EHR Go Knowledge Activity: Orientation to Data Analytics I 2.0
Part A & B IK1023.5 -Answered 2026.
Knowledge Activity: Orientation to Data
Analytics I 2.0
Part A
Prerequisites
Questions
1. Identify & list at least three data quality issues in the dataset. The three data issues that
are easy to spot: many different capitalization errors in E. coli (e. coli), the same goes
for K. pneumonia, and lastly, the word “inter” should be “intermediate.”
2. Why must these issues be addressed before conducting analysis? These issues must be
addressed to avoid confusion in grouping, such as duplicate groups for the same
microbe due to a spelling or punctuation error.
3. Choose one issue and describe the exact steps you took in Excel to clean it. The one easy fix
was to highlight the chart, sort A-Z so that I could group all the “inter” together, then
highlight those columns, CTRL+H, and replace with “intermediate”.
4. Once you’ve completed cleaning the Mass Sensitivities EHR data, rename and save the
document to your computer to submit as a final step of this activity.
Section II.
To learn more, review the resource, Antimicrobial Susceptibility (found under 1: Overview &
Resources along with this activity document) and answer the following questions.
5. What is the main purpose of Antimicrobial Susceptibility Testing (AST)?
a. To monitor how often infections occur in a hospital
b. To identify the type of bacteria causing an infection
c. To determine which antibiotics are effective against specific bacteria
d. To track side effects of antibiotic medications
EHR Go Knowledge Activity: Orientation to Data Analytics I 2.0 Part A IK1023.5
Archetype Innovations LLC ©2026 1
, 6. Name two common AST methods and briefly explain what they measure. AST methods of
testing include agar dilution and disk diffusion, which apply a “two-fold” dilution of
antibiotics in a petri dish; the bacteria are then placed on the dish and incubated to
determine which antibiotic is more or less effective against the bacteria. Broth
microdilution determines which one of the antibiotic dishes with the lowest growth
would be the MIC.
7. Define Susceptible, Intermediate, and Resistant and explain why accurate, coded results
(not free text) are important in EHRs.
a. Susceptible makes it possible for treatment with the antibiotic, Intermediate
means treatment with the antibiotic is basically in limbo or uncertain, and
resistant means that the antibiotic did not or will not work for treatment. The
importance of accurately coded results weighs heavily on how the patient will be
treated and the doses that they should be prescribed. Inaccurate coding would
produce a medication error that could result in life-threatening results.
8. What problems can happen if AST results are entered inconsistently or as unstructured text
(instead of using standard codes)? Doctors, nurses, specialists, and other healthcare
professionals rely on EHRs in order to transmit and obtain patient medical records to
make better clinical decisions, especially when prescribing medication. This is why data
entry must be consistent and well-structured to avoid confusing the CDS with
unrecognizable text. Inconsistent data can complicate medication decision-making and
increase the risk of misinterpretation errors. This could lead to an unnecessary
medication being prescribed, causing damage to the patient.
Section III.
EHR Review
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.
Tip! Open the Culture & Sensitivity Report from the Notes Tab, then click “Edit.” This will help you
determine how the information was recorded (structured, unstructured, or both) to answer
questions 9-11.
9. What specimen type was documented in the Culture & Sensitivity (C&S) report, and how
was this information recorded in the EHR? Was it structured, unstructured, or both? The
urine sample was documented in the EHR using both structured and unstructured
data.
EHR Go Knowledge Activity: Orientation to Data Analytics I 2.0 Part A IK1023.5
Archetype Innovations LLC ©2026 2
Part A & B IK1023.5 -Answered 2026.
Knowledge Activity: Orientation to Data
Analytics I 2.0
Part A
Prerequisites
Questions
1. Identify & list at least three data quality issues in the dataset. The three data issues that
are easy to spot: many different capitalization errors in E. coli (e. coli), the same goes
for K. pneumonia, and lastly, the word “inter” should be “intermediate.”
2. Why must these issues be addressed before conducting analysis? These issues must be
addressed to avoid confusion in grouping, such as duplicate groups for the same
microbe due to a spelling or punctuation error.
3. Choose one issue and describe the exact steps you took in Excel to clean it. The one easy fix
was to highlight the chart, sort A-Z so that I could group all the “inter” together, then
highlight those columns, CTRL+H, and replace with “intermediate”.
4. Once you’ve completed cleaning the Mass Sensitivities EHR data, rename and save the
document to your computer to submit as a final step of this activity.
Section II.
To learn more, review the resource, Antimicrobial Susceptibility (found under 1: Overview &
Resources along with this activity document) and answer the following questions.
5. What is the main purpose of Antimicrobial Susceptibility Testing (AST)?
a. To monitor how often infections occur in a hospital
b. To identify the type of bacteria causing an infection
c. To determine which antibiotics are effective against specific bacteria
d. To track side effects of antibiotic medications
EHR Go Knowledge Activity: Orientation to Data Analytics I 2.0 Part A IK1023.5
Archetype Innovations LLC ©2026 1
, 6. Name two common AST methods and briefly explain what they measure. AST methods of
testing include agar dilution and disk diffusion, which apply a “two-fold” dilution of
antibiotics in a petri dish; the bacteria are then placed on the dish and incubated to
determine which antibiotic is more or less effective against the bacteria. Broth
microdilution determines which one of the antibiotic dishes with the lowest growth
would be the MIC.
7. Define Susceptible, Intermediate, and Resistant and explain why accurate, coded results
(not free text) are important in EHRs.
a. Susceptible makes it possible for treatment with the antibiotic, Intermediate
means treatment with the antibiotic is basically in limbo or uncertain, and
resistant means that the antibiotic did not or will not work for treatment. The
importance of accurately coded results weighs heavily on how the patient will be
treated and the doses that they should be prescribed. Inaccurate coding would
produce a medication error that could result in life-threatening results.
8. What problems can happen if AST results are entered inconsistently or as unstructured text
(instead of using standard codes)? Doctors, nurses, specialists, and other healthcare
professionals rely on EHRs in order to transmit and obtain patient medical records to
make better clinical decisions, especially when prescribing medication. This is why data
entry must be consistent and well-structured to avoid confusing the CDS with
unrecognizable text. Inconsistent data can complicate medication decision-making and
increase the risk of misinterpretation errors. This could lead to an unnecessary
medication being prescribed, causing damage to the patient.
Section III.
EHR Review
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.
Tip! Open the Culture & Sensitivity Report from the Notes Tab, then click “Edit.” This will help you
determine how the information was recorded (structured, unstructured, or both) to answer
questions 9-11.
9. What specimen type was documented in the Culture & Sensitivity (C&S) report, and how
was this information recorded in the EHR? Was it structured, unstructured, or both? The
urine sample was documented in the EHR using both structured and unstructured
data.
EHR Go Knowledge Activity: Orientation to Data Analytics I 2.0 Part A IK1023.5
Archetype Innovations LLC ©2026 2
