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Background The clinical laboratory plays a crucial role in the diagnosis and monitoring of chronic kidney disease. The quantitative measurement of urine albumin in a spot sample, expressed as ratio per creatinine (ACR) is the most frequently used biomarker for such a purpose. Our aim was to evaluate the diagnostic performances of a strip for measuring ACR for differentiating patients who are candidates for subsequent albumin quantification, and to evaluate the economic effects of its implementation. Methods We systematically measured strip analysis when quantitative urinary albumin was requested. Semiquantitative urinary albumin was measured using a UC-3500 (Sysmex, Kobe, Japan), based on the protein error of a pH indicator. We collected and reviewed all the values of quantified urinary albumin and their corresponding results in ACR strip tests. We calculated the diagnostic indicators for ACR at different albumin and creatinine values using the quantitative ACR measurement as a "gold standard". We also studied the economic effects based on both tests prices (€1.31 for quantitative albumin plus creatinine, and €0.04 for an albumin strip). Results The study included 9148 patients (mean age 63, 46.3% men). The results at different albumin and creatinine cutoffs showed the best performance when 10 mg/L and above 50 mg/dL, respectively. Based on our results, we would have saved 3506 urine albumin and creatinine tests in the study period, corresponding to €4226.94. Conclusions The present study supports the use of the ACR strip test to identify pathological albuminuria values to be measured through quantitative methods. Considerable economic savings are possible.

Background: Severe vitamin B12 deficiency can result in serious complications if undiagnosed or untreated. Our aim was to test the efficacy of interventions in the laboratory process to improve the detection and the treatment of severe vitamin B12 deficiency., Methods: Quasi-experimental investigation with a retrospective 7-year pre-intervention period and 29-month post-intervention follow-up in a university hospital. Two interventions were designed to improve the detection and treatment of subjects with vitamin B12 deficiency: the laboratory information system (LIS) automatically added seru vitamin B12 (s-vitamin B12) based on certain conditions; and created a comment in the report and scheduled an appointment with the general practitioner (GP). We calculated the number of new diagnoses of severe vitamin deficiency (s-vitamin B12 <73.8 pmol/L) and the proportion of identified patients that were correctly treated in the pre- and post-intervention periods. We compared the number of tests needed to detect a new case when ordered by GPs vs. added by the strategy. Finally, we investigated the economic cost of each new case., Results: The strategy added 699 s-vitamin B12 and detected 66 new cases of severe vitamin deficiency. The number of tests needed to identify a new case when s-vitamin B12 was ordered by GPs was 187, as opposed to 10 when added through the intervention (p<0.001). The intervention reagent cost was €26.7 per new case. In the post-intervention cohort, 88% of patients were correctly treated, as opposed to 52% in the pre-intervention (p<0.001)., Conclusions: Interventions in the clinical laboratory process improved the diagnosis and treatment of severe vitamin B12 deficiency.

Background: One of the main duties of healthcare workers is to get an appropriate use of diagnostic and therapeutic tools. The aim of this study was to show how strategies can be designed and established in consensus with general practitioners (GPs) to reach an optimal laboratory test request., Methods: The laboratory serves a population of approximately 235,000 inhabitants, including nine primary care centers. GPs could request every test in profiles and individually. In meetings between the laboratory and GPs our request patterns were compared to other geographic regions, and we investigated the appropriateness of test requesting. The group devised strategies that consisted of removing tests from profiles [aspartate aminotransferase (AST), γ-glutamyltranspeptidase (GGT) and phosphate], removing tests from GPs requests (iron and transferrin), substituting tests (IgA antigliadin antibody), and measuring total bilirubin (tBil) only when the icteric index value was above 34.2 mmol/L (2 mg/dL). We analyzed every test request in the post- (years 2012-2013) and pre-intervention period (years 2010-2011), and the tBil measured in the post-intervention period. We studied if AST/alanine aminotransferase (ALT) and GGT/ALT achieved indicators targets and calculated the economic savings in the post-intervention period., Results: There was a significant drop in every test request in the post-intervention period. AST/ALT achieved the indicator target. GGT/ALT, never achieved the indicator goal. The strategies resulted in a savings of more than €34,000., Conclusions: The strategies designed between the laboratory and the requesting clinicians and automatically established by using our laboratory information system were successful.

Background: Laboratory performance can be measured using a set of model key performance indicators (KPIs). The design and implementation of KPIs are important issues. KPI results from 7 years are reported and their implementation, monitoring, objectives, interventions, result reporting and delivery are analyzed., Methods: The KPIs of the entire laboratory process were obtained using Laboratory Information System (LIS) registers. These were collected automatically using a data warehouse application, spreadsheets and external quality program reports. Customer satisfaction was assessed using surveys. Nine model laboratory KPIs were proposed and measured., Results: The results of some examples of KPIs used in our laboratory are reported. Their corrective measurements or the implementation of objectives led to improvement in the associated KPIs results., Conclusions: Measurement of laboratory performance using KPIs and a data warehouse application that continuously collects registers and calculates KPIs confirmed the reliability of indicators, indicator acceptability and usability for users, and continuous process improvement.