Date on Master's Thesis/Doctoral Dissertation
5-2006
Document Type
Master's Thesis
Degree Name
M.S.
Department (Legacy)
Department of Biostatistics
Committee Chair
Thompson, Caryn M.
Subject
Heart--Diseases--Patients--Rehabilitation; Data mining
Abstract
The purpose of this paper is to examine the process of text mining and using the results to show the possible benefits of cardiopulmonary rehabilitation. The 555 patients enrolled in the study were receiving inpatient cardiopulmonary rehabilitation. Each patient had comorbidity codes associated with them. These codes are secondary diagnoses to the cardiac or pulmonary event that resulted in their hospitalization. The patients had secondary conditions ranging in number from 1 to 10. The patients were assessed at admission and discharge for functional independence. Since there are numerous comorbidity codes for each patient, it would be difficult to analyze each one. Therefore, we can text mine these codes to create meaningful clusters to help in the analysis. This paper explains the process and theory of text mining and clustering. We use these results to perform statistical analysis to examine the benefits of cardiopulmonary rehabilitation.
Recommended Citation
Ferrell, Jennifer 1982-, "Text mining comorbidity codes in the analysis of cardiopulmonary rehabilitation data." (2006). Electronic Theses and Dissertations. Paper 436.
https://doi.org/10.18297/etd/436
