As discussed in this weeks readings, data warehousing is a method of data storage that allows for streamlined data management and retrieval. Data mining software aids in clarifying the relationships between stored data and assists in retrieving specific information as needed. In health care organizations, the information this process yields can be used to cut costs and improve patient care.
For this Discussion, you explore the concept of data mining from a health care perspective.
To prepare:
- What are the potential benefits of using data mining in health care?
- Review the information in the Learning Resources on the different types of data warehousing and how the one selected impacts data mining.
- Review the Hey article, The Next Scientific Revolution. Consider how data mining through machine learning can be applied to health care.
- Reflect on the information on data mining provided in Section 13.6.1 in the course text, Coronel, C. & Morris, S. (2015). Database systems: Design, implementation, and management (11th ed.). Stamford, CT: Cengage Learning, and consider how it connects to the content in the Hey article. According to the text, are the data mining techniques Hey describes guided or automated?
- Using the Walden Library, locate at least one specific example of each type of data mining (guided and automated) in health care. The examples you identify should be different from the examples discussed in the Hey article.
- Reflect on your initial impressions of automated data mining in health care. What are your thoughts on applying this type of data mining to patient care? Consider possible drawbacks of both guided and automated data mining. What approaches and strategies could be used to address those concerns?
- Consider any ethical ramifications of using data mining or machine learning as a tool for prognosis.
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