1. April 6, 20091 Back to Basics, 2009 POPULATION HEALTH (1): GENERAL OBJECTIVES N Birkett, MD Epidemiology & Community Medicine Based on slides prepared by Dr. R. Spasoff Other resources available on Individual & Population Health web siteIndividual & Population Health web site

2. April 6, 20092 THE PLAN We will follow MCC Objectives for Qualifying Examination (in italics) Focus is on topics not well covered in the Toronto Notes (UTMCCQE) Three sessions: General Objectives & Infectious Diseases, Clinical Presentations, Additional Topics

3. April 6, 20093 THE PLAN(2) First class –mainly lectures Other classes –About 1.5-2 hours of lectures –Review MCQs for 60 minutes A 10 minute break about half-way through You can interrupt for questions, etc. if things aren’t clear.

4. April 6, 20094 THE PLAN (3) Session 1 (April 6, 1300-1600) –Diagnostic tests Sensitivity, specificity, validity, PPV –Health Promotion –Critical Appraisal (more on April 7) –Elements of Health Economics –Vital Statistics –Overview of Communicable Disease control, epidemics, etc.

5. April 6, 20095 THE PLAN (4) Session 2 (April 4, 1300-1600) –Clinical Presentations Periodic Health Examination Immunization Occupational Health Health of Special Populations Disease Prevention Determinants of Health Environmental Health

6. April 6, 20096 THE PLAN (5) Session 3 (April 9, 1300-1600) –CLEO Overview of Ethical Principles Organization of Health Care Delivery in Canada –Other topics Intro to Biostatistics Brief overview of epidemiological research methods

7. April 6, 20097 LMCC New Objectives (1) Population Health Concepts of Health and Its Determinants (78-1) Assessing and Measuring Health Status at the Population Level (78-2) Interventions at the Population Level (78-3) Administration of Effective Health Programs at the Population Level (78-4) Outbreak Management (78-5) Environment (78-6) Health of Special Populations (78-7)

8. April 6, 20098 LMCC New Objectives (2) C 2 LEOC 2 LEO (URL to LMCC objective page) Considerations for –Cultural-Communication, Legal, Ethical and Organizational Aspects of the Practice of Medicine

9. April 6, 20099 LMCC New Objectives (3) We won’t be able to cover every objective in detail. Sessions will be based around objectives, with links identified as appropriate. Start with some overviews.

10. April 6, 200910 LMCC New Objectives (4) 78.1: CONCEPTS OF HEALTH AND ITS DETERMINANTS Define and discuss the concepts of health, wellness, illness, disease and sickness. Describe the determinants of health and how they affect the health of a population and the individuals it comprises. Lifecourse/natural history Illness behaviour Culture and spirituality

11. April 6, 200911 LMCC New Objectives (5) 78.1: CONCEPTS OF HEALTH AND ITS DETERMINANTS Determinants of health include: –Income/social status –Social support networks –Education/literacy –Employment/working conditions –Social environments –Physical environments –Personal health practices/coping skills –Healthy child development –Biology/genetic endowment –Health services –Gender –Culture

12. April 6, 200912 LMCC New Objectives (6) 78.2: ASSESSING AND MEASURING HEALTH STATUS AT THE POPULATION LEVEL Describe the health status of a defined population. Measure and record the factors that affect the health status of a population with respect to the principles of causation –Principles of Epidemiology, critical appraisal, causation, etc.

13. April 6, 200913 LMCC New Objectives (7) 78.3: INTERVENTIONS AT THE POPULATION LEVEL Understand three levels of prevention Concepts of Health Promotion, etc. Role of physicians at the community level. Impact of public policy

14. April 6, 200914 LMCC New Objectives (8) 78.4: ADMINISTRATION OF EFFECTIVE HEALTH PROGRAMS AT THE POPULATION LEVEL Structure of the Canadian Health Care System Concepts of economic evaluation Quality of care assessment

15. April 6, 200915 LMCC New Objectives (9) 78.5: OUTBREAK MANAGEMENT Know defining characteristics of an outbreak Demonstrate essential skills in outbreak control

