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Clinical data mining for physician decision making and investigating health outcomes = methods for prediction and analysis /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Clinical data mining for physician decision making and investigating health outcomes/ Patricia 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 outcomes = methods 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:

583858
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 outcomes = methods for prediction and analysis /
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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 583858
650 0 $a Data mining. $3 528622
650 0 $a Evidence-based medicine $x Data processing. $3 1002301
650 1 2 $a Data Mining. $3 572983
650 1 2 $a Medical Informatics Computing. $3 788375
650 2 2 $a Database Management Systems. $3 1002302
650 2 2 $a Decision Making. $3 789088
650 2 2 $a Evidence-Based Medicine. $3 583161
700 1 $a Cerrito, John, $d 1954- $3 1002300
700 1 $a Cerrito, Patricia B. $3 864949
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