Introduction In order to further advance research and development on the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) standard, the existing research must be well understood. This paper presents a methodological review of the ODM literature. Specifically, it develops a classification schema to categorize the ODM literature according to how the standard has been applied within the clinical research data lifecycle. This paper suggests areas for future research and development that address ODM’s limitations and capitalize on its strengths to support new trends in clinical research informatics. Methods A systematic scan of the following databases was performed: (1) ABI/Inform, (2) ACM Digital, (3) AIS eLibrary, (4) Europe Central PubMed, (5) Google Scholar, (5) IEEE Xplore, (7) PubMed, and (8) ScienceDirect. A Web of Science citation analysis was also performed. The search term used on all databases was “CDISC ODM.” The two primary inclusion criteria were: (1) the research must examine the use of ODM as an information system solution component, or (2) the research must critically evaluate ODM against a stated solution usage scenario. Out of 2,686 articles identified, 266 were included in a title level review, resulting in 183 articles. An abstract review followed, resulting in 121 remaining articles; and after a full text scan 69 articles met the inclusion criteria. Results As the demand for interoperability has increased, ODM has shown remarkable flexibility and has been extended to cover a broad range of data and metadata requirements that reach well beyond ODM’s original use cases. This flexibility has yielded research literature that covers a diverse array of topic areas. A classification schema reflecting the use of ODM within the clinical research data lifecycle was created to provide a categorized and consolidated view of the ODM literature. The elements of the framework include: (1) EDC (Electronic Data Capture) and EHR (Electronic Health Record) infrastructure; (2) planning; (3) data collection; (4) data tabulations and analysis; and (5) study archival. The analysis reviews the strengths and limitations of ODM as a solution component within each section of the classification schema. This paper also identifies opportunities for future ODM research and development, including improved mechanisms for semantic alignment with external terminologies, better representation of the CDISC standards used end-to-end across the clinical research data lifecycle, improved support for real-time data exchange, the use of EHRs for research, and the inclusion of a complete study design. Conclusions ODM is being used in ways not originally anticipated, and covers a diverse array of use cases across the clinical research data lifecycle. ODM has been used as much as a study metadata standard as it has for data exchange. A significant portion of the literature addresses integrating EHR and clinical research data. The simplicity and readability of ODM has likely contributed to its succe...
The complexity and size of the trial master file requires new solutions. Though ODM provides effective means to archive the study database, it shows still deficiencies, especially for the joint archiving of data and the complex documentation of the trial master file. A concept was developed in which the ODM standard is part of an integrated archiving of the trial data and documents. ODM archiving of the study database enables long-term storage which is GCP-compliant. Archiving of documents of the trial master file in PDF/A, including links and electronic signatures, as well as the storage of selected study data in a data warehouse at the sponsor site in SDTM are the other components of the concept.
Background: The CDISC SDTM standard for submission of clinical study data to the FDA was developed at a time when the extraction of data from electronic health records or hospital information systems was still uncommon. Therefore the current SDTM is not well suited for cases where interoperability between healthcare and research has already been realized. Objectives: It is therefore necessary to adapt the SDTM to accommodate for these present-day use cases. Methods: A critical analysis of the existing "Laboratory" (LB) SDTM domain has been made with respect to the suitability to represent data extracted from electronic health records.Results: An alternative "Laboratory" domain (abbreviated LN Laboratory New) for usage with data from electronic health records is presented. Conclusions: The alternative LN domain presented fullls the requirements for direct population with data from electronic health records. As a by-product, it allows reviewers at the FDA to actually compare laboratory data between studies and submissions which was not possible with the classic SDTM "Laboratory" domain.
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