Data Mining Clinic Performance Data Analysis & Sampling Essay Discussion

Question Description
Perform data mining activities on two Excel datasets. Prepare a 4-5 page report of findings, including whether datasets accurately depict performance, the use of data sampling methods in strategic decision making, and conclusions and recommendations about improving patient service and staff performance. Include in the report the analysis of the raw data in Excel data analysis tables.Data Mining Clinic Performance Data Analysis & Sampling Essay Discussion

INTRODUCTION
Data mining is a statistical analysis process used to extract data to provide useful information. Beginning with raw data, a data analyst organizes the data, rearranges it, and then searches for patterns. After identifying the patterns, the analyst can turn the data into usable information. In this assessment you will perform data mining activities and apply the results to different uses in health care information settings.

DEMONSTRATION OF PROFICIENCY
By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:

Competency 3: Use data analysis skills to support health information integrity and data quality.Data Mining Clinic Performance Data Analysis & Sampling Essay Discussion
Analyze data samples.
Explain how to use data sampling methods and data mining to inform strategic decision making.
Recommend quality of care improvements based on statistical analysis.
Competency 4: Apply statistical strategies to analyze health care data.
Organize raw data.
Perform data mining activities.
Competency 5: Communicate in a professional manner to support health care data analytics.
Create a clear, well-organized, professional document that is generally free of errors in grammar, spelling, and punctuation.
Follow APA style and formatting guides for citations and references.
PREPARATION
You will be working with datasets in Excel spreadsheets for this assessment. Download and review these datasets now:

Dataset 1 Clinic Performance 2017 [XLSX].
Dataset 2 Nursing Performance 2016 [XLSX].
INSTRUCTIONS
As a Vila Health data analyst, you have been asked to work on a project related to customer satisfaction and nursing staff performance. You will analyze two datasets. One concerns clinic performance, specifically, patient wait times and office visit lengths. The other dataset is on nursing performance.

After analyzing these two datasets, you will compose a report for the clinic’s physicians based on your analysis.

Dataset 1: Clinic Performance
This first dataset contains raw data about clinic performance from a customer-service perspective. First, organize and analyze the raw data in Excel data analysis tables. You will include these tables in your report. Write your report about Dataset 1. Be sure to include these headings and address the bullets following each heading:

Accurate Depiction of Clinic Performance.
Explain whether the sample can accurately depict clinic performance, noting variations and patterns.
Data Sampling Methods and Strategic Decision Making.
Describe how to use data sampling methods in strategic decision making.
Conclusions and Recommendations About Clinic Physicians and Customer Service.
Draw conclusions about clinic physicians and customer service.
Make two recommendations for improving patient service based on your analysis.
Dataset 2: Nursing Staff Performance
Dataset 2 provides information on nursing staff performance on two tasks. The data show a decrease in nursing staff productivity at one Vila Health clinic in the past few months. Use the Nursing Data Worksheet and the Pivot Table Report, both contained in Dataset 2 Nursing Performance 2016, to perform data mining techniques to determine how nursing staff performed when completing Tasks 1 and 2. Organize and analyze the raw data in Excel data analysis tables. You will include these tables in your report.

Note: Be careful of filters. Be sure to check data from various years.

Write your report, including all of the following:

Data Mining Techniques to Evaluate Nursing Staff Performance on Tasks.

Explain how each of these data mining techniques can be used to evaluate nursing staff task performance:
Genetic algorithms.
Neural networks.
Predictive modeling.
Rule induction.
Decision trees.
K-Nearest neighbor.
Include examples of the use of each data mining technique in relation to the nursing data.
Data Mining and Strategic Decision Making.

Describe the use of data mining in strategic decision making.
Conclusions and Recommendations About Nursing Staff Performance.

