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Activity: Orientation to Data Analytics

Link to Activity:


Learning objectives

1. Analyze data to identify trends (4)

2. Utilize technology for data collection, storage, analysis, and reporting of information (3)

3. Analyze statistical data for decision making (4)

Prerequisites

1. Use of Microsoft Excel® is required to complete this activity

2. This activity is the first activity in a sequential 5-activity series.

Student instructions

1. If you have questions about this activity, please contact your instructor for assistance.

2. You will review the de-identified chart that accompanies this activity. Your instructor has provided you with a link to the
Orientation to Data Analytics I (BS) activity. Click on
2: Launch EHR to review the patient chart and begin this activity.

3. Refer to the patient chart and any suggested resources to complete this activity.

4. Document your answers directly on this activity document as you complete the activity. When you are finished, you will save this activity document to your device and upload this activity document with your answers to your Learning Management System (LMS).

Introduction

This activity will evaluate a microbiology report of culture and sensitivity results for various microbes and antibiotics. Microsoft Excel® will be used to analyze and compile the data to draw meaningful conclusions.
You do not need to turn in the pivot tables you will create in this activity to your instructor. You will only turn in your answers to the questions below.

The activity

Foundational learning




Review the resource,
About Culture & Sensitivity Screening
(found under 1: Overview & Resources along with this activity document) and answer the following questions.

1. Why is a sensitivity analysis done?

2. What is needed for a sensitivity analysis?

3. How is the sensitivity analysis performed?

4. What does susceptible mean in a sensitivity analysis?

5. What does intermediate mean in a sensitivity analysis?

6. What does resistant mean in a sensitivity analysis?

Application

Review the

Culture & Sensitivity (C&S) Report
on the Notes Tab of the de-identified EHR that accompanies this activity under 2: Launch EHR and answer the following questions.

7. What was the specimen used in this C&S?

8. What organism was cultured from this specimen?

9. Which antibiotics were tested against this specimen?

10. Based on the
Culture & Sensitivity (C&S) Report in the EHR, which antibiotic(s) should the provider prescribe for this patient, and why?

Data organization & analysis

The General Hospital is conducting an internal review of the culture and sensitivity results from patients treated for infections of the urine, blood, and sputum over the last year. A report has been generated of all cultures positive for either E. coli, Streptococcus, or K. pneumoniae bacteria and the antibiotics these bacteria were sensitive to.
Open the resource

Mass Sensitivities Export

(found under 1: Overview & Resources along with this activity document) in Microsoft Excel®. A file with 5 columns of data will open. Follow the steps described below to analyze the data, then answer the related questions.

Notice that it’s difficult to see trends in the data just by viewing the data points (rows of data in the file). Pivot tables will be used to compile and summarize the data for each variable.

· Click and drag from on field 1A to field 1100E to highlight and select all of the data.

· Go to
Insert then
PivotTable. Leave the default settings and select
OK.

The pivot table building tool will open in a new tab.

First, determine which antibiotic is most effective (Susceptible) for each type of specimen. To do so, look at the number of susceptible results for each antibiotic by specimen type. A table with each specimen as a row and each antibiotic as the column is one way to view these data. To make this table:

· Click and drag the Susceptibilities field to the Filters area. This will allow view of only the Susceptible (effective) results.

· Click and drag the Specimen field to the Rows area. This will display each specimen as a row in the table.

· Click and drag the Antibiotics field to the Columns area. This will display each antibiotic as a column in the table.

· Click and drag the Susceptibilities field to the ∑ Values area. It should then appear as ‘Count of Susceptibilities’. This will populate the table with the total number of susceptibilities for each combination of specimen and antibiotic.

The resulting table should appear as follows:

Only display the results that have a Susceptibilities result of ‘Susceptible’ (meaning the antibiotic was effective). To do so:

· Select the dropdown arrow in cell B1 where it currently says ‘(All)’.

· Choose
Select Multiple Items and remove the checks so that only ‘Susceptible’ is checked. Then
OK.

