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International Journal of Advanced Research
Article . 2019 . Peer-reviewed
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A STUDY ON IDENTIFYING THE PRE-ANALYTICAL PHASE ERRORS LEADING TO BIOCHEMISTRY AND HEMATOLOGY SAMPLE REJECTION BY USING FMEA & PARETOS PRINCIPLE.

Authors: Golla Rachana and Manjunatha R.;

A STUDY ON IDENTIFYING THE PRE-ANALYTICAL PHASE ERRORS LEADING TO BIOCHEMISTRY AND HEMATOLOGY SAMPLE REJECTION BY USING FMEA & PARETOS PRINCIPLE.

Abstract

Laboratory specialists have been demonstrated that 70% of errors occur in the pre-analytical phase which is an important service of laboratory medicine. If the occurrence of error is manmade then it can always be identified and reduced. As the hospital management needs to evaluate the quality of laboratory services by knowing the sample rejection rate. A descriptive study was conducted to investigate and reduce the rejection rate for the Biochemistry and haematology samples received in the clinical laboratory. A strategy used in the study for the source detection of Failure modes are a) Brainstorming, b) Fish-bone diagram, c) Pareto?s chart, d) Failure Mode and Effect Analysis (FMEA) is an aid to calculate Risk Priority Number (RPN) that is the product of Occurrence Index (O.I), and Detectability Index (D.I). The total number of samples (both from OP & IP-D) received in the laboratory during the study period from January 2018 to April 2019 is about 3, 81,452 samples. The total number of samples rejected by the laboratory is 182 (0.047%). The highest rates according to Pareto?s principle & FMEA analysis are found for the failure modes sample clot, insufficient sample quantity, inappropriate sample Vacutainer/tube with RPN value of 48, 36 and 30 respectively. Even though these RPN values are highest among all identified failure modes, they are less than 50 (RPN<50) which indicates that the processes involved are well controlled.

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International Journal of Advanced Research (IJAR)

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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