Dungeons & Dragons Taught Me
How to Make Better VPs
Randomizing Physiological Data to Rapidly
Produce 97 Clinically Realistic VPs
Mike Paget, Janet Tworek,
Kevin McLaughlin, Bruce Wright
University of Calgary
Calgary, Alberta, Canada
Overview
• 97 VPs
Requirements
• Clinically relevant
Solution
• Gaming experience
• dB design
Results
• 20 mins SME time per VP
• 97 clinically relevant VPs
Requirements
1. Create 97 VPs for full year course
– Clerkship (Year 3) students
– Little SME time
– Past experience with templates
• Time consuming
• Overlooked data
– No preexisting cases for
UofC context
Requirements
2. Clinically accurate values and variety in VP
-
Names
History
Laboratory
Physical Exam
Solution - Gaming
Solution - Gaming
Dungeon Master’s Guide
• Randomized realism
• Qualities related to
numbers
Solution - Gaming
Dungeon Master’s Guide
• Randomized realism
• Qualities related to
numbers
Virtual Patients
• Assign text strings to
numbers
• Treat numeric data as
numbers that fall within
a pre-specified range.
Solution: Process of Creating VPs
• All content areas
• Ranges for
normal results
1. VP Template
2. Create Data
Tables
• Table for each
text field
• ID number per
row
• Randomized
normal values
• Variety of text
responses
3. Prepared
Normal Template
4. SME Proofread
• Change key
nodes
• Approve -, +
• Complete
content
• SME approved
5. Case ready for
upload
1a. Create Template for VPs
Node
Patient Response
Any diseases run in the
family?
Lab: Anti Hepatitis A Virus Total
Lab: Chemistry Na – Sodium
Knee exam:
Do you have any pets?
• HxExIxDxRx model of VPs
• Set questions
1b. Create dB tables of VP data
ID
Diseases that run in the family
1
Cancer
ID
Positive or Negative
2
Stupidity
1
Positive
3
Heart attacks
2
Negative
4
Lung cancer
5
Arthritis
6
Accident prone
7
Asthma
8
Strokes
9
Dementia
10
Pneumonia
ID
Pet
1
No, I don’t like animals
2
I have 3 dogs
3
I have a cat I took in
4
Just a goldfish
5
I have a dog, but I think I might be allergic
2a. Create Specific Data Range by Node
Node
Low
High
Additional Text
Any diseases run in the
family?
1
10
Not applicable
Lab: Anti Hepatitis A Virus Total
1
2
Lab: Chemistry Na – Sodium 133
145
Knee exam:
1
1
Do you have any pets?
1
5
Normal range between 133 to 145
mmol/L
2b. Randomly Assign ID Values in Data
Range to specific VPs
Node
Patient 1
Patient 2 Patient 3 Additional Text
Any diseases run in the family?
3
8
1
Lab: Anti Hepatitis A Virus - Total
1
1
2
Lab: Chemistry Na – Sodium
137
139
141
Knee exam:
Active
movement:
Flexion 140
degrees, Ext….
Active
movement:
Flexion 140
degrees, Ext….
Active
movement:
Flexion 140
degrees, Ext….
Do you have any pets?
3
5
2
Normal range between
133 to 145 mmol/L
3a. Create report by linking randomized ID
values to text fields in appropriate tables
3b. Convert IDs to actual values & text
Node
Patient 1
Patient 2 Patient 3 Additional Text
Any diseases run in the family?
Heart
attacks
Strokes
Cancer
Lab: Anti Hepatitis A Virus - Total
Positive
Positive
Negative
Lab: Chemistry Na – Sodium
137
139
141
Knee exam:
Active
movement:
Flexion 140
degrees, Ext….
Active
movement:
Flexion 140
degrees, Ext….
Active
movement:
Flexion 140
degrees, Ext….
Do you have any pets?
I have a
cat I took
in
I have a
dog, but
I think I
might be
allergic
I have 3
dogs
Normal range between
133 to 145 mmol/L
Proofing VPs
• All content areas
• Ranges for
normal results
1. VP Template
2. Create Data
Tables
• Table for each
text field
• ID number per
row
• Randomized
normal values
• Variety of text
responses
3. Prepared
Normal Template
4. SME Proofread
• Change key
nodes
• Approve -, +
• Complete
content
• SME approved
5. Case ready for
upload
4a. Normal Template to SME
4b. SME records edits
Node
John Smith
Any diseases run in the family?
Kidney
disease in a
few relatives
Lab: Anti Hepatitis A Virus - Total
Positive
Lab: Chemistry Na – Sodium
160
Knee exam:
Active movement:
Flexion 140 degrees,
Ext….
Do you have any pets?
I have a dog, but I
think I might be
allergic
Additional Text
Normal range between 133 to
145 mmol/L
5. Upload content to OLab
• SME time
Multiple cases at once
• Insert picture of multiple cases
Results
• Time:
– 20 mins per VP
– 45 mins per side-by-side VPs (2)
• Salient negatives, positives/normals
• Side-by-side
– Contextual cues & patterns by presentation or
diagnosis
– Complexity of medicine
Result – Clinically accurate content
Conclusions
• Education as driver
• Realistic VPs = data issue
– Leverage gaming, dB experience
– Existing software + open source VP software
• Multiple clinically accurate VPs
– Appropriate personnel use
– Complexity of Medicine
• Sharing
Conclusions
• Gaming “nerd” = VP programming superhero
Thank You
Janet Tworek
jktworek@ucalgary.ca