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Population Health Model (POHEM)

Population Health Model (POHEM)

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Population Health Model (POHEM)

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  1. For educational / demonstration purposes Not for distribution or citation Contact: microsimulation@statcan.gc.ca Population Health Model (POHEM) July 2007

  2. 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 impacts all these by age, sex, calendar year, geography, … any other modeled variables July 2007

  3. 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

  4. 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

  5. 2001 …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. POHEM example Starting Population: Canadian Community Health Survey 2001 (CCHS) cross-sectional representation of the Canadian population aged 18+ VARIABLE age sex province health region immigration status education level income quartile body mass index smoking status diabetic status total cholesterol* HDL* blood pressure* HUI *imputed from Canadian Heart Health Surveys (1986-1992) Every year on birthday, evaluate the hazard of developing disease (AMI, diabetes, cancer, osteoarthritis,...)  no disease events in 2001 VALUE 44 male Ontario York non-immigrant post-secondary Q4 (richest) 32.2 kg/m2 (obese) smoker non-diabetic high low high 0.96 July 2007

  6. 2002 age sex province health region immigration status education level income quartile body mass index smoking status diabetic status total cholesterol HDL blood pressure HUI 2001 …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. POHEM example Starting Population: Canadian Community Health Survey 2001 (CCHS) cross-sectional representation of the Canadian population aged 18+ Every year on birthday, evaluate the hazard of developing disease (AMI, diabetes, cancer, osteoarthritis,...)  AMI in 0.3 years AMI AMI at age 45.3 Now at risk of 2nd AMI, CHF, UA, ... July 2007

  7. 2003 … 2002 age sex province healthregion immigration status education level income quartile body mass index smoking status diabetic status total cholesterol HDL blood pressure HUI 2001 …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. apply Δ BMI model (function of age, sex education, income, region and BMI in2001)  Remains Obese POHEM example Starting Population: Canadian Community Health Survey 2001 (CCHS) cross-sectional representation of the Canadian population aged 18+ Death at age 71.2 CHF OA AMI Congestive Heart Failue at age 66.1 in year 2023 OA at age 69.4 in year 2028 (comorbid with Congestive Heart Failure) July 2007

  8. 2002 2003 … 2001 …….. …….. …….. …….. …….. …….. death …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. …….. POHEM Starting Population: Canadian Community Health Survey 2001 (CCHS) cross-sectional representation of the Canadian population aged 18+ >100,000 records on CCHS representing ~24 million Canadians (4 hours on a PC) July 2007

  9. July 2007

  10. Simple Models The Workbook Approach(selected risk factors) Cancer model Heart disease Model Smoking Smoking Obesity Obesity Cancers Heart Disease Diabetes Nutrition Alcohol Alcohol July 2007

  11. Complex Causal Web Diagram: The Microsimulation Approach Nutrition Smoking Cancers Alcohol Obesity Heart Disease Diabetes July 2007

  12. Upstream health determinants Intermediate risk factors Intermediate diseases Sequalae Death Smoking NPHS 1994-2004 Alcohol Sex transition models 2nd AMI Total cholesterol & HDL Region S(t) Nutrition S(t) blood pressure Obesity AMI* Congestive Heart Failure Death Income S(t) S(t) S(t) Diabetes Education Physical activity survival data for each transition incidence rates by province, age and sex Unstable Angina initial values & transition models Health Person-Oriented Information (HPOI) (HIRD) Registered Persons database for Ontario (ICES) (CCORT I) initial values CCHS 2001 Vital statistics (and other POHEM disease modules) Cdn Heart Health Surveys 1986-92 competing risk of death from other causes Coronary Heart Disease: Acute Myocardial Infarction (AMI) Causal pathway age (time) July 2007 *incidence-risk equation based on Framingham risk function (Wilson 1998) for “index” AMI events

