Using clinical guidelines to assess the potential value of laboratory medicine in clinical decision-making

La gestión de la demanda de las pruebas: un reto en el nuevo modelo de medicina de laboratorio

Introducción

En las últimas décadas está evolucionando el posicionamiento de la Medicina de Laboratorio en el proceso médico asistencial de atención al paciente y también el modelo de laboratorio; de un modelo tradicional, con solo intervención, a un modelo líder, que además de intervenir condiciona la decisión clínica. La mejora en tecnología y automatización ha permitido también al profesional de laboratorio centrarse en la primera y última fase del ciclo de laboratorio, la solicitud de pruebas, y la acción tras su resultado, las etapas con más errores, y donde principalmente se debe actuar para conseguir una mejora en la calidad asistencial del paciente.

Contenido

Se muestra el diseño y la implantación de intervenciones de gestión de la demanda de pruebas de laboratorio, logrando el diagnóstico de la enfermedad oculta, y mejorando la adherencia a las guías clínicas y la seguridad del paciente.

Resumen

Se expondrán los puntos clave en el proceso de gestión de la demanda, tanto de exceso como de defecto.

Perspectivas

El objetivo de la revisión es lograr que el profesional del laboratorio se involucre en el diseño e implantación de intervenciones de gestión de la demanda y en la creación de ese nuevo modelo de Laboratorio Líder.

Managing laboratory test ordering: a challenge in the new laboratory medicine model

Introduction

The role of Laboratory Medicine in patient care has evolved in the last decades. The same has occurred to the laboratory model, which has evolved from a traditional model where the laboratory is merely involved in clinical decision-making to a leading model where the laboratory is not only involved but also determines decision-making. The advent of new technologies and automation of processes have enabled laboratory professionals to focus on the first and last phase of the analytical process namely, test ordering and decision-making based on laboratory results. These phases are more error-prone than the analytical phase, and where action must be taken to improve the quality of patient care.

Content

We share our experience in the design and establishment of laboratory test demand management interventions that facilitated diagnosis of occult disease, improved adherence to clinical guidelines, and optimized patient safety.

Summary

A description is provided of key points in the management of laboratory test over/underutilization.

Outlook

The objective of this review is to promote the involvement of laboratory professionals in the design and implementation of demand management interventions and in the development of the new Leader Laboratory model.

Assessment of accuracy of laboratory testing results, relative to peer group consensus values in external quality control, by bivariate z-score analysis: the example of D-Dimer

OBJECTIVES

The aim of this study is to develop a practical method for bivariate z-score analysis which can be applied to the survey of an external quality assessment programme.

METHODS

To develop the bivariate z-score analysis, the results of four surveys of the international D-Dimer external quality assessment programme of 2022 of the ECAT Foundation were used. The proposed methodology starts by identifying the bivariate outliers, using a Supervised Sequential Hotelling T2 control chart. The outlying data are removed, and all the remaining data are used to provide robust estimates of the parameters of the assumed underlying bivariate normal distribution. Based on these estimates two nested homocentric ellipses are drawn, corresponding to confidence levels of 95 and 99.7 %. The bivariate z-score plot described provides the laboratory with an indication of both systematic and random deviations from zero z-score values. The bivariate z-score analysis was examined within survey 2022-D4 across the three most frequently used methods.

RESULTS

The number of z-score pairs included varied between 830 and 857 and the number of bivariate outliers varied between 20 and 28. The correlation between the z-score pairs varied between 0.431 and 0.647. The correlation between the z-score pairs for the three most frequently used varied between 0.208 and 0.636.

CONCLUSIONS

The use of the bivariate z-score analysis is of major importance when multiple samples are distributed around in the same survey and dependency of the results is likely. Important lessons can be drawn from the shape of the ellipse with respect to random and systematic deviations, while individual laboratories have been informed about their position in the state-of-the-art distribution and whether they have to deal with systematic and/or random deviations.

Bias in Laboratory Medicine: The Dark Side of the Moon

Physicians increasingly use laboratory-produced information for disease diagnosis, patient monitoring, treatment planning, and evaluations of treatment effectiveness. Bias is the systematic deviation of laboratory test results from the actual value, which can cause misdiagnosis or misestimation of disease prognosis and increase healthcare costs. Properly estimating and treating bias can help to reduce laboratory errors, improve patient safety, and considerably reduce healthcare costs. A bias that is statistically and medically significant should be eliminated or corrected. In this review, the theoretical aspects of bias based on metrological, statistical, laboratory, and biological variation principles are discussed. These principles are then applied to laboratory and diagnostic medicine for practical use from clinical perspectives.

Drug interference with biochemical laboratory tests

Clinical laboratory practice represents an essential part of clinical decision-making, as it influences 60-70% of medical decisions at all levels of health care. Results of biochemical laboratory tests (BLTs) have a key role in establishment of adequate diagnosis as well as in evaluation of treatment progress and outcome. The prevalence of drug-laboratory test interactions (DLTIs) is up to 43% of patients who had laboratory results influenced by drugs. Unrecognized DLTIs may lead to misinterpreted BLTs results, incorrect or delayed diagnosis, extra costs for unnecessary additional tests or inadequate therapy, as all may cause false clinical decisions. The significance of timely and adequate recognition of DLTIs is to prevent common clinical consequences such as incorrectly interpreted test results, delayed or non-treated condition due to erroneous diagnosis or unnecessary extra tests or therapy. Medical professionals should be educated that it is essential to obtain patient data about medications especially for the drugs used in the last 10 days before biological material collection. Our mini-review aims to provide a comprehensive overview of the current state in this important domain of medical biochemistry with detailed analysis of the effect of drugs on BLTs and to give detailed information to medical specialists.

Lot-to-lot reagent verification: challenges and possible solutions

Lot-to-lot verification is an important laboratory activity that is performed to monitor the consistency of analytical performance over time. In this opinion paper, the concept, clinical impact, challenges and potential solutions for lot-to-lot verification are exained.