Posted on 04/12/2015 1:53:43 PM PDT by nickcarraway
A blog post on Medium got a lot of attention recently for claiming that Uber drivers are now faster than ambulances in New York City. The numbers seemed pretty damning for the ambulances: the median Uber rider in Manhattan can expect to get a ride in 2.42 minutes. In the outer boroughs, the median wait is still just 3.1 minutes. The median ambulance wait? About twice as long at 6.1 minutes.
We wondered, how does the Bay Area stack up? Newsweek obtained some figures from Uber and mapped them.
According to Newsweek, the median wait time for an Uber in San Francisco is just 3.2 minutes. Los Angeles is not far off with 3.8 minutes. If that sounds like a hard number to beat, that's because it is. The target response time for San Francisco ambulances is 10 minutes for 90% of calls. In January, 2015, the average SF ambulance took 7.49 minutes to arrive(pdf).
But wait--you might say--aren't you comparing averages and medians? Yes, and that's a problem. But that's just where the problems start when you try to compare these two services.
All we have from Uber (via Newsweek) is that 3.1 minute median number. Recall that a "median" is the halfway point in a distribution of numbers. In other words, half of Uber rides are less than 3.1 minutes, and half are more. How much more? That, we don't know. This isn't just a matter of semantics, it's crucially important in a life or death situation. If we know that half of all rides take more than 3.1 minutes, we might hope that a lot of those longer rides are very close to 3.1 minutes. Maybe they are. But maybe a lot are closer to 10 minutes. Maybe 30? An hour? The median doesn't tell us that information. It could be anything.
The worry is that the distribution of Uber drives might be "skewed", meaning the first half might be very close to 3.1 minutes, but the last half might be very far from 3.1 minutes. If you plotted all those rides and put time on the X axis with number of rides on the Y, a skewed curve might look like this:
Importantly, we simply don't know what this curve actually looks like and Uber has no responsibility to provide it. This is one reason why emergency services uses the 90th percentile as the target: it lets you know what the wait time is for the vast majority of rides in a way that a "median" cannot.
The conclusion Medium writer Minqi Jiang came to was that Uber should get into the ambulance game--that Uber drivers with defibrillators and CPR training could act like first-responders and help take the load off of city ambulance services.
I would say that the numbers alone can't justify a call like that. We simply don't know nearly enough. But one thing we do know is that San Francisco's ambulance response has been in pretty bad shape recently.
The city has struggled for years to hit its 10-minute target for ambulance waits. In January, SF ambulances missed the goal target by 2.49 minutes. This was actually an improvement over recent months. In August of last year, the 90th percentile was 14.63 minutes.
A San Francisco Chronicle investigation last fall uncovered residents that have had to wait 30 minutes or more for an ambulance.
Fire Chief Joanne Hayes-White and Mayor Ed Lee said the problem stemmed from shortages in staffing and ambulances. The mayor convened an "Ambulance Working Group" to recommend solutions.
In February, the working group released its final memo, recommending the the fire department hire 26 new EMTs and build a new $40 million dollar ambulance facility. An earlier recommendation to acquire 19 new ambulances and replace many older ones has already been carried out. One recommendation this blog is very excited about is the creation of a "performance data dashboard" that would publish online data for ambulance response times and other "critical public safety measures."
The paramedics in the ambulance have defibrillators and stuff. They have extra bodies that can give CPR while en route, etc. They also have a siren that can clear paths for the trip to the hospital. And heaven help you in a Ford Focus comes to pick up the 350 pound man and his wife.
Pretty dumb idea. Though it might make sense for something like the dedicated systems for hauling elderly people around, to daycare centers and the doctor, etc.
Paying private individual to show up when needed is a whole lot less expensive than maintaining a whole reserve capacity that isn’t used all the time.
Could provide much better service, too.
Reminds me of a line from one of Richard Pryor’s old routines: “...HE’S ONE OF THOSE CRAZY “SHOOT ME” N****RS. “WELL KILL ME! SHOOT ME MOTHER*****R!” POW! “OH, SH*T! OH, GODD***! SOMEBODY CALL ME A CAB. DAMN IF I’M GOING TO BLEED TO DEATH WAITING FOR AN AMBULANCE.”
Hopefully not...
I worked for Uber and wouldn’t recommend anyone working for them. I had questions about several issues. I was told one question per email. Be damned if I am going to write 60 emails for 60 questions. They treat their drivers like cattle and heaven help you if you have a dispute with the customer. Uber will more than likely take the customer’s side and leave the driver high and dry. Uber is not uber friendly to its drivers whom they see as cash cows.
One other thing is good luck getting immediate help from them on a Friday night or Saturday night. Those are the busiest nights of the week. You email them and you’d be lucky enough to get a response by the following week.
My experience is that those who arrive at an overwhelmed ER, i.e. most ER’s these days, go to the head of the queue if they come in via ambulance rather than private auto.
Just another way that private enterprise beats anything a government-sponsored enterprise can do. When seconds count, ambulances (and police) are minutes away.
This article also fails to account for the numbers and densities. If there are twice as many Uber drivers as ambulances, that means chances are more likely that an Uber driver is closer to you to respond. they’ll already be closer, so obviously their median time (and likely average) is going to be lower.
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