Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jun 19, 2023
Date Accepted: Jan 18, 2024
Creation of standardized common data elements for diagnostic tests in infectious disease studies
ABSTRACT
Background:
There is a need for harmonization of variables in case report forms of infectious disease studies to facilitate merging and sharing of collected patient data. Implementation of core data elements and incorporation of interoperability standards can facilitate harmonization of these clinical data sets.
Objective:
This study’s objective was to compare laboratory variables focusing on diagnostic tests used as part of case report forms (CRFs) in six international infectious disease studies in an attempt of harmonization and standardization.
Methods:
For each of the clinical studies under consideration, we reviewed the metadata that comprises the case report form in order to identify common data elements and propose a data model that incorporates semantic and syntactic standards. In addition, we examined the availability of international semantic standard codes within Systemized Nomenclature of Medicine - Clinical Terms, the National Cancer Institute’ Thesaurus and the Logical Observation Identifiers Names and Codes system for the unambiguous representation of diagnostic testing information that make up the common data elements.
Results:
Out of 216 variables that were in-scope for this analysis, we identified 11 common data elements to describe diagnostic tests (in particular serology and sequencing) for infectious diseases (InfD-CDEs); viral lineage/clade, test date, type, performer and manufacturer, target gene, quantitative and qualitative result, as well as specimen identifier, type and collection date.
Conclusions:
The identification of InfD-CDEs ensures that a subset of data can be shared across different clinical studies (and with that large research projects), thus enabling a minimum level of interoperability. The link to standard terminologies ensures that the variable definitions are unambiguous and that their interpretation is unique across studies. Exchange of this data is assisted by “wrapping” it in a standard exchange format, such as FHIR®.
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