MHA-FP5017 Assessment 3 Predicting an Outcome Using Regression Models

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Assignment 3- Predicting an Outcome Using Regression Models

Overview

Perform multiple regression on the relationship between hospital costs and patient age, risk factors, and patient satisfaction scores, and then generate a prediction to support this health care decision. Write a 3–4-page analysis of the results in a Word document and insert the test results into this document.

Note: You are strongly encouraged to complete the assessments in this course in the order they are presented.

Regression is an important statistical technique for determining the relationship between an outcome (dependent variable) and predictors (independent variables). Multiple regression evaluates the relative predictive contribution of each independent variable on a dependent variable. The regression model can then be used for predicting an outcome at various levels of the independent variables. For this assessment, you will perform multiple regression and generate a prediction to support a health care decision.

By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria:

• Competency 2: Analyze data using computer-based programming and software.
  • Perform the appropriate multiple regression using a dataset.
• Competency 3: Interpret results of data analysis for value-based health care decisions, policy, or practice.
  • Interpret the statistical significance and effect size of the regression coefficients of a data analysis.
  • Interpret the fit of the regression model for prediction of a data analysis.
• Competency 4: Present results of data analysis to support a decision or recommendation.
  • Apply the statistical results of the multiple regression of a data analysis to support a health care decision.
  • Write a narrative summary of the results that includes practical, administration-related implications of the multiple regression.
• Competency 5: Communicate audience-appropriate health management content in a logically structured and concise manner, writing clearly with correct use of grammar, punctuation, spelling, and APA style.
  • Write clearly and concisely, using correct grammar, mechanics, and APA formatting.

Resources

Multiple Linear Regression

• Casson, R. J., & Farmer, L. D. M. (2014). Understanding and checking the assumptions of linear regression: A primer for medical researchers. Clinical & Experimental Ophthalmology, 42(6), 590–596.
• Frey, B. B. (Ed.). (2018). Multiple linear regression. In The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1–4). Thousand Oaks, CA: Sage.
• Katz, M. H. (2003). Multivariable analysis: A primer for readers of medical research. Annals of Internal Medicine, 138(8), 644–650.
• Multiple Regression in Microsoft Excel.
• Statsoft.com. (n.d.). How to find relationship between variables, multiple regression. Retrieved from http://www.statsoft.com/Textbook/Multiple-Regressi…

Regression Analysis

• Gallo, A. (2015, November 04). A refresher on regression analysis. Harvard Business Review Digital Articles, 2–9.
• SCSUEcon. (2011, August 20). Linear regression in Excel [Video] | Transcript. Retrieved from
• Using Regression Analysis Every Day.

Effect Size

• Sullivan, G. M. (2012). FAQs about effect size. Journal of Graduate Medical Education, 4(3), 283–284. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC34441…
• Sullivan, G. M., & Feinn, R. (2012). Using effect size—or why the P value is not enough. Journal of Graduate Medical Education, 4(3), 279–282.

Predictive Analytics

• Davenport, T. H. (2014, September 02). A predictive analytics primer. Harvard Business Review Digital Articles, 2–4.
• IntroToIS BYU. (2016, November 04). Creating a multiple linear regression predictive model in Excel [Video] | Transcript. Retrieved from

Textbook

• Kros, J. F., & Rosenthal, D. A. (2016). Statistics for health care management and administration: Working with Excel (3rd. ed.). San Francisco, CA: Jossey-Bass. Available in the courseroom via the VitalSource Bookshelf link.

Assessment Instructions

Preparation

Download the Assessment 3 Dataset [XLSX].

The dataset contains the following variables:

• cost (hospital cost in dollars) .
• age (patient age in years) .
• risk (count of patient risk factors).
• satisfaction (patient satisfaction score percentile rank) .

Instructions

Hospital administration needs to make a decision on the amount of reimbursement required to cover expected costs for next year. For this assessment, using information on hospital discharges from last year, perform multiple regression on the relationship between hospital costs and patient age, risk factors, and patient satisfaction scores, and then generate a prediction to support this health care decision. Write a 3–4-page analysis of the results in a Word document and insert the test results into this document (copied from the output file and pasted into a Word document). Refer to Copy From Excel to Another Office Program for instructions.

Submit both the Word document and the Excel file that shows the results.

Grading Criteria

The numbered assessment instructions outlined below correspond to the grading criteria in the Predicting an Outcome Using Regression Models Scoring Guide, so be sure to address each point. You may also want to review the performance-level descriptions for each criterion to see how your work will be assessed.

• Perform the appropriate multiple regression using a dataset.
• Interpret the statistical significance and effect size of the regression coefficients of a data analysis.
  • Interpret p-value and beta values.
• Interpret the fit of the regression model for prediction of a data analysis.
  • Interpret R-squared and goodness of fit.
• Apply the statistical results of the multiple regression of a data analysis to support a health care decision.
  • Generate a prediction with regression equation.
• Write a narrative summary of the results that includes practical, administration-related implications of the multiple regression.
• Write clearly and concisely, using correct grammar, mechanics, and APA formatting.

Additional Requirements

Your assessment should meet the following requirements:

• Written communication: Write clearly, accurately, and professionally, incorporating sources appropriately.
• Length: 3–4 pages
• Resources: Not required.
• APA format: Cite your sources using current APA format.
• Font and font size: Times Roman, 10 point.

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