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Selecting Statistical Procedures for Quality Control Planning Based on Risk Management.

Martín Yago¹, Silvia Alcover²

¹Laboratory of Biochemistry, Hospital General de Requena, Valencia, Spain. martinyago.lopez@gmail.com.

Clinical Chemistry

|May 21, 2016

Summary

This summary is machine-generated.

The probability of rejecting errors (PEDC) and maximum expected unacceptable patient results (Max E(NUF)) are related QC performance measures. This study links these metrics to analytical process capability for better risk-based QC planning in clinical labs.

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Area of Science:

Clinical Laboratory Science
Statistical Quality Control
Risk Management in Healthcare

Background:

Traditional statistical quality control (QC) planning uses the probability of rejecting errors (PEDC) to assess QC procedure performance.
The maximum expected number of unacceptable patient results (Max E(NUF)) is a newer metric, aligning QC planning with clinical laboratory risk management concepts.

Purpose of the Study:

To investigate the relationship between PEDC and Max E(NUF) for common QC procedures.
To develop charts linking Max E(NUF) with analytical process capability for risk-based QC planning.

Main Methods:

Utilized a statistical model to analyze simple QC procedures common in clinical laboratories.
Constructed charts correlating Max E(NUF) with analytical process capability.

Main Results:

A strong relationship exists between PEDC and Max E(NUF) for simple QC procedures.
Max E(NUF) values are consistent for analytical processes with similar capabilities.
High PEDC procedures typically exhibit low Max E(NUF) values, and vice versa.

Conclusions:

PEDC can be estimated from Max E(NUF), and vice versa, facilitating QC procedure selection.
The PEDC metric aids in estimating patient harm probability, supporting risk-based QC planning.