Quality control in the Netherlands; todays practices and starting points for guidance and future research.

OBJECTIVES: Adequate analytical quality of reported results is primarily ensured by performing internal quality control (iQC). Currently, several different iQC practices are in use. As a prelude to the revision of a Dutch guidance document on analytical QC, a questionnaire was sent out to gain insights in the applied practices and the need for guidance. METHODS: A questionnaire, containing 20 multiple-choice questions with possibilities for explanation and comment on iQC practices and aspects was distributed to all clinical chemistry laboratories within the Netherlands. Results were reported descriptively. RESULTS: Responses were received from 27 clinical laboratories (response 43 %). In 30 % the iQC was based on the analytical characteristics only, while 30 % used a 6-Sigma method, 19 % risk-based beyond 6-Sigma and 22 % used an alternative approach. 89 % of laboratories used a virtual analyzer model for iQC setup within one or more laboratory sites. Practices for determining standard deviation (SD) values included determining SD for each new iQC material (35 %), using historical SD values for new materials (35 %), and incorporating clinical tolerances into the SD value (31 %). Furthermore, 44 % of laboratories used patient moving averages for one or more tests. Daily iQC management was based on either "traffic lights" indicating in or out of control status, and review of all QC charts, often using multiple software systems. CONCLUSIONS: A large heterogeneity of iQC practices in clinical laboratories was observed in the Netherlands. Several starting points for further research and/or guidance were identified, particularly in relation to the determination of SD values, the virtual analyzer model and methods to ensure analyzer equivalence.

Performance specifications for sodium should not be based on biological variation.

When increasing the quality in clinical laboratories by decreasing measurement uncertainty, reliable methods are needed not only to quantify the performance of measuring systems, but also to set goals for the performance. Sigma metrics used in medical laboratories for documenting and expressing levels of performance, are evidently totally dependent on the "total permissible error" used in the formulas. Although the conventional biological variation (BV) based model for calculation of the permissible (or allowable) total error is commonly used, it has been shown to be flawed. Alternative methods are proposed, mainly also based on the within-subject BV. Measurement uncertainty models might offer an alternative to total error models. Defining the limits for analytical quality still poses a challenge in both models. The aim of the present paper is to critically discuss current methods for establishing performance specifications by using the measurement of sodium concentrations in plasma or serum. Sodium can be measured with high accuracy but fails by far to meet conventional performance specifications based on BV. Since the use of sodium concentrations is well established for supporting clinical care, we question the concept that quality criteria for sodium and similar analytes that are under strict homeostatic control are best set by biology.

ISO 15189 is a sufficient instrument to guarantee high-quality manufacture of laboratory developed tests for in-house-use conform requirements of the European In-Vitro-Diagnostics Regulation.

The EU In-Vitro Diagnostic Device Regulation (IVDR) aims for transparent risk-and purpose-based validation of diagnostic devices, traceability of results to uniquely identified devices, and post-market surveillance. The IVDR regulates design, manufacture and putting into use of devices, but not medical services using these devices. In the absence of suitable commercial devices, the laboratory can resort to laboratory-developed tests (LDT) for in-house use. Documentary obligations (IVDR Art 5.5), the performance and safety specifications of ANNEX I, and development and manufacture under an ISO 15189-equivalent quality system apply. LDTs serve specific clinical needs, often for low volume niche applications, or correspond to the translational phase of new tests and treatments, often extremely relevant for patient care. As some commercial tests may disappear with the IVDR roll-out, many will require urgent LDT replacement. The workload will also depend on which modifications to commercial tests turns them into an LDT, and on how national legislators and competent authorities (CA) will handle new competences and responsibilities. We discuss appropriate interpretation of ISO 15189 to cover IVDR requirements. Selected cases illustrate LDT implementation covering medical needs with commensurate management of risk emanating from intended use and/or design of devices. Unintended collateral damage of the IVDR comprises loss of non-profitable niche applications, increases of costs and wasted resources, and migration of innovative research to more cost-efficient environments. Taking into account local specifics, the legislative framework should reduce the burden on and associated opportunity costs for the health care system, by making diligent use of existing frameworks.

Measurement uncertainty for practical use.

