1. Online Risk Assessment for the General Public
Liz Heathcote, Dr Larry Goldenberg, Dr Kendall Ho, Marcel
Labbe and Bradut Dima
UBC
Department of
Project funder: Partners: Urologic
Sciences
eHealth Strategy Office

2. The drivers in figures…
76 Life expectancy of Canadian men (years)
4.4 Less years than Canadian women
65 “health expectancy” of Canadian men (years)
eHealth Strategy Office

3. Project Goal
The ultimate project goal is to reduce the burden of
preventable disease
in (wo)men in BC
through educating them about
their individual health risks and
empowering them with evidence
-based recommendations for
how they can add 10 years to
the middle of their lives.
eHealth Strategy Office

4. Project Aims
• Take a gendered lens to health risk assessment and
participant reporting;
• Gather data from men and women about their health;
• Inform them about their risks; and
• Educate and motivate them to take positive action to
improve their health and reduce their health risks
through tailored education on the behavior changes
needed and supports available to them.
eHealth Strategy Office

5. Overview of work so far
Literature Requirements Expert Input Design & Test
Programming
Review Gathering & Review Functionality Cases
…and to come
Focus
Testing Release Evaluation Phase 2?
Groups
Survey
validation
Population
Datasets
eHealth Strategy Office

6. Challenges
• Evidence base for risks of developing disease
• Expansive for some diseases/ populations, non-existent for
others
• Relevant population studies may not exist
• Often contradictory findings
• Multiple dependent variables
• Understandable reticence to assign a risk score
• Will change as further research is conducted
eHealth Strategy Office

7. The end in mind!
At the same time, we should
be able to identify those
factors that increase risk of
preventable diseases more
than others
and
this should assist in identifying
an individual’s top 3-4
recommendations.
eHealth Strategy Office

8. Risk Continuum – by disease
Inputs: evidence, expert opinion, test cases
Low High
Score = Negative or 0 Score = 100%
eHealth Strategy Office

9. Risk Continuum – by question
Impact of that particular factor (e.g. BMI, exercise, smoking) on
the overall disease risk.
Within each factor, relative impact of each variable along the
continuum (e.g. non-smoker, social, more than 15 a day)
Low High
Score = Negative or 0 (Varies)
(zero if no risk to that disease) Should reflect overall risk
compared to other variables
eHealth Strategy Office

10. Design: Relative Importance of Risk Factors
Family Health Exercise
BMI Diet Smoking
history history Etc. etc
Disease A
Health Exercise
BMI Family history Diet Smoking
history Etc. etc
Disease B
eHealth Strategy Office

11. 0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
-2.00%
-1.00%
Gender
Age
Ethnicity
BMI
Cholesterol
BP
Family: Diabetes
Cardio Vascular disease (in first degree…
Coronary heart disease in 1st degree…
#Prostate Cancer (brother, father)
Osteoporosis
osteo fractures (was q 40)
Mental health/Depression
Own History: Stroke
Atrial Fib
Head/ brain
depression
arthritis
diabetes
renal disease
Chemotherapy
Hemochromatosis
Minimum Risk Effect
Maximum Risk Effect
HIV
Low Testosterone
Sleep Apnea
Fracture
Malnutrition
Genital trauma
Mumps
Radiation to Pelvis
Undesc. Testicles
Low Testosterone
Heart Medication
eHealth
Prostate Treatment
Cortisone
Smoking
Alcohol
Chart showing minimum and maximum percentage weighting of the answer variables
Unhealthy Diet
Strategy
Meat
milk
coffee
soft drinks
Office
Exercise

12. Cases - Online Risk Assessment
100
Case 1: A65 year old male, with no familybad cholesterol and is on medications for
13: 59-year-old man smoker, high history of prostate cancer presents with urinary
this, diabetes x 5 one year. He is Caucasian and least one drink a he weekend heavy
symptoms lasting years, drink alcohol regularly (athas mild diabetes,day,used to smoke but quit 5
use of more than 6 drinks a sitting), occasional carbohydrate/ low strong family history
years ago and drinks socially. He enjoys a high cocaine use, has afiber diet, does eat a of
80 heart problems, comes in because of & he pain after exercise.
lot of animal fat and processed meat chestis fairly inactive,exercising less than 3 times per week.
Risk Percentage Assessed by Tool
60
ED
Card.
Low T
40 Diab.
Prost.
Bone
Mental
20
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
-20
Case Number
eHealth Strategy Office

16. Online Prototype

18. Design
Family Health Exercise
BMI Diet Smoking
history history Etc. etc
Lifestyle/ modifiable factors
1. Determine risk of the 7 diseases;
2. Where risk is medium or high, calculate which lifestyle or
modifiable factor would have the most impact on reducing the
risk;
3. Recalculate risks using the 3-4 lifestyle suggestions which will
have most positive impact.
eHealth Strategy Office

19. Lessons so far
• Flexibility in design!
• Dealing with unknowns
• Expert tools
• Keep the ultimate goal uppermost
• Gender aspects
• Iterative design & development
eHealth Strategy Office

20. Thanks to the team!
Medical Sponsors/Leads
Dr Larry Goldenberg, Dr Kendall Ho
Men’s Health Initiative of BC
Marcel Labbe, Wayne Hartrick, Joe Rachert, Dr
Larry Mroz
eHealth Strategy Office Programming team
Bradut Dima, Peter Chow and Rick Shun