Why Quantitative Fit Testing?
During the pandemic, we had the opportunity to run some controlled experiments regarding Fit Testing N95 Respirators.
The state of California invested heavily in N95s produced by BYD, and we had the opportunity to test thousands of them using Accufit 9000s. Our protocol was to test the BYD respirators provided by the State and, if they failed, try different varieties of respirators to get a proper fit.
Only 42% of individuals tested for the BYD respirator achieved a passing fit factor of greater than 100. On the other hand, some facilities reported 100% pass rates through qualitative fit testing.
It is noted that a volume of these respirators were defective, as the manufacturer acknowledged.
Regardless of the defective respirators, the respirator design had quirks that caused good respirators to fail disproportionately on specific facial profiles, making it a poor fit for the majority of those tested.
Qualitative Fit-Testing (QLFT) left many healthcare workers believing they were protected when they were not or caused individuals to doubt the effectiveness of respiratory protection.
Advantages of QNFT (Quantitative Fit Testing):
Objectivity: QNFT provides an objective, numerical measurement (fit factor) of respirator leakage, eliminating subjectivity and the potential for human error inherent in qualitative testing both on the testee’s and the administrator’s behalf. There is no argument regarding how effective or ineffective the respirator is given a calibrated and verified device. I have had many nurses tell me that after their respirator failed, they had been passing qualitative tests for years.
Accuracy: QNFT offers a more precise and accurate assessment of respirator fit, which is crucial for high-risk environments where even minor leaks can have serious consequences. This allows the user to have real data as to how well their respirator works rather than a pass-fail and gives employers assurance that their staff are protected.
Data-driven decision-making: QNFT generates data that can be used to identify patterns, track trends, and make informed decisions about respirator selection and training programs.
Regulatory compliance: QNFT is often required for certain types of respirators or specific work environments, ensuring compliance with OSHA regulations. When fit-testing a full-facepiece negative-pressure respirator, it must be used to obtain its assigned protection factor of 50 and allow it to be used in environments up to 50 times the Permissible Exposure Limit.
Improved worker confidence: QNFT can boost worker confidence in their respiratory protection, knowing their respirator has been quantitatively validated for a proper fit. This proved to be very helpful in convincing medical staff it was safe to work in areas of known infectious hazards.
While Qualitative Fit-Testing may meet the minimum requirements set forth by the 1910.134 – Respiratory Protection standard. I for one, would not bet my life on the results.