Uncertainty is an inseparable part of all kinds of measurements performed in clinical laboratories. Accreditation standards including the ISO/IEC 17025:2017 and ISO 15189:2012 require that laboratories have routines for calculating the measurement uncertainty of reported results. Various guidelines such as CLSI EP29, Nordest 537, and ISO 20914:2019 have proposed methods for this purpose. However, due to the conceived complexity of the proposed calculation methods, these guidelines have not been generally and effectively applied in clinical laboratories. High workload and measurand heterogeneity favor a pragmatic utilitarian approach. The purpose of this paper is to describe such an approach, including its advantages and disadvantages. Measurement uncertainty should include the most influential factors affecting patients' test results. Since patients' samples for the same measurand can be analyzed in one laboratory or several laboratories using different measuring systems, the measurement uncertainty should be calculated using results obtained from analyzing the same internal quality control material if commutable or patients pooled/split samples.

Awareness of drug laboratory test interactions is important for prevention of unnecessary additional diagnostics: An example.

BACKGROUND: Elevated levels of Chromogranin A (CgA) may be indicative of a neuroendocrine tumour (NET), but increased levels are also observed after intake of proton pump inhibitors (PPIs). The incidence of diagnostic confusion because of this drug-laboratory test interaction (DLTI) was examined. METHODS: Medical records of 238 patients with elevated CgA concentrations were obtained from three hospitals. The following data were extracted: PPI prescription at the time of CgA measurement, medical decision making based on elevated CgA concentrations, final diagnosis, comorbidity and other prescribed drugs. RESULTS: From 238 patients with elevated CgA concentrations, 132 used PPIs. Of these patients, 57 patients did not have a NET. In 9 of these 57 patients (16%), diagnostic work up revealed no medical cause of an elevated CgA concentration. Somatostatin receptor imaging was ordered in 4 out of 9 cases, with no abnormalities observed. In 6 out of 9 cases, CgA measurement was repeated after PPI discontinuation resulting in normalisation of CgA concentrations. CONCLUSION: In this retrospective patient record study we observed that part of the elevated CgA concentrations in patients could be caused by the usage of PPIs causing unnecessary diagnostic work-up for the exclusion of a NET. These observations illustrate the need for better DLTI awareness.

Real-time monitoring of drug laboratory test interactions: a proof of concept.

OBJECTIVES: For the correct interpretation of test results, it is important to be aware of drug-laboratory test interactions (DLTIs). If DLTIs are not taken into account by clinicians, erroneous interpretation of test results may lead to a delayed or incorrect diagnosis, unnecessary diagnostic testing or therapy with possible harm for patients. A DLTI alert accompanying a laboratory test result could be a solution. The aim of this study was to test a multicentre proof of concept of an electronic clinical decision support system (CDSS) for real-time monitoring of DLTIs. METHODS: CDSS was implemented in three Dutch hospitals. So-called 'clinical rules' were programmed to alert medical specialists for possible DLTIs based on laboratory test results outside the reference range in combination with prescribed drugs. A selection of interactions from the DLTI database of the Dutch society of clinical chemistry and laboratory medicine were integrated in 43 clinical rules, including 24 tests and 25 drugs. During the period of one month all generated DTLI alerts were registered in the laboratory information system. RESULTS: Approximately 65 DLTI alerts per day were detected in each hospital. Most DLTI alerts were generated in patients from the internal medicine and intensive care departments. The most frequently reported DLTI alerts were potassium-proton pump inhibitors (16%), potassium-beta blockers (11%) and creatine kinase-statins (11%). CONCLUSIONS: This study shows that it is possible to alert for potential DLTIs in real-time with a CDSS. The CDSS was successfully implemented in three hospitals. Further research must reveal its usefulness in clinical practice.

Clinical usefulness of drug-laboratory test interaction alerts: a multicentre survey.

OBJECTIVES: Knowledge of possible drug-laboratory test interactions (DLTIs) is important for the interpretation of laboratory test results. Failure to recognize these interactions may lead to misinterpretation, a delayed or erroneous diagnosis, or unnecessary extra diagnostic tests or therapy, which may harm patients. The aim of this multicentre survey was to evaluate the clinical value of DLTI alerts. METHODS: A survey was designed with six predefined clinical cases selected from the clinical laboratory practice with a potential DLTI. Physicians from several departments, including internal medicine, cardiology, intensive care, surgery and geriatrics in six participating hospitals were recruited to fill in the survey. The survey addressed their knowledge of DLTIs, motivation to receive an alert and opinion on the potential influence on medical decision making. RESULTS: A total of 210 physicians completed the survey. Of these respondents 93% had a positive attitude towards receiving DLTI alerts; however, the reported value differed per case and per respondent's background. In each clinical case, medical decision making was influenced as a consequence of the reported DLTI message (ranging from 3 to 45% of respondents per case). CONCLUSIONS: In this multicentre survey, most physicians stated DLTI messages to be useful in laboratory test interpretation. Medical decision making was influenced by reporting DLTI alerts in each case. Alerts should be adjusted according to the needs and preferences of the receiving physicians.

