The purpose of this assignment is to create a visual for displaying data. Use the data from the Tableau VLab Activity to create a visual representation of the data in the form of a report, chart, or graph. Include a brief rationale explaining how the data were organized and used in the creation of the visualization and why you chose the specific visual element. For your reference, please click the link below: https://www.cms.gov/Research-Statistics-Data-and-Systems/Monitoring-Programs/Medicare-FFS-Compliance-Programs/CERT/Downloads/2017-Medicare-FFS-Improper-Payment.pdf
Creating a visual representation of data is an essential aspect of data analysis and reporting. In this assignment, the goal is to use the data provided in the Tableau VLab Activity to create a visual element, such as a report, chart, or graph, to present the information effectively. This report will convey the findings in a concise and visually appealing manner, allowing users to understand and interpret the data easily.
To begin, it is important to consider how the data should be organized to facilitate meaningful insights. The data from the Tableau VLab Activity is sourced from the 2017 Medicare FFS Improper Payment Report, published by the Centers for Medicare and Medicaid Services (CMS). This report provides information on the rate of improper payments made within the Medicare Fee-for-Service (FFS) program. The report contains data on various categories of improper payments, such as documentation errors, medically unnecessary services, and coding errors.
In organizing the data, it would be prudent to first categorize the improper payment types and calculate their respective rates. This can be achieved by aggregating the data according to payment type and determining the ratio between improper payments and total payments made for each category. By presenting this information, users will gain an understanding of the relative prevalence of different types of improper payments within the Medicare FFS program.
Next, it would be valuable to analyze the improper payment rates based on specific provider types. The CMS report provides data on improper payment rates for different providers, such as hospitals, nursing homes, and home health agencies. By aggregating the data by provider type and visualizing the rates, users can identify patterns and discrepancies among different providers. This analysis can help target interventions and strategies to reduce improper payments and enhance program integrity.
Choosing the appropriate visual element is crucial in effectively conveying the data and facilitating understanding. Considering the nature of the data, a combination of bar charts and line graphs may be effective in presenting the information. Bar charts can be utilized to display the rates of improper payments for each payment category, enabling easy comparison between different types of improper payments. Additionally, line graphs can be employed to illustrate the trends in improper payment rates over time, highlighting any changes or patterns.
The rationale for selecting bar charts is rooted in their ability to represent categorical data and comparisons visually. With the categories of improper payments on the x-axis and the corresponding rates on the y-axis, bar charts allow for quick and straightforward comparisons between different improper payment types. This visual element enables users to discern which categories have the highest rates, aiding in the identification of areas requiring targeted interventions.
The use of line graphs complements the bar charts by presenting the trends in improper payment rates over time. The x-axis of the line graph would represent the timeline, while the y-axis would indicate the improper payment rate. By connecting the data points with lines, users can easily observe changes in the rates over time, providing insights into the effectiveness of interventions and program improvements.
Overall, by organizing the data based on improper payment types and provider types, and using a combination of bar charts and line graphs to visually represent the information, the visualization will effectively convey the findings of the 2017 Medicare FFS Improper Payment Report. This approach will enhance understanding and interpretation of the data, facilitating informed decisions and interventions to mitigate improper payments within the Medicare FFS program.