Laboratory services are the backbone of the modern health care sector. Effective laboratory service is the amalgamation of precision, accuracy, and speed of reports delivered to the patient. In spite of rapid advances in laboratory science, it is still susceptible to various manual and systemic errors. Various types of errors that we, as clinical biochemists, encounter in the laboratory are classified as preanalytical, analytical, and postanalytical, depending upon the time of presentation. The preanalytical phase is an important component of laboratory medicine [1]. It includes specimen collection, handling and processing variables, physiological variables, and endogenous variables. Some of the preanalytical variables such as specimen variables can be controlled, while knowledge of uncontrollable variables need to be well understood in order to be able to separate their effects from disease related changes affecting laboratory results.Most errors affecting laboratory test results occur in the preanalytical phase, primarily because of the difficulty in achieving standardized procedures for sample collection. Errors occurring during the preanalytical phase-from the time the test is ordered by the physician until the sample is ready for analysis-can account for up to 70 % of the errors currently encountered during the total diagnostic process [2]. Errors at any stage of the collection, testing, and reporting process can potentially lead to a serious patient misdiagnosis. Overall, insufficient specimen quality and quantity may account for over 60 % of preanalytical errors [3]. The human role in sample collection makes complete elimination of errors associated with laboratory testing unrealistic. Preanalytical errors are largely attributable to human mistakes [4] and the majority of these errors are preventable [5,6]. This is understandable, since the preanalytical phase involves much more human handling, compared to the analytical and postanalytical phases. The total uncertainty in the test result due to preanalytical reasons can be calculated [7]. For example, differences in preanalytical procedures can explain up to 41 % of the variation of prevalence of hypercholesterolemia [8].
Types of Errors and Their Rectification