Data mining is an analytical process used to extract data for the purpose of providing information. In this assessment, you will perform data mining activities and apply the results to different uses in health care information settings.
Preparation
You will be working with data sets in Excel spreadsheets for this assessment. Download and review these data sets now:
Dataset 1 Clinic Performance 2017 [XLS].
Dataset 2 Nursing Performance 2016 [XLS].
Instructions
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: The Clinic Performance spreadsheet 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 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.
Additional Requirements
Written communication: Written communication should be clear and generally free of grammatical errors.
Format: Word document including data analysis tables from Excel.
APA formatting: Use APA style and format for the paper, references, and citations.
Length of paper: Five pages.
Font and font size: Times New Roman, 12 points.
Competencies Measured
By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:
Competency 1: Interpret health care data.Organize raw data.
Interpret variations in data samples by recognizing patterns through data mining techniques.
Competency 3: Use data analysis tools and privacy concepts to support health information integrity and data quality.Perform data mining activities.
Analyze data samples.
Discuss data mining tools.
Competency 4: Apply statistical strategies to analyze health care data.Describe the use of data sampling methods and data mining in strategic decision-making.
Competency 5: Communicate in a professional manner to support health care data analytics.Create a document that is clearly written and generally free of grammatical errors.
Follow APA style and formatting guidelines for references and citations.
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