Metadata-driven creation of data marts from an EAV-modeled clinical research database.

Abstract:

:Generic clinical study data management systems can record data on an arbitrary number of parameters in an arbitrary number of clinical studies without requiring modification of the database schema. They achieve this by using an Entity-Attribute-Value (EAV) model for clinical data. While very flexible for creating transaction-oriented systems for data entry and browsing of individual forms, EAV-modeled data is unsuitable for direct analytical processing, which is the focus of data marts. For this purpose, such data must be extracted and restructured appropriately. This paper describes how such a process, which is non-trivial and highly error prone if performed using non-systematic approaches, can be automated by judicious use of the study metadata-the descriptions of measured parameters and their higher-level grouping. The metadata, in addition to driving the process, is exported along with the data, in order to facilitate its human interpretation.

journal_name

Int J Med Inform

authors

Brandt CA,Morse R,Matthews K,Sun K,Deshpande AM,Gadagkar R,Cohen DB,Miller PL,Nadkarni PM

doi

10.1016/s1386-5056(02)00047-3

subject

Has Abstract

pub_date

2002-11-12 00:00:00

pages

225-41

issue

3

eissn

1386-5056

issn

1872-8243

pii

S1386505602000473

journal_volume

65

pub_type

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