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Clin Chem Lab Med ; 42(6): 578-82, 2004.
Artigo em Inglês | MEDLINE | ID: mdl-15259371

RESUMO

BACKGROUND: Quality management systems should cover all the steps involved in the overall testing and non-testing processes. AIM: To identify quality indicators for extra-analytical processes in the clinical laboratory and to specify acceptability limits, in order to provide a useful tool for continuous improvement of laboratory service. METHODS: A literature review by Medline search was performed using the keywords: Q-Tracks and Q-probes alone, and management, error, mistake, and indicator crossed with quality, laboratory and medicine. The indicators retrieved were organized according to the various laboratory processes. Their expression was standardized in relation to the total activity of each process reported in each paper reviewed. The magnitude of the errors reported was considered to be the current state of the art for the extra-analytical step and was proposed as the quality specification. RESULTS: Examples of indicators and specifications for the pre-analytical process: Analytical request: Error in patient identification (0.08%), request unintelligible (0.1%). SAMPLING: Requested but not collected (7%), redraws (2%). Transport and reception of samples: Inadequate transportation conditions (0.005%), hemolyzed sample (0.2%). Examples of indicators and specifications for the post-analytical process: Report validation: Test not performed (1.4%), test performed but not requested (1.1%). Intra-laboratory reports: Laboratory reporting errors (0.05%), delivery outside specified time (11%). Consulting service: average time to communicate critical values for inpatients (6 min). CONCLUSIONS: These extra-analytical indicators and their specifications, expressed in a standardized manner, constitute a preliminary basis for comparison of individual laboratory performance with the purpose of improving laboratory quality.


Assuntos
Técnicas de Laboratório Clínico/normas , Laboratórios/normas , Indicadores de Qualidade em Assistência à Saúde , Erros de Diagnóstico , Humanos , Laboratórios/organização & administração , Sistemas Computadorizados de Registros Médicos , Controle de Qualidade
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