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Background and Motivation

The availability of very large-scale healthcare databases in electronic form has opened the possibility to generate systematic and large-scale evidence and insights about the application of healthcare to patients. This discipline is called Observational Outcome Research, and it uses longitudinal patient level clinical data in order to describe and understand the pathogenesis of disease and the effect of other clinical events as well as treatment interventions on the progression of the disease. This research constitutes secondary use of the data, which is being collected usually for purposes other than research: administrative data such as insurance reimbursement claims and Electronic Health or Medical Record (EHR, EMR).

Because of the collection purpose for primary use, the format and representation of the data follows that primary use. It also introduces artifacts and bias into the data. In addition, all source datasets differ from each other in format and content representation. Since healthcare systems differ between countries, the problem becomes even harder for research carried out internationally. All this makes robust, reproducible and automated research a significant challenge.

The solution is the standardization of the data and a standardization of the representation. This allows methods and tools to operate on data of disparate origin, freeing the analyst from having to dissect the idiosyncrasies of a particular dataset and manipulating the data to make it fit for research. It also allows to develop analytical methods on one dataset, and applying it an any other dataset in CDM format.

The OMOP Standardized Vocabularies were initially constructed together with the OMOP Common Data Model for the conduct of the OMOP Experiments. Therefore, their design is very simple and facilitates the minimum functionality necessary to conduct these experiments, while at the same time allowing for a large resource like this to be maintained and developed using the very restricted resources of an Open Source Project. After OMOP ended in November 2013, the OMOP Standard Vocabularies are now supported by OHDSI and maintained by Odysseus Inc.

documentation/vocabulary/background.txt · Last modified: 2016/06/18 19:06 by cgreich