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. This book discusses the general practice of defining a patient severity index for risk adjustments and comparison of patient outcomes to assess quality factors.
Über den Autor
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.
Inhaltsverzeichnis
Central limit theorem Hospital reimbursements Kernel density estimation Introduction to ranking models Patient severity index Predictive modeling based on providers Predictive modeling in SAS enterprise miner Provider quality measures Risk adjustment based upon resource utilization Risk adjustment models for provider reimbursements Statistical examination of the Charlson Index Text mining to define patient severity
Klappentext
The quest for quality in healthcare has led to attempts to develop models to determine which providers have the highest quality in healthcare, with the best outcomes for patients. Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons discusses the general practice of defining a patient severity index in order to make risk adjustments to compare patient outcomes across multiple providers with the intent of ranking the providers in terms of quality. This innovative reference source, valuable to medical practitioners, researchers, and academicians, brings together research from across the globe focusing on how severity indices are generally defined when determining the best outcome for patient care.
