Patient Satisfaction Analysis
To become proficient in statistical reasoning, you need to be able to interpret data from surveys. This includes preparing frequency tables and graphs, as well as histograms.
Imagine you are an intern with a community clinic. Your organization conducted a survey regarding patient satisfaction. Your supervisor has given you the original survey and the survey results and asked you to prepare a summary including the following:
- Frequency table
- Histogram
- A frequency bar graph
- A summary describing the trends and/or patterns observed in the data
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Patient Satisfaction Analysis
Creating the Frequency Table
The first step in analyzing survey data is to organize the responses in a frequency table. This displays each satisfaction level (e.g., very satisfied, satisfied, neutral, dissatisfied, very dissatisfied) along with the number of responses for each category. Frequency tables help summarize large sets of data quickly and highlight where most responses fall. It gives a clear view of how patients rated their experience.
Visualizing with Histograms
A histogram is used to show how frequently data points occur within certain ranges. In this case, patient satisfaction ratings are grouped and displayed as bars. The height of each bar represents the number of patients who selected a particular rating. Histograms are especially useful for showing patterns such as skewness or concentration in the responses, helping identify whether satisfaction is generally high or low.
Using a Frequency Bar Graph
A bar graph provides a simple, visual comparison of satisfaction levels. Unlike histograms, bar graphs include gaps between bars and are ideal for categorical data. Each bar represents a satisfaction category and its frequency. This visual tool makes it easy for stakeholders to see which ratings were most common and where improvements may be needed.
Observing Data Trends
From the visuals and frequency table, we can identify trends. For example, if most patients rated their experience as “satisfied” or “very satisfied,” the clinic is performing well. A noticeable number of “dissatisfied” responses may signal areas needing improvement. Analyzing these trends helps the clinic adjust services to enhance patient care and satisfaction.
