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Data Sampling Methods and Strategic Decision Making Discussion Paper

 

  • 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.

    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.
      • 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:

    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.
  • SCORING GUIDE

    Use the scoring guide to understand how your assessment will be evaluated.VIEW SCORING GUIDE