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Creating a One-to-One Relationship in the Data from a Many-to-Many

Creating a One-to-One Relationship in the Data from a Many-to-Many

Patricia Cerrito, John Cerrito
Copyright: © 2010 |Pages: 22
ISBN13: 9781615209057|ISBN10: 1615209050|ISBN13 Softcover: 9781616923365|EISBN13: 9781615209064
DOI: 10.4018/978-1-61520-905-7.ch006
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MLA

Patricia Cerrito and John Cerrito. "Creating a One-to-One Relationship in the Data from a Many-to-Many." Clinical Data Mining for Physician Decision Making and Investigating Health Outcomes: Methods for Prediction and Analysis, IGI Global, 2010, pp.94-115. https://doi.org/10.4018/978-1-61520-905-7.ch006

APA

P. Cerrito & J. Cerrito (2010). Creating a One-to-One Relationship in the Data from a Many-to-Many. IGI Global. https://doi.org/10.4018/978-1-61520-905-7.ch006

Chicago

Patricia Cerrito and John Cerrito. "Creating a One-to-One Relationship in the Data from a Many-to-Many." In Clinical Data Mining for Physician Decision Making and Investigating Health Outcomes: Methods for Prediction and Analysis. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-905-7.ch006

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Abstract

One of the biggest problems in dealing with healthcare data is that there can be multiple patient events for the same individual. Without finding some way to combine these many observations into one row in the dataset, it is very difficult to analyze the data by patient. When dealing with cost and reimbursement information, this can be relatively simple since a total sum of costs or reimbursements can be used to examine any one patient. However, if we are looking at patient conditions, or physician decisions in sequence, this consolidation of patient information can be especially difficult. When using the technique of survival data mining, as we will discuss in later chapters, such consolidation of information is absolutely essential. In this chapter, then, we will discuss some of the requirements for combining patient information into one data row.

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