Quality Control of Laboratory Medicine: Preventing Errors for Diagnostic Reliability

Quality assurance (QA) of laboratory medicine is vital for diagnostic reliability and patient safety. Laboratory test errors can lead to misdiagnoses, inappropriate therapy or treatments, and unwanted outcomes. This systematic review discusses and integrates quality laboratory medicine error prevention in the context of diagnostic reliability, based on 46 peer-reviewed articles. It discusses the preanalytical, analytical, and post-analytical phases of error prevention based on the nature, source, and ways to avoid errors, different QA models, approaches with new technology, a variety of ways to train or educate, and continuous improvement. The laboratory medicine errors are routine: wrong sample, analytical errors, and wrong result, and the inclusion of preanalytical errors causes the majority of errors (preanalytical errors are as high as 70%). QA models (for example, ISO 15189) offer an all-encompassing model; newer technological approaches (automation, artificial intelligence, etc.) offer an alternative with increased accuracy. The technical impediments to implementing quality management systems to prevent errors and monitor quality are scarce resources and a lack of educational/ training experience, and experience makes it more difficult for lower-resource centers or settings. Some recommendations include: effective management, testing protocols that are standardized, external quality assessment, and interprofessional working. The priorities for future agendas are considering new technology as it evolves, international harmonization of standards (decreased variability), and reducing inequities in access to laboratory testing. The review provides evidence for quality assurance systems that will lead to error reduction, diagnostically dependable outcomes, and outcome maximization for patients, with the result being quality improvement for the delivered healthcare will be laboratory professionals