How is the number of medical device test samples determined?

How is the number of medical device test samples determined?

The reliability and effectiveness of medical devices are verified by various tests. However,it is important to determine the appropriate number Medical device test samples. In this article, we will look at the basic steps that can be used to determine the number of specimens for medical device testing.

Step 1

Before testing your medical device, you should consult the ISO 13485, ISO 14971 and ISO 11607 standards. These standards provide guidance on the number of samples to be tested according to your product group.

Step 2: Conduct a risk analysis

According to ISO 13485, risk is defined as the likelihood and severity of potential harm. A risk analysis of your device can help you determine which tests need to be performed and how many samples are needed for each test.

Step 3: Define the purpose of the test.

Every test has a specific purpose. You need to clearly define the purpose of the test and the type of results you want to obtain. This is an important step in determining the number of samples.

Step 4: Statistical sampling should be planned.

It is important to use statistical methods to determine the sample size. Statistical sampling plans are used to calculate the number of samples needed to perform the tests with a given confidence level and error tolerance.

Step 5: Define confidence intervals and error tolerance.

When creating a statistical sampling plan you need to define the confidence intervals and error tolerance you want to have. This plays an important role in calculating the number of samples.

Step 6: Calculate the number of samples.

Using statistical calculations, the number of samples required for testing should be calculated according to the confidence interval and error tolerance you have set.

The Role of Risk Assessment, Failure Mode and Effects Analysis (FMEA)

  • Using FMEA: This method is used to determine how faulty equipment is and to identify which parts of the process need the most modification. FMEA considers three basic inputs:

  • The probability of something happening (S): This assesses the probability of a particular fault or failure. A low probability is close to 1 and a high probability is close to 5.

  • Severity if such a situation occurs (Po): If there is a fault or problem, how serious is it? Fatal consequences represent the greatest force of gravity.

  • Probability of detection (D): This assesses the speed and reliability with which a given defect or fault can be detected. The probability of poor detection is close to 1 and the probability of detection is close to 5.

Step 7: Calculate the Risk Priority Number (RPN).

These three inputs (S, Po and D) are used to quantify the potential damage associated with the device.  You multiply these ratings to obtain what is known as the Risk Priority Number (RPN). The RPN is a number related to the safety and risk of the device. A higher RPN value represents a higher risk.

We then use the table below to determine risk tolerance, hazard remediation and design requirements.

Step 8: Implementing the Results

The results of risk analysis and reliability assessment play an important role in the development and production of medical devices. If a device falls into the high risk category, the following measures should generally be taken Redesign, manufacturing process, testing and validation


Determining the correct number of medical device test samples before testing your medical device is an important step to ensure reliable results, safety and efficacy. You can accomplish this step by reviewing relevant standards, conducting a risk analysis, defining test objectives and using a statistical sampling plan. This helps you both improve product quality and ensure compliance with applicable regulations.

The process of calculating the sample size can be complex and requires statistical knowledge. It is therefore important that you work with a qualified statistician or quality manager to review and perform a more detailed sample count calculation.

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