Literature DB >> 23504699

A new coding system for metabolic disorders demonstrates gaps in the international disease classifications ICD-10 and SNOMED-CT, which can be barriers to genotype-phenotype data sharing.

Annet Sollie1, Rolf H Sijmons, Dick Lindhout, Ans T van der Ploeg, M Estela Rubio Gozalbo, G Peter A Smit, Frans Verheijen, Hans R Waterham, Sonja van Weely, Frits A Wijburg, Rudolph Wijburg, Gepke Visser.   

Abstract

Data sharing is essential for a better understanding of genetic disorders. Good phenotype coding plays a key role in this process. Unfortunately, the two most widely used coding systems in medicine, ICD-10 and SNOMED-CT, lack information necessary for the detailed classification and annotation of rare and genetic disorders. This prevents the optimal registration of such patients in databases and thus data-sharing efforts. To improve care and to facilitate research for patients with metabolic disorders, we developed a new coding system for metabolic diseases with a dedicated group of clinical specialists. Next, we compared the resulting codes with those in ICD and SNOMED-CT. No matches were found in 76% of cases in ICD-10 and in 54% in SNOMED-CT. We conclude that there are sizable gaps in the SNOMED-CT and ICD coding systems for metabolic disorders. There may be similar gaps for other classes of rare and genetic disorders. We have demonstrated that expert groups can help in addressing such coding issues. Our coding system has been made available to the ICD and SNOMED-CT organizations as well as to the Orphanet and HPO organizations for further public application and updates will be published online (www.ddrmd.nl and www.cineas.org).
© 2013 WILEY PERIODICALS, INC.

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Year:  2013        PMID: 23504699     DOI: 10.1002/humu.22316

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  6 in total

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2.  Extending the coverage of phenotypes in SNOMED CT through post-coordination.

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4.  Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.

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5.  SORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data.

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6.  Construction of a semi-automatic ICD-10 coding system.

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  6 in total

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