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What is Data Mining?

There are many advantages for healthcare professionals to implement data mining as it allows data to be studied. In order to identify inefficiencies and best practices data mining can be used to improve client care and reduce costs. Since the early 90s, data mining has been used across many industries but finally it is being utilized in healthcare.

Data Mining is the analytical process used to explore data with the aim of identifying consistent patterns and relationships between variables. Additionally subgroups of data can be created in order to present validity and patterns of the study. 

For instance, healthcare records continue to grow due to advancements in technology. So how do healthcare professionals filter through all the information efficiently? Here is where data mining has been recognized to be extremely effective. Data mining can be used to break down large data to find patterns to then be used to build predictive models

The most effective method of data mining is the Three System Approach:

1.The initial exploration – the initial stage consist of data preparation which may include data transformation, cleaning data, selecting subsets of records etc.

2.Pattern identification – the most appropriate model will have to be identified which will be used to achieve to the ultimate goal

3.Deployment – the selected model is applied to new data in order to generate predictions or estimate the expected outcome

To ensure validity, it is important that all three system approach stages are implemented as failing to do so may result in invalid data and therefore never leaving the laboratory. Applying all three enables a healthcare organization to apply data mining to everyday clinical practice.

Data mining has contributed to improving the quality of patient care and reducing healthcare costs. Join your peers at the 7th Annual Clinical Data Integration & Management conference to discuss the industries current advancements and challenges.

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