Publications by Mikael Nyström

Background: In order to satisfy different needs, medical terminology systems musthave richer structures. This study examines whether a Swedish primary health careversion of the mono-hierarchical ICD-10 (KSH97-P) may obtain a richer structureusing category and chapter mappings from KSH97-P to SNOMED CT and SNOMEDCT’s structure. Manually-built mappings from KSH97-P’s categories and chapters toSNOMED CT’s concepts are used as a starting point

Results: The mappings are manually evaluated using computer-producedinformation and a small number of mappings are updated. A new and polyhierarchicalchapter division of KSH97-P’s categories has been created using thecategory and chapter mappings and SNOMED CT’s generic structure. In the newchapter division, most categories are included in their original chapters. Aconsiderable number of concepts are included in other chapters than their originalchapters. Most of these inclusions can be explained by ICD-10’s design. KSH97-P’scategories are also extended with attributes using the category mappings andSNOMED CT’s defining attribute relationships. About three-fourths of all conceptsreceive an attribute of type Finding site and about half of all concepts receive anattribute of type Associated morphology. Other types of attributes are less common.

Conclusions: It is possible to use mappings from KSH97-P to SNOMED CT andSNOMED CT’s structure to enrich KSH97-P’s mono-hierarchical structure with a polyhierarchicalchapter division and attributes of type Finding site and Associatedmorphology. The final mappings are available as additional files for this paper.

Background

The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

Methods

Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

Results

An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

Conclusion

Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

Background

The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

Methods

Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

Results

An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

Conclusion

Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

Background: This paper reports on a parallel collection of rubrics from the medical terminology systems ICD-10, ICF, MeSH, NCSP and KSH97-P and its use for semi-automatic creation of an English-Swedish dictionary of medical terminology. The methods presented are relevant for many other West European language pairs than English-Swedish. Methods: The medical terminology systems were collected in electronic format in both English and Swedish and the rubrics were extracted in parallel language pairs. Initially, interactive word alignment was used to create training data from a sample. Then the training data were utilised in automatic word alignment in order to generate candidate term pairs. The last step was manual verification of the term pair candidates. Results: A dictionary of 31,000 verified entries has been created in less than three man weeks, thus with considerably less time and effort needed compared to a manual approach, and without compromising quality. As a side effect of our work we found 40 different translation problems in the terminology systems and these results indicate the power of the method for finding inconsistencies in terminology translations. We also report on some factors that may contribute to making the process of dictionary creation with similar tools even more expedient. Finally, the contribution is discussed in relation to other ongoing efforts in constructing medical lexicons for non-English languages. Conclusion: In three man weeks we were able to produce a medical English-Swedish dictionary consisting of 31,000 entries and also found hidden translation errors in the utilized medical terminology systems. © 2006 Nyström et al, licensee BioMed Central Ltd.

Methods for presentation of disease and health problem distribution in a health care environment rely among other things on the inherent structure of the controlled terminology used for coding. In the present study, this aspect is explored with a focus on ICD-10 and SNOMED CT. The distribution of 2,5 million diagnostic codes from primary health care in the Stockholm region is presented and analyzed through the “lenses” of ICD-10 and SNOMED CT. The patient encounters, originally coded with a reduced set of ICD-10 codes used in primary health care in Sweden, were mapped to SNOMED CT concepts through a mapping table. The method used for utilizing the richer structure of SNOMED CT as compared to ICD-10 is presented, together with examples of produced disease distributions. Implications of the proposed method for enriching a traditional classification such as ICD-10 through mappings to SNOMED CT are discussed.

The current Swedish regulations for medical alerts in health records were designed for paper records. Suggestions for computerized systems are now being investigated. A proposed model using three alert categories, graphically represented using three directions, probably combined with three severity levels is presented here. Up represents hypersensitivities, left/back represents alerting diagnosis and right/forward represents alerting current and planned treatments. A small qualitative user study of the alert classification model and some graphical representations of it was conducted. One main finding is that most respondents found the use of directions intuitive as a means of presenting categories. Context dependency, information overload, and future possibilities for automated alert-gathering are also discussed in the paper.

With the introduction of EHR two-level modelling and archetype methodologies pioneered by openEHR and standardized by CEN/ISO, we are one step closer to semantic interoperability and future-proof adaptive healthcare information systems. Along with the opportunities, there are also challenges. Archetypes provide the full semantics of EHR data explicitly to surrounding systems in a platform-independent way, yet it is up to the receiving system to interpret the semantics and process the data accordingly. In this paper we propose a design of an archetype-based platform-independent testing framework for validating implementations of the openEHR archetype formalism as a means of improving quality and interoperability of EHRs.

Electronic health record systems (EHR) are used to store relevant heath facts about patients. The main use of the EHR is in the care of the patient, but an additional use is to reuse the EHR information to locate and evaluate clinical evidence for treatments. To efficiently use the EHR information it is essential to use appropriate methods for information compilations. This thesis deals with use of information in medical terminology systems and ontologies to be able to better use and reuse EHR information and other medical information.

The first objective of the thesis is to examine if word alignment on bilingual English-Swedish rubrics from five medical terminology systems can be used to build a bilingual dictionary. A study found that it was possible to generate a dictionary with 42 000 entries containing a high proportion of medical entries using word alignment. The method worked best using sets of rubrics with many unique words that are consistently translated. The dictionary can be used as a general medical dictionary, for use in semi-automatic translation methods, for use in cross-language information retrieval systems, and for enrichment of other terminology systems.

The second objective of the thesis is to explore how connections from existing terminology systems and information models to SNOMED CT and the structure in SNOMED CT can be used to reuse information. A study examined whether the primary health care diagnose terminology system KSH97-P can obtain a richer structure using category and chapter mappings from KSH97-P to SNOMED CT and the structure in SNOMED CT. The study showed that KSH97-P can be enriched with a poly-hierarchical chapter division and additional attributes. The richer structure was used to compile statistics in new manners that showed new views of the primary care diagnoses. A literature study evaluated which kinds of information compilations those are necessary to create graphical patient overviews based on information from EHRs. It was found that a third of the patient overviews can have their information needs satisfied using compilations based on SNOMED CT encodings of the information entities in the EHR and the structure in SNOMED CT. The other overviews also need access to individual values in the EHR. This can be achieved by using well-defined information models in the EHR.

Förvaltningsrapporten fokuserar på Snomed CT, eftersom det redan i dag finns rutiner för förvaltningar av termbanken och nationella hälsorelaterade klassifikationer. Ett särskilt utvecklingsarbete kommer att krävas för dessa delar.

Rapporten tar upp syfte och mål med förvaltningen. Utöver det redogör rapporten för vilka konkreta ansvarsområden som ingår i förvaltningen av Snomed CT. Målet för förvaltningen är att Socialstyrelsen regelbundet ska kunna tillhandahålla en kontrollerad och uppdaterad release av Snomed CT. Det skulle möjliggöra användning inom vård och omsorg. Rapporten tar även upp behovet av kompetens, utbildning och finansiella resurser.

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