Clinical data warehousing for evidence based decision making

Lekha Narra; Tony Sahama; Peta Stapleton

doi:10.3233/978-1-61499-512-8-329

Clinical data warehousing for evidence based decision making

Lekha Narra
, Tony Sahama
, Peta Stapleton

Faculty of Society & Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

2 Citations (Scopus)

157 Downloads (Pure)

Abstract

Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

Original language	English
Title of host publication	Digital Healthcare Empowering Europeans - Proceedings of MIE 2015
Place of Publication	Spain
Publisher	IOS Press
Pages	329-333
Number of pages	5
Volume	210
ISBN (Electronic)	9781614995111
DOIs	https://doi.org/10.3233/978-1-61499-512-8-329
Publication status	Published - 2015
Event	26th Medical Informatics in Europe Conference, MIE 2015 - Madrid, Madrid, Spain Duration: 27 May 2015 → 29 May 2015

Publication series

Name	Studies in Health Technology and Informatics
Volume	210
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	26th Medical Informatics in Europe Conference, MIE 2015
Country/Territory	Spain
City	Madrid
Period	27/05/15 → 29/05/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.3233/978-1-61499-512-8-329Licence: CC BY-NC

Clinical data warehousing for evidence based decision makingFinal published version, 232 KBLicence: CC BY-NC-ND

Cite this

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title = "Clinical data warehousing for evidence based decision making",

abstract = "Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.",

author = "Lekha Narra and Tony Sahama and Peta Stapleton",

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language = "English",

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series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

pages = "329--333",

booktitle = "Digital Healthcare Empowering Europeans - Proceedings of MIE 2015",

address = "Netherlands",

note = "26th Medical Informatics in Europe Conference, MIE 2015 ; Conference date: 27-05-2015 Through 29-05-2015",

}

Narra, L, Sahama, T & Stapleton, P 2015, Clinical data warehousing for evidence based decision making. in Digital Healthcare Empowering Europeans - Proceedings of MIE 2015. vol. 210, Studies in Health Technology and Informatics, vol. 210, IOS Press, Spain, pp. 329-333, 26th Medical Informatics in Europe Conference, MIE 2015, Madrid, Spain, 27/05/15. https://doi.org/10.3233/978-1-61499-512-8-329

Clinical data warehousing for evidence based decision making. / Narra, Lekha; Sahama, Tony; Stapleton, Peta.
Digital Healthcare Empowering Europeans - Proceedings of MIE 2015. Vol. 210 Spain: IOS Press, 2015. p. 329-333 (Studies in Health Technology and Informatics; Vol. 210).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

TY - GEN

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AU - Sahama, Tony

AU - Stapleton, Peta

PY - 2015

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N2 - Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

AB - Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

UR - https://www.scopus.com/pages/publications/84937509681

U2 - 10.3233/978-1-61499-512-8-329

DO - 10.3233/978-1-61499-512-8-329

M3 - Conference contribution

AN - SCOPUS:84937509681

VL - 210

T3 - Studies in Health Technology and Informatics

SP - 329

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BT - Digital Healthcare Empowering Europeans - Proceedings of MIE 2015

PB - IOS Press

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T2 - 26th Medical Informatics in Europe Conference, MIE 2015

Y2 - 27 May 2015 through 29 May 2015

ER -

Clinical data warehousing for evidence based decision making

Abstract

Publication series

Conference

UN SDGs

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