollars are placed into the hands of White men. In the tech industry, most companies are run by, lead by, and pay the bulk of their company’s value to White men, the primary beneficiaries of such investment effort.

The Algorithmic Economy resembles feudalism complete with peasants who lack choices, and lords who decide who can become a lord, who remains a peasant, and defining the value of a peasant’s worth based on what the lord is willing to pay the peasant.

Like the feudal lords of old, neo-feudalism says they are willing to pay indebted students, just enough to not have any opportunity next year, either.

The older workers who might have known their worth will have to find a way to live off the land, creating their own slower growing opportunities because no one is funding anything which offers an opportunity for people to experience economic parity or the ability to own an operation which treats them humanely, pays them fairly, and doesn’t believe exploitation is an effective work and pay structure.

For most older workers, their opportunities lie with older exploitive corporations such as Walmart, known for its low pay and older workforce, or at the hands of the aforementioned Uber, who has, at least in the Bay Area, has a much older, and more minority workforce.

The driver diversity makeup is distinct from the much Whiter corporate office workers who draw the lion’s share of the money from the Algorithmic Economy they have helped to create and surely recognize how their algorithm exploits their workers.

If Uber’s programmers are smart enough to recognize how those numbers and gamification ensure their own prosperity, they are also aware that drivers earn less, stay with the company for less time and will eventually leave the company once they understand how they are being exploited.

Can such companies change their behaviors? It is unlikely given the expectations of double digit growth by investors and the stock market. Thus we can assume, such companies will continue to make money for the elite members of society while being a drain on every other aspect of our social fabric undermining individual wealth and earnings, employment opportunities, home ownership, and community development.

People without money can’t improve themselves or their communities. People who exploit those people don’t help with those communities either, creating a vacuum effect, taking money from communities without ever returning an equal or greater amount of money to those areas, ensuring the slow and inexorable decline of society over time.

Do a bit of research on the subject of the On-Demand economy. While prognostications promote the idea it is good for investors, almost no mention of the people doing the work and their eventual fates are ever mentioned. There is an amazing collection of essays on the On-Demand economy which point out the future of this industry and what it means to the modern workforce.

There will be arguments on both sides of the fence, pro and con, but my entreaty to you is simple: Read about it. Learn about it. Pay attention to the disruptive force it is having on your society because while you may believe it doesn’t affect you, you’re wrong.

Don’t take my word for it. Watch it and see for yourself. It is happening before you eyes. Don’t blink.

The workforce of the future will be smaller than you think.