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Legal regulations and guidelines such as the Guidelines of the German Medical Association for the Quality Assurance of Laboratory Medical Examinations (Rili-BAEK) and ISO 15189 apply to electronic laboratory reports. However, many laboratories struggle with practical implementation of these regulations and guidelines. Laboratory and legal experts analyse the relevant guidelines and provide checklists and practical recommendations for implementation. Laboratories have less control over the display of electronic laboratory reports than over paper documents. However, an electronic report alone is legally sufficient and need not be accompanied by a paper copy. Rili-BAEK and ISO 15189 stipulate a set of minimum information in every report. The laboratory must verify that reports are transmitted and displayed correctly. To help laboratories do so, agreements between laboratories and the report recipients can clarify responsibilities. Electronic laboratory reports can improve patient care, but laboratories need to verify their quality. Towards this end, Rili-BAEK and ISO 15189 set out helpful provisions. [ABSTRACT FROM AUTHOR]

The quest to use patient results as quality control for routine clinical chemistry testing has long been driven by issues of the unavailability and cost of suitable quality control material and the matrix effects of synthetic material. Hematology laboratories were early adopters of average of normals techniques, primarily because of the difficulty in acquiring appropriate, stable quality control material, while in the chemistry laboratories, the perceived advantages and availability of synthetic material outweighed the disadvantages. However, the increasing volume of testing in clinical chemistry plus the capability of computer systems to deal with large and complex calculations has now made the use of patient-based quality control algorithms feasible. The desire to use patient-based quality control is also driven by increasing awareness that common quality control rules and frequency of analysis may fail to detect clinically significant assay biases. The non-commutability of quality control material has also become a problem as laboratories seek to harmonize results across regions and indeed globally. This review describes the history of patient-based quality control in clinical chemistry, summarizes the various approaches that can be implemented by laboratory professionals, and discusses how patient-based quality control can be integrated with traditional quality control techniques. [ABSTRACT FROM AUTHOR]

Background: Terminologies facilitate data exchange and enable laboratories to assist in patient care even if complex treatment pathways involve multiple stakeholders. This paper examines the three common terminologies Nomenclature for Properties and Units (NPU), Logical Observation Identifiers Names and Codes (LOINC), and SNOMED Clinical Terms (SNOMED CT). Methods: The potential of each terminology to encode five exemplary laboratory results is assessed. The terminologies are evaluated according to scope, correctness, formal representations, and ease of use. Results: NPU is based on metrological concepts with strict rules regarding the coding of the measurand and the result value. Clinically equivalent results are regularly mapped to the same code but there is little support to differentiate results from non-standardized measurements. LOINC encodes analyses as offered by the laboratory. Its large number of entries allows different mappings for the same analysis. SNOMED CT contains few analyses natively, but its formal composition mechanism allows representing measurements by post-coordinated expressions that are equivalent to LOINC codes. SNOMED CT's strength lies in its support of many non-numerical result values. Implicit code hierarchies exist in NPU and LOINC. SNOMED CT has explicit, elaborate axioms that elucidate the meaning of its content. Its complexity and its license conditions, however, impede a more widespread use. Interpretive comments, a crucial part of laboratory results, are still difficult to encode with any of the terminologies. Conclusions: All three terminologies have distinct potentials and limitations, but the approximation of SNOMED CT and LOINC suggests using them together. Terminologies need to be expanded to also cover interpretive comments. [ABSTRACT FROM AUTHOR]

An introduction to articles in the issue is presented on topics including a set of ICT tools that is used in Switzerland to render laboratory data interoperable, the process of implementing the Australian electronic health record, and some of the challenges of new diagnostic tests that produce so much data.

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