# A test method for selecting suitable cleaning indicators for routine cleaning monitoring on a washer-disinfector in a central sterile supply department

## TL;DR

This paper presents a method to select effective cleaning indicators for monitoring automated washer-disinfector processes in healthcare settings.

## Contribution

A systematic test method is introduced to evaluate and select optimal cleaning indicators for routine monitoring in CSSD.

## Key findings

- Cleaning indicators showed varying performance under different simulated cleaning protocols.
- The optimal indicator is the last to be washed off during normal cleaning and clearly shows dirt residue under error conditions.

## Abstract

Cleaning indicators are widely used to evaluate the efficacy of cleaning processes in automated washer-disinfectors (AWDs) in healthcare settings. In this study, we systematically analyzed the performance of commercial indicators across multiple simulated cleaning protocols to guide the correct selection of suitable cleaning indicators in Central Sterile Supply Departments (CSSD). Eleven commercially available cleaning indicators were tested in five cleaning simulations, P0 to P4, where P1 represented the standard cleaning process in CSSD, while P2-P4 incorporated induced-error cleaning processes to mimic real-world errors. All indicators were uniformly positioned at the top level of the cleaning rack to ensure comparable exposure. Key parameters, including indicator response dynamics (e.g., wash-off sequence) and final residue results, were documented throughout the cleaning cycles. The final wash-off results given by the indicators under P0, in which no detergent was injected, were much worse than those of the other four processes. Under different simulations, the final results of the indicators and their wash-off sequences changed substantially. In conclusion, an effective indicator must be selected experimentally. The last indicator to be washed off during the normal cleaning process that can simultaneously clearly show the presence of dirt residue under induced error conditions is the optimal indicator for monitoring cleaning processes.