A case report: using SNOMED CT for grouping Adverse Drug Reactions Terms

نویسندگان

  • Iulian Alecu
  • Cédric Bousquet
  • Marie-Christine Jaulent
چکیده

BACKGROUND WHO-ART and MedDRA are medical terminologies used for the coding of adverse drug reactions in pharmacovigilance databases. MedDRA proposes 13 Special Search Categories (SSC) grouping terms associated to specific medical conditions. For instance, the SSC "Haemorrhage" includes 346 MedDRA terms among which 55 are also WHO-ART terms. WHO-ART itself does not provide such groupings. Our main contention is the possibility of classifying WHO-ART terms in semantic categories by using knowledge extracted from SNOMED CT. A previous paper presents the way WHO-ART term definitions have been automatically generated in a description logics formalism by using their corresponding SNOMED CT synonyms. Based on synonymy and relative position of WHO-ART terms in SNOMED CT, specialization or generalization relationships could be inferred. This strategy is successful for grouping the WHO-ART terms present in most MedDRA SSCs. However the strategy failed when SSC were organized on other basis than taxonomy. METHODS We propose a new method that improves the previous WHO-ART structure by integrating the associative relationships included in SNOMED CT. RESULTS The new method improves the groupings. For example, none of the 55 WHO-ART terms in the Haemorrhage SSC were matched using the previous method. With the new method, we improve the groupings and obtain 87% coverage of the Haemorrhage SSC. CONCLUSION SNOMED CT's terminological structure can be used to perform automated groupings in WHO-ART. This work proves that groupings already present in the MedDRA SSCs (e.g. the haemorrhage SSC) may be retrieved using classification in SNOMED CT.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Using SNOMED CT in combination with MedDRA for reporting signal detection and adverse drug reactions reporting

OBJECTIVE To investigate the feasibility of using SNOMED CT as an entry point for coding adverse drug reactions and map them automatically to MedDRA for reporting purposes and interoperability with legacy repositories. METHODS On the one hand, we attempt to map SNOMED CT concepts to MedDRA concepts through the UMLS, using synonymy and explicit mapping relations. On the other, we compute the s...

متن کامل

Determining correspondences between high-frequency MedDRA concepts and SNOMED: a case study

BACKGROUND The Systematic Nomenclature of Medicine Clinical Terms (SNOMED CT) is being advocated as the foundation for encoding clinical documentation. While the electronic medical record is likely to play a critical role in pharmacovigilance - the detection of adverse events due to medications - classification and reporting of Adverse Events is currently based on the Medical Dictionary of Regu...

متن کامل

Evaluating standard terminologies for encoding allergy information

OBJECTIVE Allergy documentation and exchange are vital to ensuring patient safety. This study aims to analyze and compare various existing standard terminologies for representing allergy information. METHODS Five terminologies were identified, including the Systemized Nomenclature of Medical Clinical Terms (SNOMED CT), National Drug File-Reference Terminology (NDF-RT), Medication Dictionary f...

متن کامل

Ontological Representation of Adverse Drug Reactions Using the Fundational Model of Anatomy

In a previous work we proposed a categorial structure for the representation of adverse drug reactions consisting of 16 semantic categories and 20 relations. We present an implementation of this categorial structure in Protégé based on four WHO-ART system organ classes: Gastro-intestinal system disorders, Liver and biliary system disorders, Central & peripheric nervous system disorders, and Psy...

متن کامل

بررسی تطبیقی سیر تکامل و ساختار سیستم های نامگذاری نظام یافته پزشکی SNOMED در کشورهای آمریکا ، انگلستان و استرالیا 86-85

Background and Aim: Systematized Nomenclature of Medicine systems are the important supportive for electronic health record in registration and retrieval of data. Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) is the most comprehensive language and then the consistency of exchanged data across health care providers and finally the high effectiveness of health care. Material...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • BMC Medical Informatics and Decision Making

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2008