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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