22 research outputs found

    Statistical distributions commonly used in measurement uncertainty in laboratory medicine

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    Uncertainty is an inseparable part of all types of measurement. Recently, the International Organization for Standardization (ISO) released a new standard (ISO 20914) on how to calculate measurement uncertainty (MU) in laboratory medicine. This standard can be regarded as the beginning of a new era in laboratory medicine. Measurement uncertainty comprises various components and is used to calculate the total uncertainty. All components must be expressed in standard deviation (SD) and then combined. However, the characteristics of these components are not the same; some are expressed as SD, while others are expressed as a ± b, such as the purity of the reagents. All non-SD variables must be transformed into SD, which requires a detailed knowledge of common statistical distributions used in the calculation of MU. Here, the main statistical distributions used in MU calculation are briefly summarized

    Sigma metrics in laboratory medicine revisited: We are on the right road with the wrong map

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    Reliable procedures are needed to quantify the performance of instruments and methods in order to increase the quality in clinical laboratories. The Sigma metrics serves that purpose, and in the present study, the current methods for the calculation of the Sigma metrics are critically evaluated. Although the conventional model based on permissible (or allowable) total error is widely used, it has been shown to be flawed. An alternative method is proposed based on the within-subject biological variation. This model is conceptually similar to the model used in industry to quantify measurement performance, based on the concept of the number of distinct categories and consistent with the Six Sigma methodology. The quality of data produced in clinical laboratories is expected, however, to be higher than the quality of industrial products. It is concluded that this model is consistent with Six Sigma theory, original Sigma metrics equation and with the nature of patients’ samples. Therefore, it can be used easily to calculate the performance of measurement methods and instruments used in clinical laboratories

    Why are clinical practice guidelines not followed?

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    Clinical practice guidelines (CPG) are written with the aim of collating the most up to date information into a single document that will aid clinicians in providing the best practice for their patients. There is evidence to suggest that those clinicians who adhere to CPG deliver better outcomes for their patients. Why, therefore, are clinicians so poor at adhering to CPG? The main barriers include awareness, familiarity and agreement with the contents. Secondly, clinicians must feel that they have the skills and are therefore able to deliver on the CPG. Clinicians also need to be able to overcome the inertia of "normal practice" and understand the need for change. Thirdly, the goals of clinicians and patients are not always the same as each other (or the guidelines). Finally, there are a multitude of external barriers including equipment, space, educational materials, time, staff, and financial resource. In view of the considerable energy that has been placed on guidelines, there has been extensive research into their uptake. Laboratory medicine specialists are not immune from these barriers. Most CPG that include laboratory tests do not have sufficient detail for laboratories to provide any added value. However, where appropriate recommendations are made, then it appears that laboratory specialist express the same difficulties in compliance as front-line clinicians

    Could accreditation bodies facilitate the implementation of medical guidelines in laboratories?

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    Several studies have shown that recommendations related to how laboratory testing should be performed and results interpreted are limited in medical guidelines and that the uptake and implementation of the recommendations that are available need improvement. The EFLM/UEMS Working Group on Guidelines conducted a survey amongst the national societies for clinical chemistry in Europe regarding development of laboratory-related guidelines. The results showed that most countries have guidelines that are specifically related to laboratory testing; however, not all countries have a formal procedure for accepting such guidelines and few countries have guideline committees. Based on this, the EFLM/UEMS Working Group on Guidelines conclude that there is still room for improvement regarding these processes in Europe and raise the question if the accreditation bodies could be a facilitator for an improvement

    Critical review of laboratory investigations in clinical practice guidelines : proposals for the description of investigation