16. April 6, 200916 LMCC New Objectives (10) 78.6: ENVIRONMENT Recognize implications of environmental health at the individual and community levels Know methods of information gathering Work collaboratively with other groups Recommend to patients and groups how they can minimize risk and maximize overall function

17. April 6, 200917 LMCC New Objectives (11) 78.7: HEALTH OF SPECIAL POPULATIONS Specific target population include: –First Nations, Inuit, Métis Peoples –Global health and immigration –Persons with disabilities –Homeless persons –Challenges at the extremes of the age continuum

18. April 6, 200918 LMCC New Objectives (12) C 2 LEO Same material as before but re- structured. Read objectives for the details

19. April 6, 200919 Getting Started We can’t cover everything. Will concentrate on topics not well covered in the Toronto notes and material of greatest importance. Material will ‘jump around’ a bit –Slides were based on previous LMCC objectives. I didn’t get new objectives until the week before these lectures. Hence, material won’t flow by LMCC objectives but rather by content links.

20. April 6, 200920 INVESTIGATIONS (1) 78.2 –Determine the reliability and predictive value of common investigations –Applicable to both screening and diagnostic tests.

21. April 6, 200921 Reliability = reproducibility. Does it produce the same result every time? Related to chance error Averages out in the long run, but in patient care you hope to do a test only once; therefore, you need a reliable test

22. April 6, 200922 Validity Whether it measures what it purports to measure in long run, viz., presence or absence of disease Normally use criterion validity, comparing test results to a gold standard Link to I&PH web on validityvalidity

23. April 6, 200923 Reliability and Validity: the metaphor of target shooting. Here, reliability is represented by consistency, and validity by aim Reliability Low High Low Validity High

24. April 6, 200924 Gold Standards Possible gold standards: –More definitive (but expensive or invasive) test –Complete work-up –Eventual outcome (for screening tests, when workup of well patients is unethical; in clinical care you cannot wait) First two depend upon current state of knowledge and available technology

25. April 6, 200925 Test Properties (1) DiseasedNot diseased Test +ve90595 Test -ve1095105 100 200 True positivesFalse positives False negativesTrue negatives

26. April 6, 200926 Test Properties (2) DiseasedNot diseased Test +ve90595 Test -ve1095105 100 200 Sensitivity = 0.90Specificity = 0.95

27. April 6, 200927 2x2 Table for Testing a Test Gold standardDisease PresentAbsent Test Positivea (TP)b (FP) Test Negativec (FN)d (TN) SensitivitySpecificity = a/(a+c) = d/(b+d)

28. April 6, 200928 Test Properties (6) Sensitivity =Pr(test positive in a personSensitivity with disease) Specificity =Pr(test negative in a person without disease) Range: 0 to 1 –> 0.9:Excellent –0.8-0.9:Not bad –0.7-0.8:So-so –< 0.7:Poor

29. April 6, 200929 Test Properties (7) Values depend on cutoff point Generally, high sensitivity is associated with low specificity and vice-versa. Not affected by prevalence, if severity is constant Do you want a test to have high sensitivity or high specificity? –Depends on cost of ‘false positive’ and ‘false negative’ cases –PKU – one false negative is a disaster –Ottawa Ankle Rules

30. April 6, 200930 Test Properties (8) Sens/Spec not directly useful to clinician, who knows only the test result Patients don’t ask: if I’ve got the disease how likely is it that the test will be positive? They ask: “My test is positive. Does that mean I have the disease?” Predictive values.

31. April 6, 200931 Test Properties (9) DiseasedNot diseased Test +ve90595 Test -ve1095105 100 200 PPV = 0.95 NPV = 0.90

32. April 6, 200932 2x2 Table for Testing a Test Gold standard Disease Present Absent Test +a (TP) b (FP) PPV = a/(a+b) Test -c (FN) d (TN) NPV= d/(c+d) a+c b+d

33. April 6, 200933 Predictive Values Based on rows, not columns –PPV = a/(a+b); interprets positive test –NPV = d/(c+d); interprets negative test Depend upon prevalence of disease, so must be determined for each clinical setting Immediately useful to clinician: they provide the probability that the patient has the disease

