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Text Mining Techniques for Healthcare Provider Quality Determination on Hardback by Patricia B Cerrito
Text Mining Techniques for Healthcare Provider Quality Determination on Hardback by Patricia B Cerrito
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Text Mining Techniques for Healthcare Provider Quality Determination

Methods for Rank Comparisons
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Description

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.

Author Biography:

Patricia Cerrito, PhD, has made considerable strides in the development of data mining techniques to investigate large, complex medical data. In particular, she has developed a method to automate the reduction of the number of levels in a nominal data field to a manageable number that can then be used in other data mining techniques. Another innovation of the PI is to combine text analysis with association rules to examine nominal data. The PI has over 30 years of experience in working with SAS software, and over 10 years of experience in data mining healthcare databases. In just the last two years, she has supervised 7 PhD students who completed dissertation research in investigating health outcomes. Dr. Cerrito has a particular research interest in the use of a patient severity index to define provider quality rankings for reimbursements.
Release date Australia
September 30th, 2009
Audiences
  • Postgraduate, Research & Scholarly
  • Professional & Vocational
Illustrations
illustrations
Pages
399
Dimensions
216x280x23
ISBN-13
9781605667522
Product ID
3245492

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