Application of a Regenstrief RELMA V.6.6 to Map Russian Laboratory Terms to LOINC.

BACKGROUND: Manual mapping of laboratory data to Logical Observation Identifiers Names and Codes (LOINC) requires a major effort. Application of the LOINC mapping assistant RELMA V.6.6 can reduce the effort required for mapping. The goal of the paper is to perform a semi-automated mapping of Russian laboratory terms to LOINC. METHODS: A semi-automated mapping of the 2563 terms from two clinics in Russia was performed. The first step was automatic mapping using RELMA V.6.6 and LOINC V.2.48 Russian translation by Yaroslavl state medical academy. The second step was a manual expert mapping. To evaluate the correctness of mapping all the mapped terms were reviewed by two experts. RESULTS: The paper presents the results of semi-automatic mapping of Russian laboratory terms to LOINC. Two clinics (A and B) and a laboratory service participated in the project. The following results were achieved: mapping of 86% terms from Clinic A and 87% from Clinic B. It has to be mentioned that 99% of terms used in 2014 were mapped. In total 2398 out of 2563 were mapped. DISCUSSION: The required effort was reasonable and the price of mapping and maintenance was considered as relatively low in comparison to manual methods. CONCLUSION: RELMA V.6.6 and LOINC V.2.48 offer the opportunity of a low effort LOINC mapping even for non-English languages. The study proved that the mapping effort is acceptable and mapping results are on the same level as the manual mapping.

Visualization of medical data based on EHR standards.

BACKGROUND: To organize an efficient interaction between a doctor and an EHR the data has to be presented in the most convenient way. Medical data presentation methods and models must be flexible in order to cover the needs of the users with different backgrounds and requirements. Most visualization methods are doctor oriented, however, there are indications that the involvement of patients can optimize healthcare. OBJECTIVES: The research aims at specifying the state of the art of medical data visualization. The paper analyzes a number of projects and defines requirements for a generic ISO 13606 based data visualization method. In order to do so it starts with a systematic search for studies on EHR user interfaces. METHODS: In order to identify best practices visualization methods were evaluated according to the following criteria: limits of application, customizability, re-usability. The visualization methods were compared by using specified criteria. RESULTS: The review showed that the analyzed projects can contribute knowledge to the development of a generic visualization method. However, none of them proposed a model that meets all the necessary criteria for a re-usable standard based visualization method. The shortcomings were mostly related to the structure of current medical concept specifications. CONCLUSION: The analysis showed that medical data visualization methods use hardcoded GUI, which gives little flexibility. So medical data visualization has to turn from a hardcoded user interface to generic methods. This requires a great effort because current standards are not suitable for organizing the management of visualization data. This contradiction between a generic method and a flexible and user-friendly data layout has to be overcome.