Clinical Data Mining For Physician Decision Making And Investigating Health Outcomes: Methods For Prediction And Analysis, 1st Edition

  • Patricia Cerrito
  • Published By:
  • ISBN-10: 1615209069
  • ISBN-13: 9781615209064
  • DDC: 610.285
  • Grade Level Range: College Freshman - College Senior
  • 356 Pages | eBook
  • Original Copyright 2010 | Published/Released October 2011
  • This publication's content originally published in print form: 2010

  • Price:  Sign in for price

About

Overview

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.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Dedication.
Table of Contents.
Preface.
Acknowledgment.
1: Preprocessing the Data.
2: Errors and Missing Values in the Dataset.
3: Introduction to the Use of MEPS (Medical Expenditure Panel Survey).
4: Preprocessing Medpar Data.
5: Extracting Data from the National Inpatient Sample.
6: Creating a One–to–One Relationship in the Data from a Many–to–Many.
7: Merging Different Datasets to Allow for a Complete Analysis (Inpatient, Outpatient, Physician Visits, Medications).
8: Introduction to Analysis Using Time Components.
9: More Survival Data Mining of Multiple Time of Endpoints.
10: Using the Data to Define Patient Compliance.
11: Compression of Diagnosis and Procedure Codes.
12: Comparisons of Patient Severity Indices.
13: Decision Trees and Their Development: Use of Data to Determine the Quality of Care.
14: Example of Diabetes Using CMS Data.
15: Example of Breathing Illnesses, Asthma and COPD Using MEPS Data.
16: Example of Wound Care Using Medpar Data.
17: Discussion.
About the Authors.
Index.