Abstract

Medical Relevance MR is the fundamental premise in Clinical Laboratories. Our mission is to provide reliable and timely information for decision making including diagnosis, prognosis, treatment and surveillance. In consequence, the necessity to establish adequate Analytical Goals AG for all the tests is evident, in order to guarantee that information provides maximum benefit with least risk and best cost, avoiding false positive and false negative results. Analytical Performance Specifications APS can be set using several strategies depending on three interdependent perspectives including Medical Relevance, Biological Variation and Technology. From technological perspective is important to acknowledge SIX SIGMA 6S which emerged in industry in 1979 to improve quality on manufacturing processes and achieve a level of only 3.4 Defects per Million Units Produced DPMUP. It comprises a whole system where importance is given to performance specifications in accordance to customer requirements, statistical measurements and technological status. To review and document SIX SIGMA 6S fundaments and tools and to assess applicability on Clinical Laboratories, comparing data with CLIA 2024 Performance Specifications. Materials and methods: This is a revision of basic concepts and fundamental methods of SIX SIGMA 6S, including definitions, formulas and indicators of Analytical Variability. with the perspective of SIX SIGMA 6S on Analytical Goals AG according to Tonks and Aspen Analytical Coefficients of Variation ACV that have been used for decades in Clinical Laboratories as indicators of reliability, precision and accuracy. Calculation of Biological Variability BV in Laboratory Medicine depend primary on Reference Limits RL where Tonks criterion represents 25% of normal range and is equal to one Biological Standard Deviation. Aspen criterion is one half of Tonks level, thus representing 12.5% of normal range. To reach SIX SIGMA 6S level, it is necessary to improve Tonks level six times, which implies reducing Analytical Variability to 4.2% of Biological Variability. To evaluate relation between Biological Variability BV and Analytical Variability AV, it is recommended to calculate AV/BV ratio, which will result <1.0 according to Tonks, <0.50 according to Aspen and <0.17 when SIX SIGMA 6S level is achieved. Discussion: Establishing attainable and challenging goals is first step in any AQCS Analytical Quality Control System. RCV Relative Coefficient of Variation calculation allows the integration of Medical Relevance, Biological Variation and Technology through a reliable and easy approach for any measurand with the only condition of having suitable reference limits for attended population and calculation of ACV Analytical Coefficient of Variation for each test. Continuous Quality Improvement CQI depends on understanding actual level in which laboratory is performing. In order to improve it is necessary to establish a formal WWWWH Strategic Plan, to enhance laboratory practices and to develop technology under Quality Management System QMS in order not to depend only on automation. 

Keywords

clinical laboratories, biological variability, analytical performance specifications, quality health care