OHDSI Standards and Tools
The Observational Health Data Sciences and Informatics (OHDSI) organization is described here. For the most up-to-date information, please visit ohdsi.org
The OMOP Common Data Model
"The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an open community data standard, designed to standardize the structure and content of observational data and to enable efficient analyses that can produce reliable evidence." [1]
To learn more about the OMOP CDM, view this tutorial.
To explore the latest OMOP CDM (v5.4), view the specification and entity-relationship diagram.
The OHDSI Standardized Vocabularies
"A central component of the OMOP CDM is the OHDSI standardized vocabularies. The OHDSI vocabularies allow organization and standardization of medical terms to be used across the various clinical domains of the OMOP common data model and enable standardized analytics that leverage the knowledge base when constructing exposure and outcome phenotypes and other features within characterization, population-level effect estimation, and patient-level prediction studies." [1,2]
Concept Sets and Cohort Definitions
OHDSI analysis tools require the use of concept sets and cohort definitions. Concept sets are groups of OMOP concept IDs selected to define the clinical concepts central to a research question. For more information on concept sets, refer to Chapter 10.3 in The Book of OHDSI and this tutorial on creating concept sets in ATLAS.
A cohort is set of persons who satisfy one or more cohort inclusion criteria for a duration of time. A cohort definition will include the clinical concepts that define the inclusion criteria as well as the temporal logic for cohort entry. For more information on cohorts, refer to Chapter 10 in The Book of OHDSI and this tutorial on ATLAS cohort design.
ATHENA
OHDSI's ATHENA is a tool to search and and manually map standardized healthcare vocabularies to standard OMOP concept IDs. [3]
ATLAS
ATLAS is a web-based tool developed by the OHDSI community that facilitates the design and execution of analyses on standardized, patient-level, observational data in the OMOP CDM format. As ATLAS is used for analysis of person-level data, an organization will typically install it in a secure environment. OHDSI hosts an ATLAS Demo instance with synthetic data that can be used for exploration of the tool and training. [3]
HADES
HADES is a collection of open-source R packages developed by the OHDSI community that offer functions which can be used together to perform a complete observational study utilizing standardized, patient-level, observational data in the OMOP CDM format. [3]
To learn more about use of OHDSI standards and tools in Rhode Island, please reach out to ursa-help@brown.edu
References
OHDSI Standardized Data: The OMOP Common Data Model. [Accessed 2025-01-22]; https://ohdsi.org/data-standardization/
Reich C, Ostropolets A, Ryan P, Rijnbeek P, Schuemie M, Davydov A, Dymshyts D, Hripcsak G. OHDSI Standardized Vocabularies-a large-scale centralized reference ontology for international data harmonization. J Am Med Inform Assoc. 2024 Feb 16;31(3):583-590. doi: 10.1093/jamia/ocad247. PMID: 38175665; PMCID: PMC10873827.
OHDSI Software Tools. [Accessed 2025-01-22]; https://ohdsi.org/software-tools/
Resources
Articles
Overhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. J Am Med Inform Assoc. 2012 Jan-Feb;19(1):54-60. doi: 10.1136/amiajnl-2011-000376. Epub 2011 Oct 28. PMID: 22037893; PMCID: PMC3240764.
Schuemie M, Reps J, Black A, Defalco F, Evans L, Fridgeirsson E, Gilbert JP, Knoll C, Lavallee M, Rao GA, Rijnbeek P, Sadowski K, Sena A, Swerdel J, Williams RD, Suchard M. Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research. Stud Health Technol Inform. 2024 Jan 25;310:966-970. doi: 10.3233/SHTI231108. PMID: 38269952; PMCID: PMC10868467.
Schuemie MJ, Ryan PB, Pratt N, Chen R, You SC, Krumholz HM, Madigan D, Hripcsak G, Suchard MA. Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND). J Am Med Inform Assoc. 2020 Aug 1;27(8):1331-1337. doi: 10.1093/jamia/ocaa103. PMID: 32909033; PMCID: PMC7481029.
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