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Pharmacy in Public Health: Epidemiology

Pharmacy in Public Health: Epidemiology. Course, date, etc. info. Learning Objectives. Explain how epidemiology is used in public health List the different types of epidemiology studies and give an example of a study design used for each type

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Pharmacy in Public Health: Epidemiology

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  1. Pharmacy in Public Health:Epidemiology Course, date, etc. info

  2. Learning Objectives • Explain how epidemiology is used in public health • List the different types of epidemiology studies and give an example of a study design used for each type • Given an epidemiological measure of disease, explain what it means • Given data about a disease in a population, calculate prevalence, incidence, relative risk, and/or odds ratio

  3. Introduction • Epidemiology is the study of disease in a population; it is considered the science of public health • Studies the determinants and distribution of disease • Assumes disease does NOT occur at random • If causes can be identified, disease may be prevented • It is a collection of study designs and methods for calculating disease rates • Pharmacoepidemiology is a subset that focuses on medication-related disease

  4. Key Assumption: Exposure-then-Disease Figure 10.2

  5. EXAMPLE Using the death rates given below, what can you say about premature death risk in the population? Death Rates from a Single Cause by Gender, Age, & Economic Status Adapted from Simonoff, 1997

  6. Roles for Epi in Public Health • Monitor health of a population • Respond to emerging public health problems • Promote research and use of evidence-based interventions • Evaluate effectiveness of a program • Develop public health policy and law • Set funding priorities for research and intervention programs

  7. Understanding an Outbreak • Epidemiology is used to better understand a disease outbreak by answering these questions • What is it? • How big is the outbreak? • Who is affected by the disease? • Where is the disease occurring? • When does the disease occur? • Why does the disease occur?

  8. Measures of Disease Frequency • Prevalence (total number of cases) • Incidence (number of new cases) • Mortality (number of deaths) • EXAMPLE: In the past month, Town A reported five new cases of HIV/AIDS. This brings the total number of HIV/AIDS cases this year to 26. In Town B, there were 10 new cases and over 100 total cases during the same time periods.

  9. Prevalence rates • Need an indication of how the number of cases relates to the population • Prevalence rate • Total number of cases during a specified time period divided by the population count

  10. Calculating a Prevalence Rate EXAMPLE Five new cases of HIV/AIDS were reported. This brings the total number of active HIV/AIDS cases this year (2006) to 56; total population is 100,000 and population at risk if HIV/AIDS is 20,000 Prevalence rate calculation: Prevalence rate (P) = 56 active HIV/AIDS cases /100,000 total population P = 56 per 100,000 (in 2006) Prevalence rates are increased by: An increase in the number of new cases (↑ incidence) A reduction in deaths due to disease (↓ mortality) New treatments that prolong life but not cure the disease Prevalence rates are decreased by: Reduced number of new cases Increased number of cures

  11. Cumulative Incidence rates • Incidence rates • Cumulative incidence rate (number of new cases in a specified time period divided by number of population that is at risk of the disease)

  12. Incidence Rates / Incidence Density • Incidence Rates • Incidence rate or density (number of new cases in a specified time period divided by the total number of person-time when at risk)

  13. Comparing Incidence Rates • EXAMPLE: Five new cases of HIV/AIDS were reported. This brings the total number of HIV/AIDS cases this year to 56; total population is 100,000 and population at risk of HIV/AIDS is 20,000. • Suppose the actual time at risk for any one individual is estimated at 183 days per year (= 0.5 years per individual). • Cumulative Incidence Rate calculation for one year: • Use 5 new cases and 20,000 at-risk individuals • CI = 5/20,000 (=25/100,000) • Incidence Rate calculation for person-years: • Use 5 new cases in numerator; • Adjust denominator: 20,000p x 0.5y/p = 10,000 person-years • IR = 5/10,000 (=50/100,000)

  14. Example: Calculation of annual Incidence Density for suspected medication-related hyperthyroidism cases for the Clinic Total population at the start of the year was 200 There were 16 new cases of medication-related hyperthyroidism No new patients were admitted, but 10 patients left during the year: 5 left at 3 months (0.25year) = 5 persons x 0.25years = 1.25person-years 3 left at 6 months (0.5year) = 3 persons x 0.5years = 1.5 person-years 2 left at 9 months (0.75 years)=2 persons x 0.75years = 1.5 person-years Person-years for patients leaving the clinic: 4.25 person-years 190 stay all 12 months (1year) = 190 persons x 1year = 190 person-years Total person-years for denominator is 190 + 4.25 = 194.25 Incidence Density = 16 / 194.25 = 8.24% Figure 10.6