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    Background: Correct information provided by guidelines may reduce laboratory test related errors during the pre-analytical, analytical and post-analytical phase and increase the quality of laboratory results. Methods: Twelve clinical practice guidelines were reviewed regarding inclusion of important laboratory investigations. Based on the results and the authors' experience, two checklists were developed: one comprehensive list including topics that authors of guidelines may consider and one consisting of minimal standards that should be covered for all laboratory tests recommended in clinical practice guidelines. The number of topics addressed by the guidelines was related to involvement of laboratory medicine specialists in the guideline development process. Results: The comprehensive list suggests 33 pre-analytical, 37 analytical and 10 post-analytical items. The mean percentage of topics dealt with by the guidelines was 33% (median 30%, range 17%-55%) and inclusion of a laboratory medicine specialist in the guideline committee significantly increased the number of topics addressed. Information about patient status, biological and analytical interferences and sample handling were scarce in most guidelines even if the inclusion of a laboratory medicine specialist in the development process seemingly led to increased focus on, e.g., sample type, sample handling and analytical variation. Examples underlining the importance of including laboratory items are given. Conclusions: Inclusion of laboratory medicine specialist in the guideline development process may increase the focus on important laboratory related items even if this information is usually limited. Two checklists are suggested to help guideline developers to cover all important topics related to laboratory testing

    Reflective testing – A randomized controlled trial in primary care patients

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    Background: Reflective testing, i.e. interpreting, commenting on and, if necessary, adding tests in order to aid the diagnostic process in a meaningful and efficient manner, is an extra service provided by laboratory medicine. However, there have been no prospective randomized controlled trials investigating the value of reflective testing in patient management. Methods: In this trial, primary care patients were randomly allocated to an intervention group, where general practitioners received laboratory tests results as requested as well as add-on test results with interpretative comments where considered appropriate by the laboratory specialist, or to a control group, where general practitioners only received the laboratory test results requested. Patients’ medical records were evaluated with a follow-up period of six months. For both groups, the primary outcome measures, i.e. both intended action and actual management action, were blindly assessed by an independent expert panel as adequate, neutral or inadequate. Results: In 226 of the 270 cases (84%), reflective testing was considered to be useful for the patient. In the intervention group (n = 148), actual management by the general practitioner was scored as adequate (n = 104; 70%), neutral (n = 29; 20%) or not adequate (n = 15; 10%). In the control group (n = 122), these numbers were 57 (47%), 37 (30%) and 28 (23%). This difference was statistically significant (P < 0.001). Conclusion: This randomized controlled trial showed a positive effect of reflective testing in primary care patients on the adequacy of their management, as documented in medical records

    Mini Review Why are clinical practice guidelines not followed?

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    Abstract: Clinical practice guidelines (CPG) are written with the aim of collating the most up to date information into a single document that will aid clinicians in providing the best practice for their patients. There is evidence to suggest that those clinicians who adhere to CPG deliver better outcomes for their patients. Why, therefore, are clinicians so poor at adhering to CPG? The main barriers include awareness, familiarity and agreement with the contents. Secondly, clinicians must feel that they have the skills and are therefore able to deliver on the CPG. Clinicians also need to be able to overcome the inertia of &quot;normal practice&quot; and understand the need for change. Thirdly, the goals of clinicians and patients are not always the same as each other (or the guidelines). Finally, there are a multitude of external barriers including equipment, space, educational materials, time, staff, and financial resource. In view of the considerable energy that has been placed on guidelines, there has been extensive research into their uptake. Laboratory medicine specialists are not immune from these barriers. Most CPG that include laboratory tests do not have sufficient detail for laboratories to provide any added value. However, where appropriate recommendations are made, then it appears that laboratory specialist express the same difficulties in compliance as front-line clinicians

    The use of error and uncertainty methods in the medical laboratory.

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    Error methods - compared with uncertainty methods - offer simpler, more intuitive and practical procedures for calculating measurement uncertainty and conducting quality assurance in laboratory medicine. However, uncertainty methods are preferred in other fields of science as reflected by the guide to the expression of uncertainty in measurement. When laboratory results are used for supporting medical diagnoses, the total uncertainty consists only partially of analytical variation. Biological variation, pre- and postanalytical variation all need to be included. Furthermore, all components of the measuring procedure need to be taken into account. Performance specifications for diagnostic tests should include the diagnostic uncertainty of the entire testing process. Uncertainty methods may be particularly useful for this purpose but have yet to show their strength in laboratory medicine. The purpose of this paper is to elucidate the pros and cons of error and uncertainty methods as groundwork for future consensus on their use in practical performance specifications. Error and uncertainty methods are complementary when evaluating measurement data
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