Data Mining

As a data analyst for Vila Health, you have been asked to work on a project related to customer satisfaction and nursing staff performance. You will analyze two data sets and compose a report for the clinic’s physicians based on your analysis. In your closing report, draw conclusions about how the information from the data sets can be connected. For example, can the physician’s performance impact nursing tasks? Or, is there an association between customer satisfaction and nursing task performance?

Data set 1: Clinic Performance linked in the Resources, contains raw data about performance at your clinic from a customer service perspective.

Organize and analyze the raw data.
Draw conclusions about clinic physicians and customer service.
Explain if the sample can provide an accurate depiction of clinic performance, noting variations and patterns.
Describe how to use data sampling methods in strategic decision-making.
Create two recommendations for improving patient service based on the results of your analysis.

Data set 2: Nursing Data Worksheet linked in the Resources, provides information on nursing staff performance on two tasks. The data shows that there has been a decrease in productivity for the nursing staff at one of the Vila Health clinics in the past few months. Using the Nursing Data Worksheet and the pivot table report, complete the following:

Perform data mining techniques to determine how the nursing staff performed when completing Task 1 and Task 2.
Discuss data mining tools. Provide a brief summary of data mining techniques that can be used to evaluate the nursing staff tasks. Include a description of how each technique can be used to help determine or detect in health care, including an example of the use of each data mining technique in relation to the nursing data.
Genetic algorithms.
Neural networks.
Predictive modeling.
Rule induction.
Fuzzy logic.
Decision trees.
K-nearest neighbor.
Describe the use of data mining in strategic decision-making.

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