Extended SQL for manipulating clinical warehouse data. Academic Article uri icon

Overview

MeSH

  • Clinical Laboratory Techniques
  • Health Services Research
  • Humans
  • Information Storage and Retrieval

MeSH Major

  • Data Interpretation, Statistical
  • Database Management Systems
  • Databases as Topic
  • Medical Records Systems, Computerized
  • Programming Languages

abstract

  • Health care institutions are beginning to collect large amounts of clinical data through patient care applications. Clinical data warehouses make these data available for complex analysis across patient records, benefiting administrative reporting, patient care and clinical research. Data gathered for patient care purposes are difficult to manipulate for analytic tasks; the schema presents conceptual difficulties for the analyst, and many queries perform poorly. An extension to SQL is presented that enables the analyst to designate groups of rows. These groups can then be manipulated and aggregated in various ways to solve a number of useful analytic problems. The extended SQL is concise and runs in linear time, while standard SQL requires multiple statements with polynomial performance. The extensions are extremely powerful for performing aggregations on large amounts of data, which is useful in clinical data mining applications.

publication date

  • 1999

has subject area

  • Clinical Laboratory Techniques
  • Data Interpretation, Statistical
  • Database Management Systems
  • Databases as Topic
  • Health Services Research
  • Humans
  • Information Storage and Retrieval
  • Medical Records Systems, Computerized
  • Programming Languages

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC2232585

PubMed ID

  • 10566474

Additional Document Info

start page

  • 819

end page

  • 823