Strategies for the successful implementation of viral laboratory automation.

It has been estimated that more than 70% of all medical activity is directly related to information providing analytical data. Substantial technological advances have taken place recently, which have allowed a previously unimagined number of analytical samples to be processed while offering high quality results. Concurrently, yet more new diagnostic determinations have been introduced - all of which has led to a significant increase in the prescription of analytical parameters. This increased workload has placed great pressure on the laboratory with respect to health costs. The present manager of the Clinical Laboratory (CL) has had to examine cost control as well as rationing - meaning that the CL's focus has not been strictly metrological, as if it were purely a system producing results, but instead has had to concentrate on its efficiency and efficacy. By applying re-engineering criteria, an emphasis has had to be placed on improved organisation and operating practice within the CL, focussing on the current criteria of the Integrated Management Areas where the technical and human resources are brought together. This re-engineering has been based on the concepts of consolidating and integrating the analytical platforms, while differentiating the production areas (CORE Laboratory) from the information areas. With these present concepts in mind, automation and virological treatment, along with serology in general, follow the same criteria as the rest of the operating methodology in the Clinical Laboratory.

Infornut® Process; improves accessibility to diagnosis and nutritional support for the malnourished hospitalized patient; impact on management indicators; two-year assessment.

Introduction: The high prevalence of disease-related hospital malnutrition justifies the need for screening tools and early detection in patients at risk for malnutrition, followed by an assessment targeted towards diagnosis and treatment. At the same time there is clear undercoding of malnutrition diagnoses and the procedures to correct it Objectives: To describe the INFORNUT program/ process and its development as an information system. To quantify performance in its different phases. To cite other tools used as a coding source. To calculate the coding rates for malnutrition diagnoses and related procedures. To show the relationship to Mean Stay, Mortality Rate and Urgent Readmission; as well as to quantify its impact on the hospital Complexity Index and its effect on the justification of Hospitalization Costs. Material and methods: The INFORNUT® process is based on an automated screening program of systematic detection and early identification of malnourished patients on hospital admission, as well as their assessment, diagnoses, documentation and reporting. Of total readmissions with stays longer than three days incurred in 2008 and 2010, we recorded patients who underwent analytical screening with an alert for a medium or high risk of malnutrition, as well as the subgroup of patients in whom we were able to administer the complete INFORNUT® process, generating a report for each.