Achieving High Reliability in Histology:  An Improvement Series to Reduce Errors

Area of Science:

• Medical Laboratory Science
• Histopathology Workflow Optimization
• Quality Improvement in Healthcare

Background:

• Histology processes have remained largely unchanged for 175 years, despite medical advancements.
• Patient label identification errors (LEs) in histology labs pose significant risks, leading to misdiagnoses and incorrect treatments.
• Identifying and mitigating LEs is crucial for patient safety and laboratory accuracy.

Purpose of the Study:

• To identify critical control points for labeling errors (LEs) within the histology workflow.
• To implement targeted interventions to reduce the frequency of LEs.
• To quantify the impact of workflow redesign on error rates and rework time.

Main Methods:

• A numerical step key (SK) was developed over 36 months to systematically capture and analyze LEs.
• Lean workflow redesign principles were applied to address manual slide printing and microtome cutting.
• Labeling error rates were compared before and after the implementation of a barcode-enabled LIS and an innovative ice tool box.

Main Results:

• Adoption of a barcode-enabled LIS reduced the LE rate from 1.03% to 0.28%.
• Implementation of a single-piece workflow for microtome cutting further decreased the LE rate to 0.22%.
• Overall, a 78.64% reduction in LEs and a 35.28% decrease in rework time were observed.

Conclusions:

• Tracking LEs using a numerical SK is vital for understanding error patterns.
• Customized Lean interventions effectively reduce labeling errors in histology.
• Workflow improvements enhance laboratory accuracy and efficiency, ultimately benefiting patient care.