July 2007

Population Health Model (POHEM)

• For educational / demonstration purposes• Not for distribution or citation

• Contact: microsimulation@statcan.gc.ca

July 2007

What can Micro-Simulation Do ?• project basic counts and distributions

– population– prevalence of risk factors – cases eligible for primary interventions– disease incidence and progression; e.g. first

AMIs, readmissions, and deaths

• simulate interventions and their potential impactsall these by age, sex, calendar year, geography, … any other modeled variables

July 2007

POpulation HEalth Model (POHEM)

• case-by-case, Monte Carlo microsimulation• directly encompasses competing risks and comorbidity• longitudinal risk factor and disease sub-modules • generates plausible health biographies for synthetic

individuals from empirical observations• population attributable fractions estimated through risk-

factor deletion (ie, relative risk set to 1)• projects population forward in continuous time

– population initialized in 2001 from Canadian Community Health Survey cycle 1.1

– subject to cohort-specific mortality hazards based on age, sex and year of birth

– new births and new immigrants generated in future years based on Census projections

July 2007

Main State Variables and Dependencies

– births / immigration / emigration – vital statistics, immigration records and demographic estimates by sex, province and year

– educational attainment - baseline = F (age, cohort, sex, …)

– mortality = F (age, cohort, sex, AMI status)– Cancer– OA

July 2007

2001

……..……..……..……..……..……..……..……..……..……..……..

POHEM exampleStarting Population: Canadian Community Health Survey 2001 (CCHS)

cross-sectional representation of the Canadian population aged 18+

VARIABLEage sex provincehealth regionimmigration statuseducation levelincome quartilebody mass index smoking statusdiabetic statustotal cholesterol*HDL*blood pressure*HUI

*imputed from Canadian Heart Health Surveys (1986-1992)

VALUE44maleOntarioYorknon-immigrantpost-secondaryQ4 (richest)32.2 kg/m2 (obese)smokernon-diabetichighlowhigh0.96

Every year on birthday, evaluate the hazard of developing disease (AMI, diabetes, cancer, osteoarthritis,...)

no disease events in 2001

July 2007

AMI at age 45.3

Now at risk of 2nd AMI, CHF, UA, ...

2001

……..……..……..……..……..……..……..……..……..……..……..

POHEM example

2002

……..

Starting Population: Canadian Community Health Survey 2001 (CCHS)cross-sectional representation of the Canadian population aged 18+

AMI

agesexprovincehealth region immigration statuseducation levelincome quartilebody mass indexsmoking statusdiabetic statustotal cholesterolHDLblood pressureHUI

Every year on birthday, evaluate the hazard of developing disease (AMI, diabetes, cancer, osteoarthritis,...)

AMI in 0.3 years

July 2007

…

……..

2001

……..……..……..……..……..……..……..……..……..……..……..

POHEM example

2002

……..

Starting Population: Canadian Community Health Survey 2001 (CCHS)cross-sectional representation of the Canadian population aged 18+

2003

…….. Death

at age 71.2

OA at age 69.4 in year 2028

(comorbid with Congestive Heart Failure)

AMI CHF OA

Congestive Heart Failueat age 66.1 in year 2023

agesexprovincehealth regionimmigration statuseducation levelincome quartilebody mass indexsmoking statusdiabetic statustotal cholesterolHDLblood pressureHUI

apply Δ BMI model (function of age, sex education, income, region and BMI in 2001) Remains Obese

July 2007

2001

……..……..……..……..……..……..……..……..……..……..……..

POHEM

2002

……..……..

Starting Population: Canadian Community Health Survey 2001 (CCHS)cross-sectional representation of the Canadian population aged 18+

2003

……..……..

