Pharmacy in Public Health Epidemiology Course date etc

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 • 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

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

Key Assumption: Exposure-then-Disease Figure 10. 2

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 SES: Male Female Child Adult High 0% 67% 0% 3% Medium 0% 92% 0% 14% Low 73% 84% 55% 54% Unknown --N/A--- 78% --N/A--- 13% Adapted from Simonoff, 1997

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

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?

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.

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

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

Cumulative 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)

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)

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, 000 p x 0. 5 y/p = 10, 000 person-years IR = 5/10, 000 (=50/100, 000)

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. 25 year) = 5 persons x 0. 25 years = 1. 25 person-years 3 left at 6 months (0. 5 year) = 3 persons x 0. 5 years = 1. 5 person-years 2 left at 9 months (0. 75 years)=2 persons x 0. 75 years = 1. 5 person-years Person-years for patients leaving the clinic: 4. 25 person-years 190 stay all 12 months (1 year) = 190 persons x 1 year = 190 person-years Total person-years for denominator is 190 + 4. 25 = 194. 25 Incidence Density = 16 / 194. 25 = 8. 24% Figure 10. 6

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

Descriptive Study Designs • There are three types of study designs 1. Case report (or case series) 2. Cross-sectional 3. Correlational • They differ in these ways: – Ability to tie cause to effect – Ability to allow comparisons across time or with other groups

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

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: 1. Cohort 2. Case control

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

Calculating Relative Risk using a 2 x 2 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

EXAMPLE - Calculating Relative Risk Exposed Not Exposed Disease 300 150 No Disease 200 350 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

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

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

EXAMPLE - Calculating Odds Ratio Exposed Not Exposed Disease 300 150 No Disease 200 350 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

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

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.

Case Example • The following slides are optional

Handwritten prescription and label placed on prescription vial Figure 10. 1

Population level data for Clinic Patients with medication-related Hyperthyroidism for current year (n=16) and the previous year Characteristics: THIS YEAR LAST YEAR (% or mean) Total hypothyroid patient population 200 195 Subset of population with hyperthyroidism due to medication 16 4 4 (25%) male 12 (75%) female 3 (75%) female Age, years (mean ± std dev) 46 (± 14) 44 (± 12) Years since diagnosis (mean ± std dev) 15 (± 22) 14 (± 24) 16 (100%) 4 (100%) Average l-thyroxine dose (mean ± std dev) 38 mcg (± 10 mcg) 45 mcg (± 18 mcg) Months on current dose (mean ± std dev) 15 (± 56) 14 (± 53) 1. 5 (± 0. 04) 3 (± 4. 5) Gender (%) ICD-9 -CM code 244. 9 (%) Months since most recent symptoms appeared (mean ± std dev) Table 10. 1

Cross-Sectional Survey of Patients with medicationrelated Hyperthyroidism for one year (n=16) Characteristics: Gender (%) TOTAL 4 (25%) male 12 (75%) female Age, years (mean ± std dev) 46 (± 14) Years since diagnosis (mean ± std dev) 18 (± 29) Average l-thyroxine dose (mean ± std dev) 32 mcg (± 16 mcg) Months on current dose (mean ± std dev) 18 (± 64) Months since most recent symptoms appeared (mean ± std dev) 1 (± 0. 34) Pharmacies used during past year Rx corner 12 (75%) (can list more than one) Chain Scripts 4 (25%) Clinic pharmacy 8 (50%) VA mail order 1 (7%) Brand name of medication Synthroid® 4 (25%) Levo-throid® 4 (25%) levo-thyroxine (Gen. X brand) 8 (50%) Usual number of days in prescription (mean ± std dev) 30 (± 2) Self-reported compliance 28 (± 3) (mean days/ month took dose ± std dev) Medical Lab where T 4 / TSH analyzed MML 16 (100%) Table 10. 2

Sample of Case Report Data for five of the 16 clinic patients with medication-related hyperthyroidsim Characteristics: CF LA CW HT HC Gender F F M Age 62 23 43 13 37 02/1988 04/08 11/1997 05/04 02/09 25 mcg 50 mcg 25 mcg Rx Corner Rx Corner Brand of l-thyroxine last dispensed Gen. X Date last prescription filled prior to onset of Jan 29 Feb 1 Jan 24 Jan 29 Jan 25 Feb 2 Feb 5 Jan 29 Feb 4 Jan 30 Date of diagnosis Current l-thyroxine dose Pharmacy filling last prescription hyperthyroidism symptoms Date hyperthyroidism symptoms appeared Table 10. 3

Relative Risk from Cohort Study of Medication Errors Figure 10. 9

Odds Ratios from Case-Control Study of Med Errors Figure 10. 11