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Background Some clinical chemistry measurement methods are vulnerable to interference if hemolyzed serum samples are used. The aims of this study were: (1) to obtain updated information about how hemolysis affects clinical chemistry test results on different instrument platforms used in Nordic laboratories, and (2) to obtain data on how test results from hemolyzed samples are reported in Nordic laboratories. Methods Four identical samples containing different degrees of hemolysis were prepared and distributed to 145 laboratories in the Nordic countries. The laboratories were asked to measure the concentration of cell-free hemoglobin (Hb), together with 15 clinical chemistry analytes. In addition, the laboratories completed a questionnaire about how hemolyzed samples are handled and reported. Results Automated detection of hemolysis in all routine patient samples was used by 63% of laboratories, and 88% had written procedures on how to handle hemolyzed samples. The different instrument platforms measured comparable mean Hb concentrations in the four samples. For most analytes, hemolysis caused a homogenous degree of interference regardless of the instrument platform used, except for alkaline phosphatase (ALP), bilirubin (total) and creatine kinase (CK). The recommended cut-off points for rejection of a result varied substantially between the manufacturers. The laboratories differed in how they reported test results, even when they used the same type of instrument. Conclusions Most of the analytes were homogeneously affected by hemolysis, regardless of the instrument used. There is large variation, however, between the laboratories on how they report test results from hemolyzed samples, even when they use the same type of instrument.

Objectives Internal quality control (IQC) plays an important role in quality assurance in laboratory medicine. However, there is no universal consensus or guideline on when and how IQC should be analyzed on point-of-care testing (POCT) devices. The aim of this study was to develop a scoring system to determine how often IQC should be analyzed in primary healthcare on the various POCT devices. Methods Based on a systematic literature review and a thorough process involving the whole Noklus, a nationwide POC organization, a scoring system for when to analyze IQC was developed. Four factors were considered to significantly impact IQC frequency: The importance of the analyte in diagnosing and monitoring patients, type of POCT device, user-friendliness, and number of patient samples. For each POCT device, the first three factors were given a score, and the sum of the scores determined the general recommended IQC frequency. The number of patient samples determined whether and how to adjust these frequencies in each individual general practice. Results The scoring system was applied to 17 analytes and 134 different POCT devices (153 analyte-device combinations). Most of the devices analyzing high-risk analytes (71 out of 74) obtained daily or weekly IQC frequency. For example, all blood-cell counters and all glucose meters should undergo IQC daily and weekly, respectively. Conclusions This study presents a consensus-based scoring system for differentiated and device-specific recommendations for IQC frequency on POCT devices in primary healthcare. The scoring system can easily be adopted to other local environments and is easy to use.

Objectives Differences between laboratory results attributable to the use of different reagent lots can potentially affect the diagnosis and monitoring of patients. To minimize patient risks, all laboratories should verify that new reagent lots meet agreed analytical performance specifications (APS). We propose a simplified, pragmatic approach for laboratories that involves compilating results into a national surveillance program, and present the first results obtained when applying this approach to troponins, glycated hemoglobin (HbA1c), prostate-specific antigen (PSA) and D-dimer. Methods In the surveillance program we have (i) determined APS for selected analytes, (ii) implemented a simplified procedure for lot evaluation with patient samples used in laboratories across Norway and (iii) performed central processing of the results from the participating laboratories. Results Over a one-year period, 27 Norwegian laboratories returned results from 28 lot changes for troponin I, 11 for troponin T, and 29 for HbA1c, PSA and D-dimer. The mean difference between two reagent lots was 4.5% for troponin I (for a concentration interval of 20–32 ng/L), 5.1% for troponin T (10.7–17.5 ng/L), 2.2% for HbA1c (40–50 mmol/mol), 3.7% for PSA (3–5 μg/L) and 5.5% for D-dimer (0.4–1.0 mg/L FEU). Conclusions A novel procedure for reagent lot evaluation is proposed in which information about multiple lot changes from different medical laboratories can be accumulated nationally. Sharing this information allows simplification of lot evaluations in individual laboratories and provides real-world data about lot-to-lot variations.