…

……..…….. death

>100,000 records on CCHS representing ~24 million Canadians(4 hours on a PC)

July 2007

July 2007

Simple Models The Workbook Approach

(selected risk factors)

Smoking

Obesity

Nutrition

Cancers

Cancer model

Alcohol

Smoking

Obesity

Alcohol

Heart Disease

Heart disease Model

Diabetes

July 2007

Obesity

Smoking Cancers

Diabetes

Complex Causal Web Diagram:The Microsimulation Approach

Nutrition

Alcohol

Heart Disease

July 2007

Coronary Heart Disease: Acute Myocardial Infarction (AMI)

Upstream health determinants

Intermediate risk factors

Intermediate diseases

Sequalae Death

AMI*

Health Person-Oriented Information (HPOI)

(HIRD)

incidence rates by province, age and sex

2nd AMI

Congestive Heart

Failure

Unstable

Angina

Death

Registered Persons database for Ontario (ICES)

(CCORT I)

survival data for each transition

*incidence-risk equation based on Framingham risk function (Wilson 1998) for “index” AMI events

competing risk of death from other causes

Vital statistics(and other POHEM disease modules)

initial values & transition models

Diabetes

Total cholesterol

& HDL

blood pressur

e

Cdn Heart Health Surveys 1986-92

age (time)

initial values

Obesity

Smoking

Nutrition

Physical activity

Alcohol

Income

Education

Region

Sex

CCHS 2001

transition models

NPHS 1994-2004

S(t)

S(t)

S(t)

S(t)

S(t)

Causal pathway

July 2007

Data Analysis and Input to POHEM:

a) incidence rates (I) estimated from administrative data by age group, sex and province

b) incidence-risk equation obtained from the literature:

• Framingham risk function

• α represents the baseline risk (by age, sex, province) after accounting for the other risk factors

coefficients vary by category for cholesterol, high density lipids, diabetes and smoking obtained from the study (Wilson, 1998)

c) the baseline risk (α) is calibrated such that the incidence-risk equation implemented in POHEM (F) reproduces the observed incidence rates by age, sex and province

• takes into account the distribution of the risk factors (by category) in the population

d) values and models of change in risk factors based on data and trends from national surveys

How POHEM Generates an Incident Case of AMI1) POHEM selects a record from CCHS in simulation year 2001:

male, age 44, smoker, non-diabetic, high total cholesterol, low HDL, medium blood pressure...

2) Lookup baseline risk and risk factor coefficients from input parameter table.

3) Evaluate the probability (p) of AMI

using the Framingham risk function

(with rescaling):

p = F/(1+F) = 0.877

4) Convert to annualized hazard (h):

h = -ln(1-p) = 2.09

5) Generate a a random number (u) between 0 and 1

u = 0.025

6) Transform the hazard to a waiting time:

t = -ln(u) / h = 1.76 years

7) AMI does not occur at age 44 in year 2001. The risk of AMI will be re-evaluated at the next birthday.

8) POHEM ages the person forward to next birthday

• updates the person’s risk factors profile

• re-evaluates risk of AMI (steps 2-7).

• repeated every year until AMI occurs or death

• other events are evaluated

9) Steps 1 to 8 are repeated for every record on CCHS

α = 0.00138βsmoking= 0.523βdiab = 0βchol = 0.657βHDL = 0.497βBP = 0.283

SmokingDiabBPHDLcholeF

July 2007

Data Sources• Canadian Community Health Survey (2001)

– starting population for POHEM (initialize age, sex, geography, BMI, smoking, diabetes)

• National Population Health Survey (1994-2004)– models of change in BMI and smoking

• Canadian Heart Health Survey (1986 to 1992)– joint distribution of other cardiac risk factors cholesterol, diabetes, blood pressure – HDL imputed

• Health Person-Oriented Information (1992/93 to 2001/02) – hospital separations by province– rate of index AMI (5-yr wash-out) by province– managed at STC

• Registered Person database (1988/89 to 2001/02) – Ontario hospital separations linked to vital statistics– Survival time from AMI event to subsequent AMI event or death– managed at ICES

July 2007

Geography

• Geography is an explanatory variable in the BMI model– ATLANTIC, QUEBEC, ONTARIO, PRAIRIES, BC

• Geography is a dimension of the incidence rates for index AMI (by sex, age group, province groups– ATLANTIC, QUEBEC, ONTARIO, PRAIRIES, BC

• Geography was not used in the smoking model, and was not used in the joint risk factor transition model

July 2007

Model Input: Smoking transitions

Never smokers

Successful quitter in1996

Quit in1998

Smokers in all 3 years

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

non-smoker 94 smoker 94

non-smoker 96 and 98 non-smoker 96 and smoker 98smoker 96 and non-smoker 98 smoker 96 and 98

