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Resumen Introduccion El objetivo del trabajo es mostrar y analizar los resultados de errores preanaliticos en las muestras de laboratorio remitidas desde atencion primaria a 7 laboratorios de la Comunidad Valenciana que atienden a 7 departamentos de salud. Material y metodos Se realizo un estudio transversal mediante la evaluacion y el analisis de los errores preanaliticos de 7 laboratorios. El error preanalitico se definio como muestra que no puede ser analizada por no cumplir los criterios de aceptabilidad o que no se recibe en el laboratorio. Se disenaron indicadores de proporcion que cuantifican cada incidencia respecto al total de cada muestra (hematologia, coagulacion, bioquimica y orina). Los errores preanaliticos y las muestras se recogieron automaticamente del Sistema de Informacion del Laboratorio, y tambien se calcularon los indicadores a tiempo real mediante un software basado en data warehouse y cubos OLAP. Resultados La variabilidad de los resultados entre los diferentes centros fue elevada, evidenciandose que el mayor porcentaje de incidencias se debio a la falta de disponibilidad de las muestras, en especial de coagulacion y de orina. Conclusiones Existe una gran variabilidad de errores preanaliticos dependiendo del Departamento de Salud. Existe una necesidad de homogeneizar la practica de la extraccion de muestras.

Purpose To show turnaround time to client source in eight laboratories covering eight Health Areas (2,014,475 inhabitants) of the Valencian Community (Spain). Material and methods Internal Laboratory Information System (LIS) registers (test register and verification date and time), and daily LIS registers were used to design the indicators, These indicators showed the percentage of key tests requested (full blood count and serum glucose and thyrotropin) that were validated on the same day the blood was taken (inpatients and Primary Care and/or at 12 a.m. (inpatients). Urgent (stat) tests were also registered as key tests (serum troponin and potassium) and were recorded in minutes. Registers were collected and indicators calculated automatically through a Data Warehouse application and OLAP cube software. Results Long turnaround time differences were observed at 12 a.m. in inpatients, and in the day of sample extraction in primary care patients. The variability in turnaround of stat tests is related to hospital size, activity and validation by the laboratory physician. Conclusions The study results show the large turnaround time disparity in eight Health Care Areas of Valencian Community. The various requesting sources covered by the laboratories create the need for continuous mapping processes redesign and benchmarking studies to achieve customer satisfaction.