Quality benchmarking of smartphone laboratory medicine applications: comparison of laboratory medicine specialists' and non-laboratory medicine professionals' evaluation.

OBJECTIVES: There are many mobile health applications (apps) now available and some that use in some way laboratory medicine data. Among them, patient-oriented are of the lowest content quality. The aim of this study was to compare the opinions of non-laboratory medicine professionals (NLMP) with those of laboratory medicine specialists (LMS) and define the benchmarks for quality assessment of laboratory medicine apps. METHODS: Twenty-five volunteers from six European countries evaluated 16 selected patient-oriented apps. Participants were 20-60 years old, 44% were females, with different educational degrees, and no professional involvement in laboratory medicine. Each participant completed a questionnaire based on the Mobile Application Rating Scale (MARS) and the System Usability Scale, as previously used for rating the app quality by LMS. The responses from the two groups were compared using the Mann-Whitney U test and Spearman correlation. RESULTS: The median total score of NLMP app evaluation was 2.73 out of 5 (IQR 0.95) compared to 3.78 (IQR 1.05) by the LMS. All scores were statistically significantly lower in the NLMP group (p<0.05), except for the item Information quality (p=0.1631). The suggested benchmarks for a useful appear: increasing awareness of the importance and delivering an understanding of persons' own laboratory test results; understandable terminology; easy to use; appropriate graphic design, and trustworthy information. CONCLUSIONS: NLMP' evaluation confirmed the low utility of currently available laboratory medicine apps. A reliable app should contain trustworthy and understandable information. The appearance of an app should be fit for purpose and easy to use.

Reflective testing - A randomized controlled trial in primary care patients.

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.

Statistical distributions commonly used in measurement uncertainty in laboratory medicine.

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.

The end of the laboratory developed test as we know it? Recommendations from a national multidisciplinary taskforce of laboratory specialists on the interpretation of the IVDR and its complications.

The in vitro diagnostic medical devices regulation (IVDR) will take effect in May 2022. This regulation has a large impact on both the manufacturers of in vitro diagnostic medical devices (IVD) and clinical laboratories. For clinical laboratories, the IVDR poses restrictions on the use of laboratory developed tests (LDTs). To provide a uniform interpretation of the IVDR for colleagues in clinical practice, the IVDR Task Force was created by the scientific societies of laboratory specialties in the Netherlands. A guidance document with explanations and interpretations of relevant passages of the IVDR was drafted to help laboratories prepare for the impact of this new legislation. Feedback from interested parties and stakeholders was collected and used to further improve the document. Here we would like to present our approach to our European colleagues and inform them about the impact of the IVDR and, importantly we would like to present potentially useful approaches to fulfill the requirements of the IVDR for LDTs.

Diagnostic error as a result of drug-laboratory test interactions.

Background Knowledge of possible drug-laboratory test interactions (DLTIs) is important for the interpretation of laboratory test results. Test results may be affected by physiological or analytical drug effects. Failure to recognize these interactions may lead to misinterpretation of test results, a delayed or erroneous diagnosis or unnecessary extra tests or therapy, which may harm patients. Content Thousands of interactions have been reported in the literature, but are often fragmentarily described and some papers even reported contradictory findings. How can healthcare professionals become aware of all these possible interactions in their individual patients? DLTI decision support applications could be a good solution. In a literature search, only four relevant studies have been found on DLTI decision support applications in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the interpretation of laboratory test results. All physicians reported that part of the DLTI messages were useful. In one study, 74% of physicians even sometimes refrained from further additional examination. Summary and outlook Unrecognized DLTIs potentially cause diagnostic errors in a large number of patients. Therefore, efforts to avoid these errors, for example with a DLTI decision support application, could tremendously improve patient outcome.

Opinion: redefining the role of the physician in laboratory medicine in the context of emerging technologies, personalised medicine and patient autonomy ('4P medicine').

The role of clinical pathologists or laboratory-based physicians is being challenged on several fronts-exponential advances in technology, increasing patient autonomy exercised in the right to directly request tests and the use of non-medical specialists as substitutes. In response, clinical pathologists have focused their energies on the pre-analytical and postanalytical phases of Laboratory Medicine thus emphasising their essential role in individualised medical interpretation of complex laboratory results. Across the European Union, the role of medical doctors is enshrined in the Medical Act. This paper highlights the relevance of this act to patient welfare and the need to strengthen training programmes to prevent an erosion in the quality of Laboratory Medicine provided to patients and their physicians.

