Help develop sampling plan for prototype samples (medical devices)

SGquality

Quite Involved in Discussions
#1
Hello everyone,

I need help on developing sampling plans for prototype samples and am looking for which valid statistical technique to use.
Please be kind on me as I am new to Statistics :)

Thank you
 
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Bev D

Heretical Statistician
Staff member
Super Moderator
#2
We need more information.
What are the prototypes - what do they do?
What are you testing for?
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#4
OK but what do they actually do? and what will you be testing for?

sample sizes depend on many specific things. what defect rate are you looking to be under? is the device a single use device or is it a multi use instrument?
 

chris1price

Trusted Information Resource
#5
You need to consider the risk associated with the devices and of the testing. For verification of attributes I suggest looking at a binomial type model or the normal distribution for variable data. For both V&V make sure you justify the use of prototype very carefully.

These papers give good examples of the how the sample size can be determined.
Sample Sizes: How Many Do I Need? | 2014-07-07 | Quality Magazine
Statistical Sampling Plan for Design Verification and Validation of Medical Devices | IVT - JVT
 

SGquality

Quite Involved in Discussions
#6
Bev, these prototypes will be used to test the functional requirements of the device. For example, these prototypes are hearing aids and used to test various aspects of hearing aids for audio etc.
 

Mark Meer

Trusted Information Resource
#7
Bev, these prototypes will be used to test the functional requirements of the device. For example, these prototypes are hearing aids and used to test various aspects of hearing aids for audio etc.
I believe Bev replied to your inquiry in a different, related thread here. (see Post #9)
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#8
Sorry - two threads that are very similar:

I’m not an expert in hearing aids (my only exposure is that my wife wears them and I’m in charge of replacing the batteries).



Usually these things are not about some statistical calculation of the sample size, although that is important. It’s about understanding what constitutes the ‘population’.



In design verify, a re-usable device such as a hearing aid would have a smaller sample size of the device than a single use device. Sample size will still depend on what characteristics you need to verify.


Although some characteristics are deterministic - either it works or it doesn’t - some variation will have to be included. For example battery fit. Batteries have a specified size range and your design has a specified size range. At a minimum I would expect that you would need to ensure that the minimum and maximum battery size fits in the minimum and maximum specified sizes of your hearing aids. So the sample size is determined by counting the conditions to be verified.



Another example: I’m sure you have requirements regarding the wear of the battery compartment. How many battery changes are you targeting? that and your confidence level as well as the margin you need for your requirement will tell you the sample size – how many insertions do you need? Of course you could go to directed testing around stress vs strength that would not require actual insertions until validation with ‘production’ level parts.


Some characteristics are subject to inherent variation from use conditions: for example, I can imagine that you need to prove that the hearing aid meets output requirements given a range of sound volume and frequency as well as ‘fit’ in the ear? In this case your sample size is more dependent on the range of each condition than anything else. The number of devices is less important than the number of conditions. Do you just test at the extremes and the nominal? Or across the range in a distribution of conditions that is representative of the conditions that exist in actual use? It is also dependent on whether or not the hearing aid is consistent in its performance across the range. In this case of design verify you can usually have a small number of devices tested across a full range of conditions. I typically would recommend 3 devices just to be safe. The ‘number of conditions tested on each device’ is then the real sample size.
 
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