A STATISTICAL LOOK AT COPD

Author(s)

Patricia B Cerrito, PhD, Professor, Paul Augustus, N/A, StudentUniversity of Louisville, Louisville, KY, USA

Objective: The purpose of this paper is to take an analytical view of the diagnosis and procedures that most frequently occur with Chronic Obstructive Pulmonary Disease (COPD) patients when they are admitted to the hospital. Methods: The data was collected from the National Inpatient Sample (NIS); they were analyzed using the SAS Program Enterprise Guide 4. The data were from over 32,000 patients that were diagnosed with some type of COPD using a 10% sample from 2004. Some of the variables examined were: the age, the length of stay, mortality rates, total charges, and the diagnostic, and procedure codes for the patients. In analyzing the data, codes were compressed to filter the top 20 principle diagnosis codes, the top 20 procedure codes, and the top twenty DRG codes. Results: The results of the data analysis show that there are many different principal diagnoses, procedures, and DRG's used when patients come to the hospital with COPD. The highest principal diagnosis is COPD and bronchiectasis, the top procedure is classified as other vascular catheterization, and the top DRG in effect on the discharge date is COPD. The results also show that 5% of the patients died while they were in the hospital. The total charges for the patients show that the majority of the patients' total charges were less than $10,000. Logistic regression showed that mortality is directly related to these diagnostic and procedure codes. Conclusion: More research on COPD is necessary. COPD is the fourth leading cause of death in the US, but there is virtually no research on the disease. The analysis of this dataset shows that the knowledge of this disease is limited and more research must be conducted.

Conference/Value in Health Info

2008-05, ISPOR 2008, Toronto, Ontario, Canada

Value in Health, Vol. 11, No. 3 (May/June 2008)

Code

PRS35

Topic

Epidemiology & Public Health, Specialized Treatment Areas

Topic Subcategory

Disease Classification & Coding, Personalized & Precision Medicine

Disease

Respiratory-Related Disorders

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