Adding clinical utility to the laboratory reports: automation of interpretative comments.

In laboratory medicine, consultation by adding interpretative comments to reports has long been recognized as one of the activities that help to improve patient treatment outcomes and strengthen the position of our profession. Interpretation and understanding of laboratory test results might in some cases considerably be enhanced by adding test when considered appropriate by the laboratory specialist - an activity that was named reflective testing. With patient material available at this stage, this might considerably improve the diagnostic efficiency. The need and value of these forms of consultation have been proven by a diversity of studies. Both general practitioners and medical specialists have been shown to value interpretative comments. Other forms of consultation are emerging: in this time of patient empowerment and shared decision making, reporting of laboratory results to patients will be common. Patients have in general little understanding of these results, and consultation of patients could add a new dimension to the service of the laboratory. These developments have been recognized by the European Federation of Clinical Chemistry and Laboratory Medicine, which has established the working group on Patient Focused Laboratory Medicine for work on the matter. Providing proper interpretative comments is, however, labor intensive because harmonization is necessary to maintain quality between individual specialists. In present-day high-volume laboratories, there are few options on how to generate high-quality, patient-specific comments for all the relevant results without overwhelming the laboratory specialists. Automation and application of expert systems could be a solution, and systems have been developed that could ease this task.

Impact of interactions between drugs and laboratory test results on diagnostic test interpretation - a systematic review.

Intake of drugs may influence the interpretation of laboratory test results. Knowledge and correct interpretation of possible drug-laboratory test interactions (DLTIs) is important for physicians, pharmacists and laboratory specialists. Laboratory results may be affected by analytical or physiological effects of medication. Failure to take into account the possible unintended influence of drug use on a laboratory test result may lead to incorrect diagnosis, incorrect treatment and unnecessary follow-up. The aim of this review is to give an overview of the literature investigating the clinical impact and use of DLTI decision support systems on laboratory test interpretation. Particular interactions were reported in a large number of articles, but they were fragmentarily described and some papers even reported contradictory findings. To provide an overview of information that clinicians and laboratory staff need to interpret test results, DLTI databases have been made by several groups. In a literature search, only four relevant studies have been found on DLTI decision support applications for laboratory test interpretation in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the correct interpretation of laboratory test results. Physicians reported 30-100% usefulness of DLTI messages. In one study 74% of physicians sometimes even refrained from further additional examination. The benefit of decision support increases when a refined set of clinical rules is determined in cooperation with health care professionals. The prevalence of DLTIs is high in a broad range of combinations of laboratory tests and drugs and these frequently remain unrecognized.

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

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.

Performance specifications and six sigma theory: Clinical chemistry and industry compared.

Analytical performance specifications are crucial in test development and quality control. Although consensus has been reached on the use of biological variation to derive these specifications, no consensus has been reached which model should be preferred. The Six Sigma concept is widely applied in industry for quality specifications of products and can well be compared with Six Sigma models in clinical chemistry. However, the models for measurement specifications differ considerably between both fields: where the sigma metric is used in clinical chemistry, in industry the Number of Distinct Categories is used instead. In this study the models in both fields are compared and discussed.

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

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.

Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference.

Measurements in clinical laboratories produce results needed in the diagnosis and monitoring of patients. These results are always characterized by some uncertainty. What quality is needed and what measurement errors can be tolerated without jeopardizing patient safety should therefore be defined and specified for each analyte having clinical use. When these specifications are defined, the total examination process will be "fit for purpose" and the laboratory professionals should then set up rules to control the measuring systems to ensure they perform within specifications. The laboratory community has used different models to set performance specifications (PS). Recently, it was felt that there was a need to revisit different models and, at the same time, to emphasize the presuppositions for using the different models. Therefore, in 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) organized a Strategic Conference in Milan. It was felt that there was a need for more detailed discussions on, for instance, PS for EQAS, which measurands should use which models to set PS and how to set PS for the extra-analytical phases. There was also a need to critically evaluate the quality of data on biological variation studies and further discussing the use of the total error (TE) concept. Consequently, EFLM established five Task Finish Groups (TFGs) to address each of these topics. The TFGs are finishing their activity on 2017 and the content of this paper includes deliverables from these groups.