34. April 6, 200934 Prevalence of Disease Is your best guess about the probability that the patient has the disease, before you do the test Also known as Pretest Probability of Disease (a+c)/N in 2x2 table Is closely related to Pre-test odds of disease: (a+c)/(b+d)

35. April 6, 200935 Test Properties (10) DiseasedNot diseased Test +veaba+b Test -vecdc+d a+cb+da+b+c+d =N odds prevalence

36. April 6, 200936 Prevalence and Predictive ValuesPredictive Values Predictive values for a test dependent on the pre-test prevalence of the disease –Tertiary hospitals see more pathology then FP’s; hence, their tests are more often true positives. How to ‘calibrate’ a test for use in a different setting? Relies on the stability of sensitivity & specificity across populations.

37. April 6, 200937 Methods for Calibrating a Test Four methods can be used: –Apply definitive test to a consecutive series of patients (rarely feasible) –Hypothetical table –Bayes’s Theorem –Nomogram You need to be able to do one of the last 3. By far the easiest is using a hypothetical table.

38. April 6, 200938 Calibration by hypothetical table Fill cells in following order: “Truth” DiseaseDiseaseTotal PV PresentAbsent Test Pos 4 th 7 th 8 th 10 th Test Neg 5 th 6 th 9 th 11 th Total 2 nd 3 rd 1 st (10,000)

39. April 6, 200939 Test Properties (12) DiseasedNot diseased Test +ve42550475 Test -ve75450525 500 1,000 Tertiary care: research study. Prev=0.5 PPV = 0.89 Sens = 0.85Spec = 0.90

40. April 6, 200940 Test Properties (13) DiseasedNot diseased Test +ve Test -ve 10,000 Primary care: Prev=0.01 PPV = 0.08 9,900 85 15 100 990 8,910 1,075 8,925 0.01*10000 0.85*100 0.9*9900

41. April 6, 200941 Calibration by Bayes’ Theorem You don’t need to learn Bayes’ theorem Instead, work with the Likelihood Ratio (+ve).Likelihood Ratio

42. April 6, 200942 Test Properties (9) DiseasedNot diseased Test +ve 90595 Test - ve 1095105 100 200 Pre-test odds = 1.00 Post-test odds = 18.0 Likelihood ratio (+ve) = LR(+) = 18.0/1.0 = 18.0

43. April 6, 200943 Calibration by Bayes’s Theorem You can convert sens and spec to likelihood ratios –LR+ = sens/(1-spec)  LR+ is fixed across populations just like sensitivity & specificity. Bigger is better. Posttest odds = pretest odds * LR+ –Convert to posttest probability if desired…

44. April 6, 200944 Calibration by Bayes’s Theorem How does this help? Remember: –Post-test odds = pretest odds * LR (+) To ‘calibrate’ your test for a new population: –Use the LR+ value from the reference source –Compute the pre-test odds for your population –Compute the post-test odds –Convert to post-test probability to get PPV

45. April 6, 200945 Converting odds to probabilities Pre-test odds = prevalence/(1-prevalence) –if prevalence = 0.20, then pre-test odds =.20/0.80 = 0.25 Post-test probability = post-test odds/(1+post-test odds) –if post-test odds = 0.25, then prob =.25/1.25 = 0.2

46. April 6, 200946 Example of Bayes’s Theorem (‘new’ prevalence 1%, sens 85%, spec 90%) LR+ =.85/.1 = 8.5 (>1, but not that great) Pretest odds =.01/.99 = 0.0101 Positive Posttest odds =.0101*8.5 =.0859 PPV =.0859/1.0859 = 0.079 = 7.9% Compare to the ‘hypothetical table’ method (PPV=8%)

47. April 6, 200947 Calibration with Nomogram Graphical approach avoids some arithmetic Expresses prevalence and predictive values as probabilities (no need to convert to odds) Draw lines from pretest probability (=prevalence) through likelihood ratios; extend to estimate posttest probabilities Only useful if someone gives you the nomogram!

