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Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator.

Salinas M, López-Garrigós M, Flores E, Santo-Quiles A, Gutierrez M, Lugo J, Lillo R, Leiva-Salinas C - Biochem Med (Zagreb) (2015)

Bottom Line: We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square.We present a practical and effective methodology to monitor unsuitable sample preanalytical errors.The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system.

View Article: PubMed Central - PubMed

Affiliation: Clinical Laboratory, Hospital Universitario de San Juan, San Juan de Alicante, Spain ; Department of Biochemistry and Molecular Pathology, Universidad Miguel Hernandez, Elche, Spain.

ABSTRACT

Introduction: Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy centres; and finally to evaluate a single synthetic preanalytical indicator that may be included in the balanced scorecard management system (BSC).

Materials and methods: We collected individual and global preanalytical errors in haematology, coagulation, chemistry, and urine samples analysis. We also analyzed a synthetic indicator that represents the sum of all types of preanalytical errors, expressed in a sigma level. We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square.

Results: There was a decrease in the number of errors along the years (P<0.001). This pattern was confirmed in primary care patients, inpatients and outpatients. In blood samples, fewer errors occurred in outpatients, followed by inpatients.

Conclusion: We present a practical and effective methodology to monitor unsuitable sample preanalytical errors. The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system.

Show MeSH
Annual synthetic indicator results: Shows the annual synthetic indicator results that represent the sum of all types of preanalytical errors with respect to all samples collected calculated as the number of errors per million samples and converted to a sigma level.
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f3: Annual synthetic indicator results: Shows the annual synthetic indicator results that represent the sum of all types of preanalytical errors with respect to all samples collected calculated as the number of errors per million samples and converted to a sigma level.

Mentions: The annual synthetic indicator was again significantly (P < 0.001) lower in 2012 (90.14 errors per 10,000 samples) than in 2003 (144.92 errors per 10,000 samples). The synthetic indicator results, expressed as a sigma level (3.68 in 2003 vs. 3.87 in 2012), shows the same trend that prior indicator results, but in the opposite direction: the higher the sigma level, the higher the performance of the process, and the lower number of errors and variability (Figure 3).


Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator.

Salinas M, López-Garrigós M, Flores E, Santo-Quiles A, Gutierrez M, Lugo J, Lillo R, Leiva-Salinas C - Biochem Med (Zagreb) (2015)

Annual synthetic indicator results: Shows the annual synthetic indicator results that represent the sum of all types of preanalytical errors with respect to all samples collected calculated as the number of errors per million samples and converted to a sigma level.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4401317&req=5

f3: Annual synthetic indicator results: Shows the annual synthetic indicator results that represent the sum of all types of preanalytical errors with respect to all samples collected calculated as the number of errors per million samples and converted to a sigma level.
Mentions: The annual synthetic indicator was again significantly (P < 0.001) lower in 2012 (90.14 errors per 10,000 samples) than in 2003 (144.92 errors per 10,000 samples). The synthetic indicator results, expressed as a sigma level (3.68 in 2003 vs. 3.87 in 2012), shows the same trend that prior indicator results, but in the opposite direction: the higher the sigma level, the higher the performance of the process, and the lower number of errors and variability (Figure 3).

Bottom Line: We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square.We present a practical and effective methodology to monitor unsuitable sample preanalytical errors.The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system.

View Article: PubMed Central - PubMed

Affiliation: Clinical Laboratory, Hospital Universitario de San Juan, San Juan de Alicante, Spain ; Department of Biochemistry and Molecular Pathology, Universidad Miguel Hernandez, Elche, Spain.

ABSTRACT

Introduction: Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy centres; and finally to evaluate a single synthetic preanalytical indicator that may be included in the balanced scorecard management system (BSC).

Materials and methods: We collected individual and global preanalytical errors in haematology, coagulation, chemistry, and urine samples analysis. We also analyzed a synthetic indicator that represents the sum of all types of preanalytical errors, expressed in a sigma level. We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square.

Results: There was a decrease in the number of errors along the years (P<0.001). This pattern was confirmed in primary care patients, inpatients and outpatients. In blood samples, fewer errors occurred in outpatients, followed by inpatients.

Conclusion: We present a practical and effective methodology to monitor unsuitable sample preanalytical errors. The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system.

Show MeSH