Based on the resulting pivot table, answer questions 11-13 below by determining which antibiotic has the highest susceptibility count for each specimen type. Then answer questions 14-15 based on the Grand Total for each antibiotic.

Questions

11. Which antibiotic is most effective in urine-based infections? Explain.

12. Which antibiotic is most effective in blood-based infections? Explain.

13. Which antibiotic is most effective in sputum-based infections? Explain.

14. Which antibiotic is most effective overall? Explain. 

15. Which antibiotic is least effective overall? Explain. 

Now, determine which specimen has the most resistance for each type of microbe. To do so, change the Susceptibilities filter in cell B1 from ‘Susceptible’ to ‘Resistant’. Answer question 16 below.

Question

16. Which type of specimen has the most resistance? Explain. 

Next, assess which antibiotic is most effective for the various types of infections. Return to the Culture & Sensitivity Data tab and create a new pivot table. If your columns aren’t already selected, repeat that step and then choose
Insert and
PivotTable and
OK.

· Click and drag the ‘Susceptibilities’ field to the Filters area. This will allow the susceptible (effective) results to be isolated.

· Click and drag the ‘Specimen’ field to the Filters area. This will allow the type of specimen for the results to also be isolated.

· Click and drag the ‘Antibiotics’ field to the Columns area. This will display each antibiotic type as a column in the table.

· Click and drag the ‘Microbes’ field to the Rows area. This will display each microbe type as a row in the table.

· Click and drag the ‘Susceptibilities’ field to the ∑ Values area. This will populate the table with the total number of susceptibilities for each microbe and antibiotic combination.

· Specify the susceptibility of ‘Susceptible’ in cell B1 to display only the effective results.

· Specify the specimen of ‘Urine’ in cell B2 to display only the results for urine.

Use the results in the pivot table to answer question 17 below.

Question

17. Which antibiotic would you recommend be tried with a urine-based E. coli infection? Explain. 

· Change the specimen filter (cell B2) from Urine to
Blood and answer question 18.

Question

18. Which antibiotic would you recommend be tried with a blood-based Streptococcus infection? Explain. 

Lastly, determine if overall age plays a role in susceptibilities. Return to the original Culture & Sensitivity Data set tab and insert a new pivot table again. Follow the steps below:

· Click and drag the ‘Susceptibilities’ field to the Filters area. This will allow the susceptible (effective) results to be specified.

· Click and drag the ‘Age’ field to the Rows area. This will display each age as a row in the table.

· Click and drag the ‘Susceptibilities’ field to the ∑ Values area. It should show as ‘Count of Susceptibilities’. This will populate the table with the total number of susceptibilities for each age.

· In the Susceptibilities filter (cell B1), specify ‘Susceptible’. The resulting table should appear as follows.

When analyzing ages and/or dates, it’s often helpful to group them by ranges. In this case, group the ages by 10 to display the results for people in their 20s, 30s, 40s, etc. To do so:

· Click on one of the ages in Column A. For example, age 18 in cell A4. Choose
Analyze and
Group Field as demonstrated in the screenshot below.

· Group by 10 starting at 20 and ending at 100.

Answer question 19 below based on the results. Disregard the data for <20 as that segment only includes 2 years (18 and 19) whereas the rest includes 10 years.

Question

19. Does age make a difference in susceptibilities? Explain.

Critical Thinking Question

20. Summarize your findings in 100 words or less to share with the General Hospital administration.

Submit your work

Document your answers directly on this activity document as you complete the activity. When you are finished, save this activity document to your device and upload this activity document with your answers to your Learning Management System (LMS). If you have any questions about submitting your work to your LMS, please contact your instructor.

References

Healthline. Sensitivity Analysis: Purpose, Procedure, and Results. Medically reviewed by Steve Kim, MD on February 24, 2016 — Written by Christine Case-Lo and Brian Wu. Available at

EHR Go Knowledge Activity: Orientation to Data Analytics I (Baccalaureate) HBK1023.1

1

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