TY - JOUR
T1 - The Use of Temperature and Pressure Data Loggers to Validate the Steam Sterilization of Category A Clinical Waste
AU - Flinn, Jade
AU - Michalek, Andrew
AU - Bow, Lindsay
AU - Hynes, Noreen A.
AU - Philpot, Donald
AU - Garibaldi, Brian T.
N1 - Publisher Copyright:
© Copyright 2022, ABSA International 2022 2022.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - Introduction: Over the past decade, there have been outbreaks associated with high consequence infectious diseases such as Ebola virus disease, Lassa fever, and Monkeypox. The proper handling of clinical waste from patients infected with such pathogens is critical to ensure healthcare personnel and community safety. Methods: Mock clinical waste bags were created to simulate four distinct waste streams: personal protective equipment (PPE), dry linens, wet linens, and solidified liquids. Pressure and temperature data loggers were buried in the middle of simulated waste loads to record time at a sterilization temperature of 132°C (270°F) to reduce sterilization time. We also validated super rapid biological indicators (BIs) by embedding standard BIs (48 h), rapid BIs (3 h), and super rapid BIs (24 min) within each load. Cycles were validated over a 2-day period, using a total of 36 simulated waste bags (6 bags each for PPE, dry linen, and wet linen, and 18 bags for solidified liquids). Results: All waste bags achieved the target sterilization temperature, all BIs passed and cycle times were substantially decreased. For PPE waste processing, an estimated 15 h was saved for a 24-h period. Discussion: Default factory settings are inadequate to disinfect Category A clinical waste. Reliance on autoclave temperature readings may overestimate time at goal sterilization temperature for actual waste loads. Conclusions: The data provided by within bag data loggers and BIs allow for the optimization of autoclave parameters to increase throughput and enhance staff safety.
AB - Introduction: Over the past decade, there have been outbreaks associated with high consequence infectious diseases such as Ebola virus disease, Lassa fever, and Monkeypox. The proper handling of clinical waste from patients infected with such pathogens is critical to ensure healthcare personnel and community safety. Methods: Mock clinical waste bags were created to simulate four distinct waste streams: personal protective equipment (PPE), dry linens, wet linens, and solidified liquids. Pressure and temperature data loggers were buried in the middle of simulated waste loads to record time at a sterilization temperature of 132°C (270°F) to reduce sterilization time. We also validated super rapid biological indicators (BIs) by embedding standard BIs (48 h), rapid BIs (3 h), and super rapid BIs (24 min) within each load. Cycles were validated over a 2-day period, using a total of 36 simulated waste bags (6 bags each for PPE, dry linen, and wet linen, and 18 bags for solidified liquids). Results: All waste bags achieved the target sterilization temperature, all BIs passed and cycle times were substantially decreased. For PPE waste processing, an estimated 15 h was saved for a 24-h period. Discussion: Default factory settings are inadequate to disinfect Category A clinical waste. Reliance on autoclave temperature readings may overestimate time at goal sterilization temperature for actual waste loads. Conclusions: The data provided by within bag data loggers and BIs allow for the optimization of autoclave parameters to increase throughput and enhance staff safety.
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U2 - 10.1089/apb.2022.0003
DO - 10.1089/apb.2022.0003
M3 - Article
C2 - 36776749
AN - SCOPUS:85132199865
SN - 1535-6760
VL - 27
SP - 106
EP - 115
JO - Applied Biosafety
JF - Applied Biosafety
IS - 2
ER -