NR 503 - Study Guide for Final Exam

. Objectives of epidemiology.2-7 Step 1. Understanding the etiology or cause of a disease (risk factors) Step 2. Finding out the extent that a disease or health problem affects a community or population. Step 3. Determine the natural history or prognosis Step 4. Evaluate existing and newly developed preventative therapeutic measures and modes of healthcare delivery Step 5. Provide the foundation for developing public policy relating to environmental problems, genetic issues, and other considerations regarding disease prevention and health promotion. 2. Define, compare, calculate, and interpret Measures of Morbidity .41.58 a. Incidence rate.41.51 (# of NEW cases of a disease occurring in the population during a specified period of time / # of persons who are at risk of developing the disease during that period of time) x 1000 = Incidence rate per 1,000 : the NEW cases of a disease over a period of time. b. Attack rate.46 - special form of cumulative incidence - Used for diseases of short observation time period - Not a true rate because the time dimension is often uncertain (food borne outbreaks) = (# of new cases among population during period / population at risk at beginning of period) x 100 (expressed as %) c. Prevalence.46 : the EXISTING cases of a disease over a period of time. (# of cases of a disease present in the population at a specified time / # of persons in the population at that specified time) x 1,000 = Prevalence per 1,000 3. Understand why incidence data are important for measuring risk.  Measures risk (probability of developing disease)  Useful for investigating determinants of disease (not survival)  To investigate causes of disease  Need to know population ‘at risk’ or ‘person-time’ at risk 4. Define, compare, calculate, and interpret Measures of Mortality a. Cause-specific mortality rate.64.65 =(Total number of deaths due to x cause / total population at mid year) x 1,000 =(N deaths from leukemia in one year in children younger than 10 years of age / N children in the population younger than 10 years of age at midyear) x 1,000 b. Annual mortality rate .64 -annual death rate, or mortality rate from all causes. (total # of deaths from all causes in 1 year / total population at mid year ) x 1,000 c. Case-fatality.65 --what percentage of people who have a certain disease die within a certain time after their disease was diagnosed? =(# of deaths due to a certain disease/total # suffering from that disease) x 100 % -Measure of the severity of the disease -As therapy improves, case-fatality would be expected to decline. d. Proportionate mortality. This is Not a rate. 66 -the proportionate mortality from cardiovascular disease in the U.S. in 2010 (percent, %) -of all deaths in the US, what proportion was caused by cardiovascular disease? =( # of deaths from cardiovascular diseases in US in 2010 / total deaths in the US in 2010) x 100 5. Assess the Validity.89 and Reliability105.110 of Diagnostic and Screening Tests a. Define, compare and calculate measures of validity, including sensitivity and specificity. -Validity of test: its ability to distinguish between who has a disease and who does not. -Sensitivity of test is defined as the ability of the test to identify correctly those who have the disease. -Specificity of test is defined as the ability of the test to identify correctly those who do not have the disease. Have a Disease Do not have Disease Positive True Positive (TP) Have the disease And test positive a False Positive (FP) Do not have the disease But test positive b Positive predictive value = (TP/TP+FP)x10 0 =(a/a+b)x100 Negative False Negative (FN) Have the disease But test negative c True Negative (TN) Do not have the disease And test negative d Negative Predictive value =TN/TN+FN Sensitivity = TP /TP+FN Specificity =TN /TN+FP b. Define and calculate positive predictive value.100. -what is the probability that the patient has the disease? -PPV is proportion of people who screened positive and actually have the disease (True positive/All positives)x100 c. Relationship between Positive predictive value (PPV) and disease prevalence.101 : the higher the prevalence, the higher the predictive value. Therefore, a screening program is most productive and efficient if it is directed to a highrisk target population. Sensitivity = 99%, Specificity = 95%