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. 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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