48. April 6, 200948 Example of Nomogram (pretest probability 1%, LR+ 45, LR– 0.102) Pretest Prob. LR Posttest Prob. 1% 45.102 31% 0.1%

49. April 6, 200949 INVESTIGATIONS (2) State the effect of demographic considerations on the sensitivity and specificity of diagnostic tests Generally, assumed to be constant. BUT….. Sensitivity and specificity usually vary with severity of disease, and may vary with age and sex Therefore, you can use sensitivity and specificity only if they were determined on patients similar to your own Spectrum bias

50. April 6, 200950 The Government is extremely fond of amassing great quantities of statistics. These are raised to the nth degree, the cube roots are extracted, and the results are arranged into elaborate and impressive displays. What must be kept ever in mind, however, is that in every case, the figures are first put down by a village watchman, and he puts down anything he damn well pleases! Sir Josiah Stamp, Her Majesty’s Collector of Internal Revenue.

51. April 6, 200951 78.3: HEALTH PROMOTION & MAINTENANCE (1) Definitions of health Concepts of Health Promotion

52. April 6, 200952 Definitions of Health 1.A state of complete physical, mental and social well- being and not merely the absence of disease or infirmity. [The WHO, 1948] 2.A joyful attitude toward life and a cheerful acceptance of the responsibility that life puts upon the individual [Sigerist, 1941] 3.The ability to identify and to realize aspirations, to satisfy needs, and to change or cope with the environment. Health is therefore a resource for everyday life, not the objective of living. Health is a positive concept emphasizing social and personal resources, as well as physical capacities. (WHO Europe, 1986]

53. April 6, 200953 HEALTH PROMOTION Distinct from disease prevention. Focuses on ‘health’ rather than ‘illness’ Broad perspective. Concerns a network of issues, not a single pathology. Participatory approach. Requires active community involvement. Partnerships with NGO’s, NPO’s, etc.

54. April 6, 200954 HEALTH PROMOTION Ottawa Charter for Health Promotion (1996)Ottawa Charter Five key pillars to action: –Build Healthy Public Policy –Create supportive environments –Strengthen community action –Develop personal skills –Re-orient health services

55. April 6, 200955 HEALTH PROMOTION Health Education –Health Belief model –Stages of Change modelStages of Change Risk reduction strategies Social Marketing Healthy public policy –Tax policy to promote healthy behaviour –Anti-smoking laws, seatbelt laws –Affordable housing

56. April 6, 200956 78.1: Illness Behaviour “Describe the concept of illness behaviour and its influence on health care” Utilization of curative services, coping mechanisms, change in daily activities Patients may seek care early or may delay (avoidance, denial) Adherence may increase or decrease

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60. April 6, 200960 78.2: CRITICAL APPRAISAL (1) “Evaluate scientific literature in order to critically assess the benefits and risks of current and proposed methods of investigation, treatment and prevention of illness” Most will be covered in session on April 9 UTMCCQE does not present hierarchy of evidence (e.g., as used by Task Force on Preventive Health Services)Task Force

61. April 6, 200961 Hierarchy of evidence (lowest to highest quality, approximately) Expert opinion Case report/series Ecological (for individual-level exposures) Cross-sectional Case-Control Historical Cohort Prospective Cohort Quasi-experimental Experimental (Randomized) } similar/identical

62. April 6, 200962 78.1: MEDICAL ECONOMICS (1) Define the socio-economic rationales, implications and consequences of medical care Medical care costs society financial and other resources. This objective aims to raise awareness of these types of issues.

63. April 6, 200963 MEDICAL ECONOMICS (2) Is there a net financial benefit from medical care? How do we value non-fiscal benefits such as quality of life, ‘health’, not being dead? Should resources be spent on health or other societal objectives? How do we value non-traditional expenditures, etc which impact on health (Healthy Public Policy).