  15. Study Designs • There are three main categories of epidemiology studies • Descriptive • Analytical • Interventional • Potential disease risks are often identified in descriptive studies then studied in analytical and interventional designs

  16. Descriptive Study Designs • There are three types of study designs • Case report (or case series) • Cross-sectional • Correlational • They differ in these ways: • Ability to tie cause to effect • Ability to allow comparisons across time or with other groups

  17. Summary of Descriptive Designs Correlate Cross-Section Characteristic Case XXX --- XX XXX --- XXX --- • Individual-level data • Population-level data • Links cause-effect • Timeline measured • Allows comparisons to other groups • Observational • Experimental --- XXX --- --- XXX XXX --- XXX --- X --- XXX XXX ---

  18. Analytic Study Designs • These designs must be able to: • Establish that exposure preceded disease • Determine if risk factor is necessary and/or sufficient • Determine if risk factor is a direct or indirect cause • Rule out confounding factors • Eliminate or reduce systematic bias • Two basic types: • Cohort • Case control

  19. Cohort Study • Use two groups of subjects • Subjects selected on basis of exposure status • Exposed • Not exposed • May be prospective or retrospective • Seeks to determine whether an exposure affects the likelihood that a person will get the disease • Results usually reported as Relative Risk

  20. Calculating Relative Risk using a 2x2 Table A ratio of percent of exposed individuals who get the disease compared to percent of not-exposed people who get the disease Figure 10.8

  21. EXAMPLE - Calculating Relative Risk RR = a/(a+c) ÷(c/(c+d) = 300/450 ÷ 150/500 = 2.23 Interpreting results: RR >1; exposure increases risk of disease RR=1; no difference due to exposure RR<1; exposure is protective and reduces risk of disease or When 95% CI includes a “1” then no difference in risk is seen (such as 95% CI of 0.55 – 3.6) Figure 10.8

  22. Case Control Study • Use two groups of subjects • Subjects selected on basis of disease status • Disease • No Disease • Retrospective only • Seeks to determine whether a person with the disease was more likely exposed to the risk factor than someone without the disease • Results usually reported as odds ratios

  23. Calculating an Odds Ratio (Cross-Products Ratio) A ratio of the probabilities diseased individuals were/were not exposed is compared to the ratio of probabilities that disease-free people were/were not exposed Figure 10.10

  24. EXAMPLE - Calculating Odds Ratio OR = (a/c) ÷(b/d) = (300/150)÷ (200/350) = 2/0.5714 = 3.5 Interpreting results: OR >1; person with disease was more likely exposed OR=1; no difference in exposure likelihood OR<1; person with disease was less likely exposed or When 95% CI includes a “1” then no difference in likelihood of exposure (such as 95% CI of 0.25 – 2.7) Figure 10.8

  25. Interventional Study Designs • Use same approach as experimental design • Random assignment to study arms • Researcher controls the exposure • Indirect method for learning more about a disease • Used to test the effects of removing risk factors or adding protective factors on subsequent disease development • Never used to directly test whether an exposure causes a disease

  26. Summary • Epidemiology is the scientific tool used in public health to describe disease behavior and distribution within a population; • Measures of disease frequency include prevalence, incidence, and mortality rates; • Study designs are used to establish exposure-to-disease associations and timelines, and • Pharmacoepidemiology is the application of these methods to study adverse events after a medication is approved.

  27. Case Example • The following slides are optional

  28. Handwritten prescription and label placed on prescription vial Figure 10.1

  29. Population level data for Clinic Patients with medication-related Hyperthyroidism for current year (n=16) and the previous year Table 10.1

  30. Cross-Sectional Survey of Patients with medication-related Hyperthyroidism for one year (n=16) Table 10.2

  31. Sample of Case Report Data for five of the 16 clinic patients with medication-related hyperthyroidsim Table 10.3

  32. Relative Risk from Cohort Study of Medication Errors Figure 10.9

  33. Odds Ratios from Case-Control Study of Med Errors Figure 10.11

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