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Clinical data mining for physician d...

Cerrito, John, (1954-)

Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Clinical data mining for physician decision making and investigating health outcomesPatricia Cerrito, John Cerrito.
Reminder of title:	methods for prediction and analysis /
other author:	Cerrito, John,
Published:	Hershey, Pa. :IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA),c2010.
Description:	1 online resource (351 p.) :ill.
Subject:	Medical informatics.
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-61520-905-7
ISBN:	9781615209064 (ebook)

Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /
Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /[electronic resource] :Patricia Cerrito, John Cerrito. - Hershey, Pa. :IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA),c2010. - 1 online resource (351 p.) :ill.

Includes bibliographical references.

Preprocessing the data -- Errors and missing values in the dataset -- Introduction to the use of MEPS (medical expenditure panel survey) -- Preprocessing Medpar data -- Extracting data from the national inpatient sample -- Creating a one-to-one relationship in the data from a many-to-many -- Merging different datasets to allow for a complete analysis (inpatient, outpatient, physician visits, medications) -- Introduction to analysis using time components -- More survival data mining-multiple time of endpoints -- Using the data to define patient compliance -- Compression of diagnosis and procedure codes -- Comparisons of patient severity indices -- Decision trees and their development -- Example of diabetes using CMS data -- Example of breathing illnesses, asthma and COPD using MEPS data -- Example of wound care using Medpar data -- Discussion.

Restricted to subscribers or individual electronic text purchasers.

The investigation of healthcare databases can be used to examine physician decisions and develop evidence-based treatment guidelines that optimize patient outcomes. This book demonstrates how concern for detail in datasets and the use of data mining techniques can extract important and meaningful knowledge from healthcare databases. Basic information on processing data with step-by-step instructions is provided, allowing readers to use their own data and follow the instructions to find meaningful results.

Mode of access: World Wide Web.

ISBN: 9781615209064 (ebook)

LCCN: 2010006306Subjects--Topical Terms:

196487
Medical informatics.

LC Class. No.: R859.7.D36 / C55 2010e

Dewey Class. No.: 610.285

National Library of Medicine Call No.: W 26.55.I4 / C6415 2010e

Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /
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020 $a 9781615209064 (ebook)
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050 4 $a R859.7.D36 $b C55 2010e
060 4 $a W 26.55.I4 $b C6415 2010e
082 0 4 $a 610.285 $2 22
245 0 0 $a Clinical data mining for physician decision making and investigating health outcomes $h [electronic resource] : $b methods for prediction and analysis / $c Patricia Cerrito, John Cerrito.
260 $a Hershey, Pa. : $b IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), $c c2010.
300 $a 1 online resource (351 p.) : $b ill.
504 $a Includes bibliographical references.
505 0 $a Preprocessing the data -- Errors and missing values in the dataset -- Introduction to the use of MEPS (medical expenditure panel survey) -- Preprocessing Medpar data -- Extracting data from the national inpatient sample -- Creating a one-to-one relationship in the data from a many-to-many -- Merging different datasets to allow for a complete analysis (inpatient, outpatient, physician visits, medications) -- Introduction to analysis using time components -- More survival data mining-multiple time of endpoints -- Using the data to define patient compliance -- Compression of diagnosis and procedure codes -- Comparisons of patient severity indices -- Decision trees and their development -- Example of diabetes using CMS data -- Example of breathing illnesses, asthma and COPD using MEPS data -- Example of wound care using Medpar data -- Discussion.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a The investigation of healthcare databases can be used to examine physician decisions and develop evidence-based treatment guidelines that optimize patient outcomes. This book demonstrates how concern for detail in datasets and the use of data mining techniques can extract important and meaningful knowledge from healthcare databases. Basic information on processing data with step-by-step instructions is provided, allowing readers to use their own data and follow the instructions to find meaningful results.
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
650 0 $a Medical informatics. $3 196487
650 0 $a Data mining. $3 184440
650 0 $a Evidence-based medicine $x Data processing. $3 695403
650 1 2 $a Data Mining. $3 304461
650 1 2 $a Medical Informatics Computing. $3 501930
650 2 2 $a Database Management Systems. $3 240222
650 2 2 $a Decision Making. $3 396970
650 2 2 $a Evidence-Based Medicine. $3 208980
700 1 $a Cerrito, John, $d 1954- $3 695402
700 1 $a Cerrito, Patricia B. $3 482548
856 4 8 $3 Chapter PDFs via platform: $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-61520-905-7