  13. How POHEM Generates an Incident Case of AMI • POHEM selects a record from CCHS in simulation year 2001: male, age 44, smoker, non-diabetic, high total cholesterol, low HDL, medium blood pressure... • Lookup baseline risk and risk factor coefficients from input parameter table. • Evaluate the probability (p) of AMI • using the Framingham risk function • (with rescaling): • p = F/(1+F) = 0.877 • Convert to annualized hazard (h): • h = -ln(1-p) = 2.09 • Generate a a random number (u) between 0 and 1 • u = 0.025 • Transform the hazard to a waiting time: • t = -ln(u) / h = 1.76 years • AMI does not occur at age 44 in year 2001. The risk of AMI will be re-evaluated at the next birthday. • 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 • Steps 1 to 8 are repeated for every record on CCHS • Data Analysis and Input to POHEM: • incidence rates (I) estimated from administrative data by age group, sex and province • 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) • 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 α = 0.00138 βsmoking= 0.523 βdiab = 0 βchol = 0.657 βHDL = 0.497 βBP = 0.283 July 2007

  14. 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

  15. 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

  16. 100% Smokers in all 3 years 90% Never smokers 80% 70% 60% 50% 40% Quit in1998 30% 20% Successful quitter in1996 10% 0% non-smoker 94 smoker 94 non-smoker 96 and 98 non-smoker 96 and smoker 98 smoker 96 and non-smoker 98 smoker 96 and 98 Model Input: Smoking transitions July 2007 Source: NPHS

  17. Initialization 2001 Year 2001 2003 2005 2007 2009 2011 CCHS 2001 age = 55 sex = male income education region BMI diabetes hypertension (y/n) smoker (y/n) t=0 t+5 t+10 CHHS (86-92) total cholesterol HDL Blood pressure transitions derived from NPHS (1996-2002) transitions derived from CHHS Modeling Risk Factor Transitions Smokt+10 Smokt+6 Smokt+8 Smokt+4 Smokt+2 Smokingt BMIt+10 BMIt+6 BMIt+8 BMIt+4 BMIt+2 BMIt Diabt+10 Cholt+10 Hyptt+10 Diabt+5 Cholt+5 Hyptt+5 Diabt Cholt Hyptt Legend: July 2007

  18. Example of HDL distribution by cholesterol for male aged 55-59, overweight and non-diabetic July 2007

  19. Preliminary Results July 2007

  20. Acute Myocardial Infarction in Canada: Projection of risk factors, incidence and progression from 2001 to 2021 July 2007

  21. 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

  22. Model Projection: Prevalence of Smoking Prop. of Pop Illustrative - not for distribution July 2007

  23. Model Projection: Prevalence of Diabetes Prop of Pop Illustrative - not for distribution July 2007

  24. Projected rate of new AMI cases per 1000 Illustrative - not for distribution July 2007

  25. Projected number of new AMI cases by province Illustrative - not for distribution July 2007

  26. Projected number of new AMI events (from new Index AMIs only) Illustrative - not for distribution * * includes death from non-IHD causes July 2007

  27. Projected Number Eligible for Statin Use in Ontario in 2001 – CMAJ 2000 Guidelines (’000s) Total Cholesterol / HDL Illustrative - not for distribution 10-year predicted risk of AMI Medication if target not reach after 6 months of lifestyle changes, n = 399,000 Medication if target not reach after 3 months of lifestyle changes, n = 162,000 Medication and lifestyle change, n = 109,000 Based on the recommendations for the management and treatment of dyslipidemia (CMAJ 2000) July 2007

  28. 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

  29. Cumulative number of index AMIs avoided by calendar year, by “what-if” scenario, Canada • 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 Illustrative - not for distribution July 2007

  30. Projected fraction of AMI cases attributable to risk factors Illustrative - not for distribution 62% 58% 47% 37% July 2007

  31. Additivity(?) of risk factors Illustrative - not for distribution Number of index AMI cases July 2007

  32. 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

  33. Future Work • 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 July 2007

  34. 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)

  35. POHEM: Overall causal flow Intermediate risk factors Upstream health determinants Intermediate diseases Diseases Treatment Death age and sex Health-related Quality of life (HUI) Coronary Heart Disease Alcohol CAPG, PCI, CATH, Drugs, lifestyle Ethnicity Stroke Smoking ABS Region Peripheral Vascular Disease Cholesterol Amputation hypertensive Diabetes Diabetic Retinopathy Nutrition Income Cataract surgery... blood pressure Kidney Disease Dialysis Education Obesity Osteoarthritis Surgery Physical activity other risk factors other diseases 25 Cancers Surgery, Radio/Chemo/Hormonal therapy competing risk of death from other causes Initial state assigned from CCHS (+CHHS) July 2007