Validation of the Device Feature Approach for Reusable Medical Device Cleaning Evaluations.

Area of Science:

• Medical Device Reprocessing
• Infection Prevention and Control
• Biomedical Engineering

Background:

• Worst-case device feature identification is crucial for validating cleaning processes, especially for reusable medical devices.
• Current compendial methods may not be as conservative or targeted as a device feature approach.
• Existing patient safety gaps exist at the interface of device manufacturers and healthcare facilities regarding device processing.

Purpose of the Study:

• To investigate and verify the efficacy of a device feature approach for cleaning validation.
• To mitigate patient risk by ensuring effective reprocessing of reusable medical devices.
• To develop a quantitative cleaning classification system to augment the Spaulding classification.

Main Methods:

• Focused on identifying and testing worst-case device features for cleaning validation.
• Conducted 56,000 flushes targeting specific device features to ensure rigorous validation.
• Utilized a device feature approach to isolate and study the most challenging cleaning variables.

Main Results:

• The device feature approach provides a more conservative validation method compared to testing entire devices.
• This approach can inform the development of a design feature database for device cleanliness validation.
• Data generated from design features serve as critical control points for cleaning and microbiological quality.

Conclusions:

• The device feature approach effectively verifies cleaning procedures and mitigates patient risk.
• This method enhances microbial risk reduction and closes patient safety gaps in medical device reprocessing.
• Findings will inform the digital transformation of the medical device industry and healthcare delivery, including automation.