Draw conclusions about nursing performance on tasks.
Create two recommendations for improving nursing performance.
Conclusion
Summarize the findings of your analysis of the two datasets. Draw conclusions about how the information from the datasets might be connected. For example, how might physician performance impact nursing tasks? Or what is the association between customer satisfaction and nursing task performance?

ADDITIONAL REQUIREMENTS
Format: Word document, including data analysis tables from Excel.
Length: Four to five double-spaced pages.
Font: Times New Roman, 12 point.
References and citations: Include citations and references in APA format and style.
Writing: Create a clear, well-organized, professional document that is generally free of errors in grammar, punctuation, and spelling.

You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.Data Mining Clinic Performance Data Analysis & Sampling Essay Discussion

Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.

Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.

The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.

ADDITIONAL INSTRUCTIONS FOR THE CLASS

Discussion Questions (DQ)

Initial responses to the DQ should address all components of the questions asked, include a minimum of one scholarly source, and be at least 250 words.
Successful responses are substantive (i.e., add something new to the discussion, engage others in the discussion, well-developed idea) and include at least one scholarly source.
One or two sentence responses, simple statements of agreement or “good post,” and responses that are off-topic will not count as substantive. Substantive responses should be at least 150 words.
I encourage you to incorporate the readings from the week (as applicable) into your responses.
Weekly Participation

Your initial responses to the mandatory DQ do not count toward participation and are graded separately.
In addition to the DQ responses, you must post at least one reply to peers (or me) on three separate days, for a total of three replies.
Participation posts do not require a scholarly source/citation (unless you cite someone else’s work).
Part of your weekly participation includes viewing the weekly announcement and attesting to watching it in the comments. These announcements are made to ensure you understand everything that is due during the week.
APA Format and Writing Quality

Familiarize yourself with APA format and practice using it correctly. It is used for most writing assignments for your degree. Visit the Writing Center in the Student Success Center, under the Resources tab in LoudCloud for APA paper templates, citation examples, tips, etc. Points will be deducted for poor use of APA format or absence of APA format (if required).
Cite all sources of information! When in doubt, cite the source. Paraphrasing also requires a citation.
I highly recommend using the APA Publication Manual, 6th edition.
Use of Direct Quotes

I discourage overutilization of direct quotes in DQs and assignments at the Masters’ level and deduct points accordingly.
As Masters’ level students, it is important that you be able to critically analyze and interpret information from journal articles and other resources. Simply restating someone else’s words does not demonstrate an understanding of the content or critical analysis of the content.
It is best to paraphrase content and cite your source.
LopesWrite Policy

For assignments that need to be submitted to LopesWrite, please be sure you have received your report and Similarity Index (SI) percentage BEFORE you do a “final submit” to me.
Once you have received your report, please review it. This report will show you grammatical, punctuation, and spelling errors that can easily be fixed. Take the extra few minutes to review instead of getting counted off for these mistakes.
Review your similarities. Did you forget to cite something? Did you not paraphrase well enough? Is your paper made up of someone else’s thoughts more than your own?
Visit the Writing Center in the Student Success Center, under the Resources tab in LoudCloud for tips on improving your paper and SI score.
Late Policy

The university’s policy on late assignments is 10% penalty PER DAY LATE. This also applies to late DQ replies.
Please communicate with me if you anticipate having to submit an assignment late. I am happy to be flexible, with advance notice. We may be able to work out an extension based on extenuating circumstances.
If you do not communicate with me before submitting an assignment late, the GCU late policy will be in effect.
I do not accept assignments that are two or more weeks late unless we have worked out an extension.
As per policy, no assignments are accepted after the last day of class. Any assignment submitted after midnight on the last day of class will not be accepted for grading.
Communication

Communication is so very important. There are multiple ways to communicate with me:
Questions to Instructor Forum: This is a great place to ask course content or assignment questions. If you have a question, there is a good chance one of your peers does as well. This is a public forum for the class.
Individual Forum: This is a private forum to ask me questions or send me messages. This will be checked at least once every 24 hours.