Source: NPHS

July 2007

transitions derived from NPHS (1996-2002)

transitions derived from CHHS

Diabt

CholtHyptt

Year2001 2003 2005 2007 2009 2011

t=0 t+5 t+10

BMIt+2

Diabt+10

Cholt+10Hyptt+10

BMIt BMIt+6 BMIt+8 BMIt+4

Diabt+5

Cholt+5Hyptt+5

BMIt+10

Initialization 2001

CCHS 2001age = 55sex = male income educationregionBMIdiabetes hypertension (y/n)smoker (y/n)

CHHS (86-92)total cholesterolHDLBlood pressure

Modeling Risk Factor Transitions

Legend:

Smokt+2 Smokingt Smokt+6 Smokt+8 Smokt+10 Smokt+4

July 2007

Example of HDL distribution by cholesterol for male aged 55-59, overweight and non-diabetic

Sex MaleAge 55-59BMI overweightDiabetic No

Total cholesterol Low HDL <35 mg/dl

Medium-Low HDL [35,45)

Medium HDL [45,50)

Medium-High HDL [50,60)

High HDL >=60

Low <160 mg/dl 0.06 0.11 0.53 0.30 0.00Medium-Low [160,200) 0.08 0.47 0.19 0.15 0.10Medium [200,240) 0.16 0.59 0.03 0.06 0.16Medium-Hi [240,280) 0.26 0.48 0.07 0.17 0.02High Chol. >=280 0.07 0.17 0.52 0.02 0.21

July 2007

Preliminary Results

July 2007

Acute Myocardial Infarction in Canada: Projection of risk

factors, incidence and progression from 2001 to 2021

July 2007

Objectives

• project the prevalence of risk factors most commonly associated with acute myocardial infarction (AMI) between 2001 and 2021

• project the number of resulting AMI events over that period

• estimate the contribution of each risk factor to AMI outcomes in future years

July 2007

Model Projection: Prevalence of Smoking

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

< 30 30-39 40-49 50-59 60-69 70-79 80+ All

Age

2001

2006

2011

Prop. of Pop

July 2007

Model Projection: Prevalence of Diabetes

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

20-29 30-39 40-49 50-59 60-69 70-79 80+ All

Age

2001

2006

2011

Prop of Pop

July 2007

Projected rate of new AMI cases per 1000

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Can

ada

Brit

ish

Col

umbi

a

Alb

erta

Sas

katc

hew

an

Man

itoba

Ont

ario

Que

bec

New

Bru

nsw

ick

Nov

a S

cotia

P.E

.I.

New

foun

dlan

d

20012006201120162021

age (current) All sex All

Sum of Rate AMI per 1000

province

Year

July 2007

Projected number of new AMI cases by province

0

5000

10000

15000

20000

25000

30000

British Columbia

Alberta

Saskatchewan

ManitobaOntario

Quebec

Nova Scotia

New BrunswickP.E.I.

Newfoundland

Nu

mb

er o

f in

dex

AM

I ev

ents

20012006201120162021

July 2007

Projected number of new AMI events (from new Index AMIs only)

0

20000

40000

60000

80000

100000

120000

140000

2001 2006 2011 2016 2021

Year

Nu

mb

er o

f A

MI-

rela

ted

eve

nts

Death after CHFDeath after UADeath after second AMIDeath after incidence AMIIn-hospital deathsCongestive Heart FailureUnstable AnginaSecond AMIIndex AMI

* includes death from non-IHD causes

*

July 2007

Projected Number Eligible for Statin Use in Ontario in 2001 – CMAJ 2000 Guidelines (’000s)

<4 4-5 5-6 6-7 >=7 Total

0-5% 4 148 1 887 969 373 288 7 666

5-10% 201 278 238 116 111 945

10-15% 54 102 88 51 56 351

15-20% 14 40 41 28 27 150

20-25% 2 11 19 14 16 63

25-30% 1 5 9 8 9 33

>=30% 0 2 8 9 13 33

Medication and lifestyle change, n = 109,000

Medication if target not reach after 6 months of lifestyle changes, n = 399,000Medication if target not reach after 3 months of lifestyle changes, n = 162,000

Based on the recommendations for the management and treatment of dyslipidemia (CMAJ 2000)

Total Cholesterol / HDL

10-y

ear

pre

dic

ted

ris

k o

f A

MI

July 2007

Illustrative “What-if ?” Scenarios• Statins: given to people at high risk according to

guidelines from working group on dyslipidemias; reduces their AMI risk by 31% (La Rosa, 99).

