Pivoting approaches for bulk extraction of Entity-Attribute-Value data

Valentin Dinu, Prakash Nadkarni, Cynthia Brandt

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Entity-Attribute-Value (EAV) data, as present in repositories of clinical patient data, must be transformed (pivoted) into one-column-per-parameter format before it can be used by a variety of analytical programs. Pivoting approaches have not been described in depth in the literature, and existing descriptions are dated. We describe and benchmark three alternative algorithms to perform pivoting of clinical data in the context of a clinical study data management system. We conclude that when the number of attributes to be returned is not too large, it is feasible to use static SQL as the basis for views on the data. An alternative but more complex approach that utilizes hash tables and the presence of abundant random-access-memory can achieve improved performance by reducing the load on the database server.

Original languageEnglish (US)
Pages (from-to)38-43
Number of pages6
JournalComputer Methods and Programs in Biomedicine
Issue number1
StatePublished - Apr 2006
Externally publishedYes


  • Clinical patient record systems
  • Clinical study data management systems
  • Databases
  • Entity-Attribute-Value

ASJC Scopus subject areas

  • Software
  • Health Informatics
  • Computer Science Applications


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