Quality indicators (QIs) are key tools for improving the quality of laboratory services, by reducing error rates and safeguarding patient safety. A body of accumulated evidence confirms the relevance of QIs and their impact on the overall quality of laboratory information. The consensus achieved on a list of "harmonized" QIs, along with the system used for data collection and reporting throughout an international benchmarking programme, has enabled achieving realistic performance targets, based on knowledge of the state-of-the-art. Data collected in 2017 and 2018 have been analyzed and performance measures obtained by laboratories participating in the project are summarized in the present article. The laboratory performance measures have been classified into three levels (optimum, desirable or minimum) in agreement with the widely accepted model of analytical quality specifications.

Quality indicators (QIs) are fundamental tools for enabling users to quantify the quality of all operational processes by comparing it against a defined criterion. QIs data should be collected over time to identify, correct, and continuously monitor defects and improve performance and patient safety by identifying and implementing effective interventions. According to the international standard for medical laboratories accreditation, the laboratory shall establish and periodically review QIs to monitor and evaluate performance throughout critical aspects of pre-, intra-, and post-analytical processes. However, while some interesting programs on indicators in the total testing process have been developed in some countries, there is no consensus for the production of joint recommendations focusing on the adoption of universal QIs and common terminology in the total testing process. A preliminary agreement has been achieved in a Consensus Conference organized in Padua in 2013, after revising the model of quality indicators (MQI) developed by the Working Group on "Laboratory Errors and Patient Safety" of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). The consensually accepted list of QIs, which takes into consideration both their importance and applicability, should be tested by all potentially interested clinical laboratories to identify further steps in the harmonization project.

Abstract Background: The adoption of Quality Indicators (QIs) has prompted the development of tools to measure and evaluate the quality and effectiveness of laboratory testing, first in the hospital setting and subsequently in ambulatory and other care settings. While Laboratory Medicine has an important role in the delivery of high-quality care, no consensus exists as yet on the use of QIs focussing on all steps of the laboratory total testing process (TTP), and further research in this area is required. Methods: In order to reduce errors in laboratory testing, the IFCC Working Group on “Laboratory Errors and Patient Safety” (WG-LEPS) developed a series of Quality Indicators, specifically designed for clinical laboratories. In the first phase of the project, specific QIs for key processes of the TTP were identified, including all the pre-, intra- and post-analytic steps. The overall aim of the project is to create a common reporting system for clinical laboratories based on standardized data collection, and to define state-of-the-art and Quality Specifications (QSs) for each QI independent of: a) the size of organization and type of activities; b) the complexity of processes undertaken; and c) different degree of knowledge and ability of the staff. The aim of the present paper is to report the results collected from participating laboratories from February 2008 to December 2009 and to identify preliminary QSs. Results and conclusions: The results demonstrate that a Model of Quality Indicators managed as an External Quality Assurance Program can serve as a tool to monitor and control the pre-, intra- and post-analytical activities. It might also allow clinical laboratories to identify risks that lead to errors resulting in patient harm: identification and design of practices that eliminate medical errors; the sharing of information and education of clinical and laboratory teams on practices that reduce or prevent errors; the monitoring and evaluation of improvement activities.