People go on vacation typically for a week or more. A mini vacation is perhaps two days. With our plane, we have been taking nano vacations. For example, the last one was leaving around 10 am, flying to Martha’s Vineyard, walking around Edgartown and having lunch, flying back, and home around 2:30.
Recently, I became aware of an analysis of the Gulfstream IV crash last year in Bedford, MA (KBED), an airport where I train.
To recall, the crew attempted to takeoff with the gust lock* engaged – the plane was never airborne and crashed after overrunning the runway. All aboard died.
*gust lock is a device which prevents the control surfaces from moving to protect them on the ground from wind gusts. It is supposed to be disengaged before flight.
Besides not disengaging the gust lock, the pilots failed to perform a flight control check (that verifies that controls move in all directions that they should). This check is standard for any plane and if performed would have alerted the crew to the problem.
But the astounding revelation in the NTSB report is that the flight crew almost never performed checklists: “A review of data from the airplane’s quick access recorder revealed that the pilots had neglected to perform complete flight control checks before 98% of their previous 175 takeoffs in the airplane, indicating that this oversight was habitual and not an anomaly.”
This has been referred to as normalization of deviance and is explained here. That is, deviant behavior is so commonplace that it is no longer considered deviant. And yes, it happens in healthcare too.
For those who want more details, the NTSB report is here.
[The photo is Martha’s Vineyard snow removal operations taken during a flight two days after two feet of snow fell in the Boston area.]
I had previously mentioned in this blog how the editor of Clinical Chemistry is not fond of letters and replies so any thought of me replying to the reply would be a lost cause. Not that I would anyway. The authors who replied were kind in their comments and I have only one comment which I make at the end of this entry.
One cynical comment about these glucose meter models that relate precision and bias to total error is that you can make beautiful contour graphs because there are three variables. If you add interferences, no more simple contour graphs.
But what does it take to add interferences to the glucose meter (simulation) model. First one needs to list all candidate interfering substances and test them. Manufacturers have already done this but unfortunately, don’t try to use the information in the package insert. You can thank CLSI EP7 for this which allows a manufacturer to say compound XYZ does not interfere – if the manufacturer finds that the interference is less than 10% and the goal was 10%. So there could be a bunch of compounds that interfere but at levels less than 10%. This means that unless one can access the original manufacturing data, one would have to do over all of the interference studies. Then one needs the patient distribution of the concentration of each interfering substance. With this information one can randomly select a concentration of each interfering substance and apply the appropriate equation to generate a bias.
Thus, simulations, while still models and subject to the possibility of being incorrect, can require a significant amount of work.
My comment to the authors who replied to my Letter deals with their statement: “This is exactly the reason we advised in our work to adopt accuracy requirements more stringent than those resulting from simulations.” A similar statement was made by Boyd and Bruns back when I similarly critiqued their model. Now for sure, if the required bias is reduced and interferences are small, this will work because the total error will meet goals. The problem is, one has no knowledge of the bias contributed by interferences. And perhaps more importantly, this strategy will not work to prevent errors in the D zone of an error grid. I mention in my last post that with a bias of zero and a CV of 5%, one could get a D zone error if the observation is 80 standard deviations away. This will not happen anytime soon, but a gross interference is possible.
I’ve been filming my flights for some time. Originally, I attached a camera to a suction mount but it fell shortly after I started the engine. I tried it on another flight with the same result. I realized that even if I replaced the suction mount, I’d always being worrying about it falling. So I turned to the clamp mounts. Here are the ones I use:
The SafeRacer clamp is inexpensive and relatively versatile.
I often use this clamp with an iPhone 5, which requires an adapter: http://www.rakuten.com/SR/SearchResults.aspx?mfgid=391307
The Mini Cardellini with Noga Arm aka Israeli Arm is the Cadillac of clamps.
Strut mount – This fits on the strut of a Cessna
I wanted to fly from Norwood MA to Montauk, NY, which as a direct flight is 75 nm, as shown below.
I decided to fly IFR but the likelihood of getting a direct routing for a trip of this length is tiny. So I looked up previous routes and found and filed for this one, which is only 77 nm.
But when I called ground for my clearance, I was given this routing.
Not only is it longer (132 nm) including flying past my destination for about 20 nm (adds 40 nm to the trip), much more is over water. So I cancelled IFR and flew VFR.
I attended an aviation club where a video was shown which depicts a fly-by-wire system for general aviation. The benefit of such a system is that a stall or unusual attitude is eliminated. The reception to the video was varied with some doubting that it would improve safety but one comment that caught my attention was that this advance removes the challenge of flying.
But progress is inevitable – here is a table of progress for general aviation planes, starting with the introduction of the aileron. So if you really wanted to go back to the old days, you would turn by warping the wing. Some pilots might enjoy the challenge of flying legacy (steam) gauges in a tail wheel plane without an autopilot in IMC but I would rather have all of the latest technology.
|Warped wing||Aileron||Easier to turn|
|Carburetor||Fuel injection||No ice build up|
|Hand flying||Auto pilot||Relieves pilot workload|
|Legacy gauges||Glass cockpit||More information|
|Hand Flying||Straight and level button||Easier recovery from unusual attitudes|
|Tail wheel||Tricycle||Easier to land|
|No fly by wire||Airbus style fly by wire*||Can’t put plane in unusual attitude|
|No BRS||BRS (parachute)||Safer|
*Not yet available for general aviation
A flying blog that I read posed the question “go or no go” meaning would a pilot fly the flight with the potential for bad weather (in a general aviation airplane from San Francisco to Seattle). The intent of this was to get people who responded to discuss the weather reports that were presented in the blog and that’s just what people did. But in doing this, virtually all of the responses were about the risk side of the equation but every risk management decision should weigh the risk benefit tradeoff. Thus, the benefit of flying your own plane is the enjoyment of flying and also getting to a destination but in this case, the risk of bad weather (and its consequences) was greatly increased with no gain in benefit, and flying commercially was a viable alternative.
I suspect that for in-vitro diagnostics, the other side of the risk benefit equation is also neglected. My sense is that …
FDA focuses more on risk than benefit. That is, many diagnostic assays provide important information to the clinician and outweigh the harm of assay error. Put another way, more people are helped by the assay information provided to the clinician than the people that are harmed by assay error.
POC assays are often evaluated more on benefit than risk. Most POC assays can also be performed in the laboratory, albeit not as fast but the POC assays usually have more error. Does the rapid result outweigh harm due to increased error? In the case of A1C, some say no.