Text Mining Techniques for Healthcare Provider Quality Determination: Methods fo
Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons (Premier Reference Source) By Patricia Cerrito
Publisher: Medical Information Science Reference 2009-08-21 | 399 Pages | ISBN: 1605667528 | PDF | 13 MB
Useful to healthcare providers, severity indices conclude which patients are most at risk for infection as well as the intensity of illness while in the hospital. Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons discusses the general practice of defining a patient severity index for risk adjustments and comparison of patient outcomes to assess quality factors. This Premier Reference Source examines the consequences of patient severity models and investigates the general assumptions required to perform standard severity adjustment.
Table of Contents:
Chapter I: Introduction to Ranking Models
Chapter II: Data Visualization and Data Summary
Chapter III: Statistical Methods
Chapter IV: Predictive Mining Versus Statistical Methods
Chapter V: The Charlson Comorbidity Index
Chapter VI: The All Patient Refined Diagnosis Related Group
Chapter VII: Risk Adjustment Based Upon Resource Utilization
Chapter VIII: Text Mining to Define Patient Severity Index
Chapter IX: Working from Claims Data
Chapter X: Use of Risk Adjustment Models for Provider Reimbursements
Chapter XI: How to Check Measures for Adequacy
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Charlson Comorbidity Index Medical Information Science Severity Adjustment Severity Indices Patricia Cerrito Risk Adjustments Severity Index Diagnosis Related Group Mirror Mirror Determination Methods Risk Adjustment Science Reference Index Chapter Data V
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