Clinical data mining for physician decision making and investigating health outcomes
Clinical data mining for physician decision making and investigating health outcomes methods for prediction and analysis
Patricia Cerrito, John Cerrito, editors.
- Hershey, PA Medical Information Science Reference c2010.
- xiv, 356 p. ill. 29 cm.
"Premier Reference Source" --Cover.
Includes bibliographical references and index.
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 of 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 : use of data to determine the quality of care -- Example of diabetes using CMS data -- Example of breathing illness, asthma and COPD using MEPS data -- Example of wound care using Medpar data.
"This book shows how the investigation of healthcare databases can be used to examine physician decisions to develop evidence-based treatment guidelines that optimize patient outcomes"--Provided by publisher.
9781615209057 (h/c) 1615209050 (h/c)
2010006306
Medical informatics
Evidence-Based Medicine--Data processing.
Data mining
R859.7.D36 / C47 2010
610.285 / C6413
W 26.55.I4 / C6415 2010
"Premier Reference Source" --Cover.
Includes bibliographical references and index.
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 of 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 : use of data to determine the quality of care -- Example of diabetes using CMS data -- Example of breathing illness, asthma and COPD using MEPS data -- Example of wound care using Medpar data.
"This book shows how the investigation of healthcare databases can be used to examine physician decisions to develop evidence-based treatment guidelines that optimize patient outcomes"--Provided by publisher.
9781615209057 (h/c) 1615209050 (h/c)
2010006306
Medical informatics
Evidence-Based Medicine--Data processing.
Data mining
R859.7.D36 / C47 2010
610.285 / C6413
W 26.55.I4 / C6415 2010