Summary
Introduction: 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 inter-operability
for AE reporting.
Method: 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 avail able
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.
Conclusion: SALUS platform’s interopera bility solutions enable partial automation of the AE
reporting process, which could con tribute to improve current spontaneous reporting
practices and reduce under-report ing, which is currently one major obstacle in the
process of acquisition of pharmacovigilance data.
Keywords
Pharmacovigilance - adverse drug event reporting - semantic interoperability - EHR
data models - secondary use of EHR
