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Answer: There are numerous applications of data mining in healthcare and in its related disciplines of biotech, pharma and healthcare insurance. I see no disadvantages in the proper use of data mining. However, if planned or executed poorly, not targeting data mining efforts towards business goals or training employees to mine inadequate data, there are obvious disadvantages. You can do a lot of data mining with repetitive and elongated interactive queries, but if you can master some data mining, the analysis will be faster and, realistically, you'll open up the environment to much more analysis.
Data mining is used successfully and extensively in healthcare today. For example, I was part of a project that mined healthcare claims to determine best providers and procedures for conditions, diagnostic aids for certain procedures and protein analysis for drug development. I wrote a white paper with R. Chris Christy, Global Healthcare Marketing Director at Business Objects. It talks about the applications of business intelligence in healthcare today. Although it doesn't talk about data mining specifically, data mining is a tool in the toolbox and it does enable or assist many of the analysis mentioned in the paper.
For more about data mining
Data mining tools: Advantages and disadvantages of implementation
Is data mining reliable?
Defining web business intelligence (WBI), data mining and data warehousing
This was first published in December 2007