Original scientific paper

https://doi.org/10.11613/BM.2018.020707

Risk analysis and assessment based on Sigma metrics and intended use

Yong Xia ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China
Hao Xue ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China
Cunliang Yan ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China
Bowen Li ; Student, Guangdong Medical University, Dongguan, China
ShuQiong Zhang ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China
Mingyang Li ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China
Ling Ji ; Department of Clinical Medical Laboratory, Peking University Shenzhen Hospital, Futian District, Shenzhen, China

Abstract

Introduction: In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and
assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance (σ) expectations of
42 analytes were developed.
Materials and methods: Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which
was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity
of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined
as acceptable standards; the sigma performance expectations were calculated.
Results: Among the 42 analytes, tests with σ ≥ 6, 5 ≤ σ < 6, 4 ≤ σ < 5, 3 ≤ σ < 4, σ < 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk
tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had
sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations
≥ 3.
Conclusions: Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify
the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and
meet the low risk requirements of patients and clinicians.

Keywords

risk analysis; risk assessment; Six Sigma; Sigma metrics; failure mode and effects analysis

Hrčak ID:

201527

URI

https://hrcak.srce.hr/201527

Publication date:

15.6.2018.

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