64. April 6, 200964 MEDICAL ECONOMICS (3) “Outline the principles of cost-containment, cost benefit analysis and cost effectiveness” Not addressed in UTMCCQE

65. April 6, 200965 Principles of cost-containment Eliminate ineffective care Reduce costs of effective care –Substitute cheaper but equally effective care, day surgery for hospital admission, nurse practitioners for some primary care, generic drugs –Reduce unit costs reduce salaries (risk of reduced effectiveness) or fees (but quantity provided may increase)

66. April 6, 200966 Types of economic analysis [Costs always expressed in dollars] Cost-minimization: assume equal outcomes Cost-benefit: outcomes in dollars *Cost-effectiveness: outcomes in natural units (deaths, days of care or disability, etc.) *Cost-utility: outcomes in QALYs (quality- adjusted life years)

67. April 6, 200967 78.1: VITAL STATISTICS INFORMATION What are the key causes of illness or death in Canada? Common things are common – using epidemiology can help you run a better clinical practicekey causes of illness or death How have disease incidence and mortality change in Canada in the past 20 years? –Little good information on disease incidence except for cancer (cancer registries)

68. April 6, 200968 13/7/200868 # deaths in Canada from 1979-2004; men and women.

69. April 6, 200969 13/7/200869 Mortality RATES in Canada from 1979-2004; men and women.

70. April 6, 200970 VITAL STATISTICS VITAL STATISTICS (2) Leading causes of death –‘Cardiovascular disease’: 37% Heart disease: 20% ‘Other circulatory disease’: 10% ‘Stroke’ 7% –‘Cancer’: 28% Lung cancer: 9% (M); 6% (W) Breast cancer: 4% (W) Prostate cancer: 4% (M) –Respiratory Disease: 10% –Injuries: 6% –Diabetes: 3% –Alzheimer’s: 1%

71. April 6, 200971 CANCER: 30.3% Circ Disease: 27.6% †† † † Pneumonia & influenza grouped with respiratory disease. Would increase infectious % to about 3.4%.

72. April 6, 200972 CANCER: 29.8% Circ Disease: 29.0% † † † Pneumonia & influenza grouped with respiratory disease. Would increase infectious % to about 3.5%.

73. April 6, 200973 CANCER: 31.6% Circ Disease: 27.3% † † † Pneumonia & influenza grouped with respiratory disease. Would increase infectious % to about 3.3%.

74. April 6, 200974 Sex ratio (M/F) in Canada from 1979-2004.

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77. April 6, 200977 PYLL’s for various conditions, 2001

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82. April 6, 200982 Vital Stats (3) In the USA, it is estimated that 86,000 people are sent to ER every year after a fall caused by a cat or dog! –Mainly minor injuries but 10% are fractures, internal bleeding, etc. –Cats mainly trip people by walking under your feet. –Dogs (the main source of injuries!) causes trips, push people over or pull them over on walks. Watch out!!

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84. April 6, 200984 Overall trends in mortality from Cancer 1976-2005: rates and numbers

85. April 6, 200985 Overall trends in mortality 1976-2005: rates and numbers

86. April 6, 200986 Cancer and Age Age-Specific Incidence Rates for All Cancers by Sex, Canada, 2003 Surveillance Division, CCDPC, Public Health Agency of Canada

87. April 6, 200987 Cancer and Age Age-Specific Mortality Rates for All Cancers by Sex, Canada, 2003 Surveillance Division, CCDPC, Public Health Agency of Canada

88. April 6, 200988 Time trends in incidence - Males Age-Standardized Incidence Rates (ASIR) for Selected Cancer Sites, Males, Canada, 1978-2007 Surveillance and Risk Assessment Division, CCDPC, Public Health Agency of Canada Estimated

89. April 6, 200989 Time trends in mortality - Males Age-Standardized Incidence Rates (ASIR) for Selected Cancer Sites, Males, Canada, 1978-2007 Surveillance and Risk Assessment Division, CCDPC, Public Health Agency of Canada Estimated

90. April 6, 200990 Time trends in incidence - Females Age-Standardized Incidence Rates (ASIR) for Selected Cancer Sites, Females, Canada, 1978-2007 Surveillance and Risk Assessment Division, CCDPC, Public Health Agency of Canada Estimated

91. April 6, 200991 Time trends in mortality - Females Age-Standardized Incidence Rates (ASIR) for Selected Cancer Sites, females, Canada, 1978-2007 Surveillance and Risk Assessment Division, CCDPC, Public Health Agency of Canada Estimated