C207 Task 2

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Western Governors University *

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C207

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Statistics

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May 24, 2024

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C207 Data-Driven Decision Making Task 2 Julie Henson WGU

A. Summary of Situation The situation we will be analyzing is whether a small-town surgical services team is able to provide surgical case turnover times that are within the national norm. The information being gathered is from the institution's last year of surgical cases in 2021. Is there a significant difference between average surgical case turnover times and the standard surgical case turnover time of 15 minutes? Analyzing situation would benefit the institution by revealing the case turnover times for future use to improve case turnover efficiency, if need be, and to ensure the surgical team is functioning efficiently. If the turnover times are below average or more than the 15-minute standard, the data could be utilized to improve the turnover times by utilizing ideas to increase the turnover and a performance improvement measure could be put into place. B1. Summary of Data The data will be collected using the institution's surgical case turnover times for the year 2021. To assure data reliability, a minimum of 30 surgical case turns will be obtained from the institution's surgical case record. The times will be collected in minutes and chosen at random throughout the year. This randomly collected data should ensure a sound analysis for the research. In return, this will provide results that will influence future decisions and performance measures for the team. B2. Graphical Display A bar chart was chosen to display the random case turnover times chosen from the surgical case log for the year 2021. The information was obtained and placed in an excel spreadsheet. At that point, the software constructed this bar chart to provide a more visual image of the data. Visualizing this chart makes the raw data much more appealing and understandable with a quick glance versus a bunch of numbers and lines on an excel spreadsheet. Utilizing this chart will provide the surgical team and administration with understandable and reliable results of the research.

C1. Description of Analysis Technique The statistical method that will be used to examine the data acquired is the one sample t- Test Analysis. This method will provide credible proof as to whether surgical case turnover times are within the average 15-minute range by comparing the mean. This data analysis technique was selected to demonstrate whether surgical case turnover times were within range of the average 15-minute standard. The one sample t-Test is an appropriate choice for analysis of this data because we can use the mean of the data collected to compare with the average standard time mean. C2. Output and Calculations The Excel data analysis results are listed below. As stated previously, the one sample t- Test is used to determine the mean of the data collected compared with the average standard mean time. This is used for one group and one standard. The alpha used is 0.05. See below for the Excel data analysis.

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t-Test: Two-Sample Assuming Unequal Variances Minutes Standard Mean 14.46666667 15 Variance 25.42988506 0 Observations 30 30 Hypothesized Mean Diffe 0 df 29 t Stat -0.57927816 P(T<=t) one-tail 0.283437251 t Critical one-tail 1.699127027 P(T<=t) two-tail 0.566874502 t Critical two-tail 2.045229642 C3. Justification of Analysis Technique I used the one sample t-Test due to only comparing one group and one standard. This analysis is the best way to determine the mean of the group and standard using the Excel data analysis. The analysis utilizes an alpha of 0.05. I will analyze the absolute value of the t Stat with the t Critical two tail along with the P value. This analysis will determine if there is a significant difference and if my hypothesis shall be accepted or rejected by knowing if my case turnover is within range of the standard. D1. Data Analysis Results As shown above, the Excel data analysis technique found that there is no significant difference between the surgical case turnovers and the standard of 15 minutes. This is evidenced by the results of the absolute value of the t Stat (0.5) being less than my t Critical of 2.04. The P value is also greater than 0.05 which also reveals that the results are not significant. Utilizing this data along with the P value, we determine as previously stated that the null hypothesis is not significant and will be accepted. D2. Data Analysis Limitations This data analysis is an interesting technique. However, I can think of a major limitation that could affect the analysis. The limitation which comes to mind is that the data is from a rural surgical department which only performs a small number of cases. By analyzing a small

department with few case turnovers and volume it worries me that the data is not along the same lines as a huge surgical department with numerous cases, surgeons, and case types. The other limitation is that within a small surgical department, the case types are smaller and require less room setup, breakdown, and staff. All these limitations may seem to alter the analysis versus a larger institution. D3. Recommended Course of Action Although the results of the analysis were within range, I feel that the surgical case turnovers shall remain under watch. I feel the case turnover times play a huge part in patient and surgeon satisfaction. I recommend that the analysis be repeated quarterly as a quality assurance measure. With the measure being performed quarterly, the administration and staff will be aware of the trends which will allow everyone be mindful and strive for excellence.

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