• BMI: 10% reduction for everyone overweight or obese (BMI ≥ 25) at baseline in 2001

• Smoking: 20% of smokers permanently quit smoking at baseline in 2001

• Cholesterol: 5% reduction of total cholesterol value for everyone at baseline in 2001

• Note: interactions in RF dynamics change in one at baseline affects subsequent levels of others

July 2007

Cumulative number of index AMIs avoided by calendar year, by “what-if” scenario, Canada

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

2001 2003 2005 2007 2009 2011

Year

Cu

mu

lati

ve n

um

ber

of

ind

ex A

MIs

avo

ided Cholesterol -5%

Statins to mediumand high risk

Statins to highrisk

BMI -10%

Smoking -20%

Limitations:

• statin coverage at baseline not modeled so this graph overestimates benefit;

• uncertainty of benefit of statins not captured and this modeling exercised assumed relatively large benefit which may also over-estimate benefit;

•no side-effects of statins were modeled

July 2007

0%

20%

40%

60%

80%

100%2

001

20

022

003

20

042

005

20

062

007

20

082

009

20

102

011

20

122

013

20

142

015

20

162

017

20

182

019

20

202

021

20

012

002

20

032

004

20

052

006

20

072

008

20

092

010

20

112

012

20

132

014

20

152

016

20

172

018

20

192

020

20

21

Female Male

Background Smoking Diabetes Blood pressure Cholesterol HDL

Projected fraction of AMI cases attributable to risk factors

37%

47%

58%62%

July 2007

Additivity(?) of risk factors

0

10000

20000

30000

40000

50000

60000

70000

8000020

01

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

Year

Background Smoking Diabetes Blood pressure Cholesterol HDL Base case

Num

ber

of in

dex

AM

I ca

ses

July 2007

Summary of preliminary results

• Number of AMI cases projected to increase, principally due to aging of the population

• smoking projected to decline, reduces the overall increase in AMI

• proportion of persons with diabetes projected to rise• approximately 10% of new index AMI cases attributed to

diabetes• in males, 24% of new AMI cases attributed to elevated

blood pressure• in females, 17% of new AMI cases attributed to elevated

total cholesterol

July 2007

• Revise, finalize and publish current work– revise / explore intervention scenarios– validation – e.g. recreate 1994 – 2004 history of incidence and mortality

• Improve POHEM’s data foundations– update index AMI rates with most recent data (from 2001 to 2004)– update to CCHS cycle 3.1 (or pooled) to initialize POHEM– update with measured risk factor prevalence from CHMS (when available)– update survival with cause-specific mortality data (HPOI linked to vital stats)

• Expand cardio-vascular disease model– develop more robust model of diabetes (Rosella and Manual, ICES)– add procedures (CABG, PCI, catheterizations) as consequence of AMI– relate procedures to survival outcomes – to the extent there are data– add CHF and UA as index events (if appropriate)???– add models of stroke and peripheral vascular disease– other CVD

• Health-related Quality of Life– estimate health-adjusted life expectancy

• Burden of disease– Build POHEM towards a comprehensive tool covering multiple diseases, risk factors and

functional health status and other sequalae

Future Work

Health-Related Quality of Life – Beyond Life Expectancy (LE)

• LE = area under survival curve• HALE = “weighted” area under survival curve

– where “weights” are levels of individual health status, ranging between zero (dead) and one (fully healthy)

July 2007

NutritionDiabetes

Kidney Disease

Diabetic Retinopathy

Osteoarthritis

CoronaryHeart

Disease

PeripheralVascularDisease

Stroke

Obesity

Physical activity

Alcohol

25 Cancers

Region

Smoking

Cholesterol

blood pressur

e

hypertensive

Ethnicity

Upstream health determinants

Intermediate risk factors

Intermediate diseases Diseases Treatment

Initial state assigned from CCHS (+CHHS)

Dea

th

competing risk of death from other causes

Amputation

Dialysis

ABS

Surgery

Surgery, Radio/Chemo/Hor

monal therapy

Cataract surgery...

CAPG, PCI, CATH, Drugs,

lifestyle

POHEM: Overall causal flow

age and sex

other risk factors

other diseases

Income

Education

Health-related Quality of life (HUI)