title: Bridging data models and terminologies to support adverse drug event reporting using EHR data.
abstract: BACKGROUND
  This article is part of the Focus Theme of METHODs of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".
  
  
  BACKGROUND
  SALUS project aims at building an interoperability platform and a dedicated toolkit to enable secondary use of electronic health records (EHR) data for post marketing drug surveillance. An important component of this toolkit is a drug-related adverse events (AE) reporting system designed to facilitate and accelerate the reporting process using automatic prepopulation mechanisms.
  
  
  OBJECTIVE
  To demonstrate SALUS approach for establishing syntactic and semantic interoperability for AE reporting.
  
  
  METHODS
  Standard (e.g. HL7 CDA-CCD) and proprietary EHR data models are mapped to the E2B(R2) data model via SALUS Common Information Model. Terminology mapping and terminology reasoning services are designed to ensure the automatic conversion of source EHR terminologies (e.g. ICD-9-CM, ICD-10, LOINC or SNOMED-CT) to the target terminology MedDRA which is expected in AE reporting forms. A validated set of terminology mappings is used to ensure the reliability of the reasoning mechanisms.
  
  
  RESULTS
  The percentage of data elements of a standard E2B report that can be completed automatically has been estimated for two pilot sites. In the best scenario (i.e. the available fields in the EHR have actually been filled), only 36% (pilot site 1) and 38% (pilot site 2) of E2B data elements remain to be filled manually. In addition, most of these data elements shall not be filled in each report.
  
  
  CONCLUSIONS
  SALUS platform's interoperability solutions enable partial automation of the AE reporting process, which could contribute to improve current spontaneous reporting practices and reduce under-reporting, which is currently one major obstacle in the process of acquisition of pharmacovigilance data.
authors.affiliation: Gunnar Declerck, Centre de recherche des Cordeliers, 15 rue de l'école de médecine, 75006 Paris, France, E-mail: gunnar.declerck@upmc.fr.
authors.forename: G
authors.initials: G
authors.lastname: Declerck
authors.forename: S
authors.initials: S
authors.lastname: Hussain
authors.forename: C
authors.initials: C
authors.lastname: Daniel
authors.forename: M
authors.initials: M
authors.lastname: Yuksel
authors.forename: G B
authors.initials: GB
authors.lastname: Laleci
authors.forename: M
authors.initials: M
authors.lastname: Twagirumukiza
authors.forename: M-C
authors.initials: MC
authors.lastname: Jaulent
mesh_terms: D064420:Drug-Related Side Effects and Adverse Reactions; D057286:Electronic Health Records; D006801:Humans; D060735:Pharmacovigilance; D039061:Systematized Nomenclature of Medicine; D018511:Systems Integration
keywords: EHR data models; Pharmacovigilance; adverse drug event reporting; secondary use of EHR; semantic interoperability