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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 healthcare decision.
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).
Walkthrough: You may view the Predicting an Outcome Using Regression Models Walkthrough to help you prepare for your assessment.
Hospital administration needs to make a decision on the amount of reimbursement required to cover expected costs for next year. Hospital administration is considering value-based reimbursement and needs to decide whether to accept a value-based reimbursement contract based on their expected costs. The administrators need to determine if this is a viable strategy and what action needs to occur to make this a viable strategy.
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 healthcare 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). Write a recommendation to determine if a value-based contract should be accepted and what actions should be taken to support the decision. Refer to the Copy From Excel to Another Office Program resource for instructions.
Submit both the Word document and the Excel file that shows the results.
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