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Online Risk Assessment for the General PublicLiz Heathcote, Dr Larry Goldenberg, Dr Kendall Ho, MarcelLabbe and Bradut Dim...
The drivers in figures…76   Life expectancy of Canadian men (years)4.4 Less years than Canadian women65   “health expectan...
Project GoalThe ultimate project goal is to reduce the burden ofpreventable diseasein (wo)men in BCthrough educating them ...
Project Aims• Take a gendered lens to health risk assessment and  participant reporting;• Gather data from men and women a...
Overview of work so farLiterature    Requirements     Expert Input     Design &         Test                              ...
Challenges• Evidence base for risks of developing disease   • Expansive for some diseases/ populations, non-existent for  ...
The end in mind!At the same time, we shouldbe able to identify thosefactors that increase risk ofpreventable diseases more...
Risk Continuum – by disease  Inputs: evidence, expert opinion, test cases  Low                                            ...
Risk Continuum – by question  Impact of that particular factor (e.g. BMI, exercise, smoking) on  the overall disease risk....
Design: Relative Importance of Risk Factors            Family                         Health        Exercise  BMI         ...
0.00%                                                                                                    1.00%            ...
Cases - Online Risk Assessment                                   100                                             Case 1: A...
Online Prototype
Design           Family                                Health      Exercise  BMI                      Diet        Smoking ...
Lessons so far• Flexibility in design!• Dealing with unknowns• Expert tools• Keep the ultimate goal uppermost• Gender aspe...
Thanks to the team!Medical Sponsors/LeadsDr Larry Goldenberg, Dr Kendall HoMen’s Health Initiative of BCMarcel Labbe, Wayn...
Online Risk Assessment for the General Public
Online Risk Assessment for the General Public
Online Risk Assessment for the General Public
Online Risk Assessment for the General Public
Online Risk Assessment for the General Public
Online Risk Assessment for the General Public
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Online Risk Assessment for the General Public

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  • Men’s Health Initiative of BC (MHIBC)Canadian men have a life expectancy of 76 and in BC live on average 4.4 years less than women. But beyond length of life, more revealing statistics relate to the age at which a person loses their good health (“Health Expectancy”) and the numbers of years of life lost because of dying at an early age (“Potential Years of Life Lost”). With an average health expectancy of 65 years, Canadian men may experience 11 or more years of poor health and disability before they die. And Canadian men have a 20% higher number of potential years of life lost, as they are more likely to die at a younger age when struck by a stroke or heart disease, or as a result of risk taking behaviour, suicide, or workplace mortality.
  • Lit Review – existing risk assessments, health behavior change & health risks by diseaseReq’s – 7 diseases (CVD, Diabetes, Mental Health, Bone Disease, ED, Low Testosterone, Prostate)
  • Login issues especially for men – focus group
  • Transcript of "Online Risk Assessment for the General Public "

    1. 1. Online Risk Assessment for the General PublicLiz Heathcote, Dr Larry Goldenberg, Dr Kendall Ho, MarcelLabbe and Bradut Dima UBC Department ofProject funder: Partners: Urologic Sciences eHealth Strategy Office
    2. 2. The drivers in figures…76 Life expectancy of Canadian men (years)4.4 Less years than Canadian women65 “health expectancy” of Canadian men (years) eHealth Strategy Office
    3. 3. Project GoalThe ultimate project goal is to reduce the burden ofpreventable diseasein (wo)men in BCthrough educating them abouttheir individual health risks andempowering them with evidence-based recommendations forhow they can add 10 years tothe middle of their lives. eHealth Strategy Office
    4. 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. 5. Overview of work so farLiterature 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. 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. 7. The end in mind!At the same time, we shouldbe able to identify thosefactors that increase risk ofpreventable diseases morethan othersandthis should assist in identifyingan individual’s top 3-4recommendations. eHealth Strategy Office
    8. 8. Risk Continuum – by disease Inputs: evidence, expert opinion, test cases Low HighScore = Negative or 0 Score = 100% eHealth Strategy Office
    9. 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 HighScore = Negative or 0 (Varies)(zero if no risk to that disease) Should reflect overall risk compared to other variables eHealth Strategy Office
    10. 10. Design: Relative Importance of Risk Factors Family Health Exercise BMI Diet Smoking history history Etc. etcDisease A Health Exercise BMI Family history Diet Smoking history Etc. etcDisease B eHealth Strategy Office
    11. 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 MedicationeHealth Prostate Treatment Cortisone Smoking Alcohol Chart showing minimum and maximum percentage weighting of the answer variables Unhealthy DietStrategy Meat milk coffee soft drinksOffice Exercise
    12. 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
    13. 13. Online Prototype
    14. 14. Design Family Health Exercise BMI Diet Smoking history history Etc. etcLifestyle/ modifiable factors1. 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
    15. 15. Lessons so far• Flexibility in design!• Dealing with unknowns• Expert tools• Keep the ultimate goal uppermost• Gender aspects• Iterative design & development eHealth Strategy Office
    16. 16. Thanks to the team!Medical Sponsors/LeadsDr Larry Goldenberg, Dr Kendall HoMen’s Health Initiative of BCMarcel Labbe, Wayne Hartrick, Joe Rachert, DrLarry MrozeHealth Strategy Office Programming teamBradut Dima, Peter Chow and Rick Shun
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