Exploring the extent of post-analytical errors, with a focus on transcription errors - an intervention within the...

Area of Science:

• Medical Research
• Clinical Data Management
• Cardiovascular Disease Risk Assessment

Background:

• The VIPVIZA study involves transcribing lipid parameters (total cholesterol, triglycerides, HDL, LDL) into a research database.
• Transcription errors can occur during this data entry process, potentially affecting downstream analyses and clinical decisions.

Purpose of the Study:

• To quantify transcription errors in lipid variables within the VIPVIZA study.
• To evaluate the effectiveness of an educational intervention in reducing these transcription errors.
• To assess the impact of transcription errors on the SCORE2 cardiovascular disease risk prediction algorithm.

Main Methods:

• Lipid parameters were transcribed by research nurses.
• Transcription errors were identified by recalculating LDL cholesterol; a difference >0.15 indicated an error.
• The SCORE2 risk category was compared using both incorrect and correct lipid values to assess misclassification.

Main Results:

• The transcription error frequency was 0.55% in 2019, decreasing to 0.25% in 2023 after an educational intervention.
• Among individuals with transcription errors in total or HDL cholesterol, 15% were assigned an incorrect SCORE2 risk category.

Conclusions:

• Transcription errors in clinical data persist despite digitalization efforts.
• Minimizing manual transcriptions outside the laboratory is crucial for data accuracy.
• Accurate lipid values are essential for reliable cardiovascular risk prediction algorithms like SCORE2.