NR503 / NR 503 Final Exam Study Guide (Latest 2022 / 2023): Population Health, Epidemiolog, Study Guides, Projects, Research of Nursing

Download NR503 / NR 503 Final Exam Study Guide (Latest 2022 / 2023): Population Health, Epidemiolog and more Study Guides, Projects, Research Nursing in PDF only on Docsity! NR 503 Study Guide for Final Exam 1. Objectives of epidemiology a. b. Understand the aetiology or cause of a disease (risk factors) Find out the extent that a disease or health problem affects a community or population Determine the natural history or prognosis Evaluate existing and newly developed preventative therapeutic measures and modes of healthcare delivery 2. Define, compare, calculate, and interpret Measures of Morbidity a. d Incidence rate: measurement of the number of new individuals who contract a disease during a particular period of time i. Calculation: Number of new cases of disease or injury during specified period DIVIDED BY Size of population at start of period Attack rate: Same as risk, proportion of individuals in a population (initially freeof disease) who develop the disease within a specified time interval. i. Calculation: Total number of new cases DIVIDED BY The total population Prevalence: measurement of all individuals affected by the disease at a particular time i. Calculation: Number of new cases of disease or injury during specified period DIVIDED BY Time each person was observed, totaled for all persons . These rates are used to measure disease occurrence and make comparisons between population groups. They are commonly used measures that help our understanding of the distribution of disease in a given population. 3. Understand why incidence data are important for measuring risk. a. Incidence is important for measuring risk because it tells you the rate at which new people are contracting the disease 4. Define, compare, calculate, and interpret Measures of Mortality a. Cc. Mortality: a measure of the frequency of occurrence of death in a defined population during a specified interval. Morbidity and mortality measures are often the same mathematically; it's just a matter of what you choose to measure, illness or death. i. Calculation: Deaths occurring during agiven time period DIVIDED BY Size of the population among which the deaths occurred TIMES 10" Cause-specific mortality rate: The mortality rate from a specified cause fora population. i. Calculation: The number of deaths attributed to a specific cause DIVIDED BYThe size of the population at the midpoint of the time period Annual mortality rate: The rate of death ina one-year period. i. Calculation: Deaths occurring within the one-year period DIVIDED BY Size of population in which the deaths occured d. Case-fatality: the proportion of deaths within a designated population of "cases" (people with a medical condition) over the course of the disease i. Calculation: he number of deaths from a specified disease over a defined period of time DIVIDED BY The number of individuals diagnosed with the disease during that time T/MES 100 (final answer should be percentage) e. Proportionate mortality: the proportion of deaths in a particular population overa specified period of time, attributable to different causes i. Calculation: Number of deaths within a population due to a specific disease or cause DIVIDED BY the total number of deaths in the population during atime period such as a year. 5. Assess the Validity and Reliability of Diagnosticand Screening Tests a. Define, compare and calculate measures of validity, including sensitivity and specificity. i. Sensitivity identifies the proportion of individuals who truly DO have the disease AND are given a positive test result. | find it helpful to remember: sensiTivity = sensitive to the Truth (i.e. do have disease + do have positive result) 1. We want to know what proportion of individuals who have the disease (atc) were given a positive test result (a), therefore... a. Sensitivity = a/(a+c) ii. Specificity identifies the proportion of individuals who truly DO NOT have the disease AND were given the correct negative test result. | find it helpful to remember: specificity = speciFies the False (i.e. do not have disease and do not have positive test result 1. This time we want to know what proportion of people who do not have the disease (b+d) were given the correct negative test result (d), therefore... a. Specificity = d/(b+d). b. Define and calculate positive predictive value. i. Positive Predictive Value: The probability that subjects with a positive screening test truly have the disease. 1. Calculation: a/(a+c) c. Understand positive predictive value (PPV) and relationship to disease prevalence and specificity of a screening test. i. Higher prevalence/specificity rates=higher ppvrates 6. Epidemiologic transition a. Phase of development witnessed by a sudden and stark increase in population growth rates brought by improved food security and innovations in publichealth and medicine, followed by a re-leveling of population growth due to subsequent declines in fertility rates. 7. Study designs (case-control, cross sectional, prospective and retrospective cohort, clinical trial) a. Case-control study: An observational study that compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease or outcome (controls) and looks back retrospectively to compare how frequently additional support for a causal relationship. However, absence of specificity in no way negates a causal relationship. 10. Estimating Risks (risk measures) a. Calculate and interpret relative risk ina cohort study (i.e., estimate of the risk measure). i. Relative Risk: the ratio of the probability of an event occurring (for example, developing a disease, being injured) in an exposed group tothe probability of the event occurring in a comparison, non-exposed group. 1. Calculation: the probability of an event occurring for group 1 DIVIDED BY the probability of an event occurring for group 2 b. Interpret an odds ratio in a cohort study and in a case-control study i. Odds Ratio: they refer to the ratio of the odds of an event occurring in the exposed group versus the unexposed group. ii. Relative Risk is very similar to Odds Ratio, however, RR is calculated by using percentages, whereas Odds Ratio is calculated by using the ratio of odds c. Calculate and interpret absolute risk i. Absolute Risk: is the absolute difference in outcomes between one group (usually the control group) and the group receiving treatment. The percentage tells you how much the risk of something happening decreases if a certain intervention happens. 1. Calculation: the number of events (good or bad) in treated or control groups DIVIDED BY the number of people in that group. d. Purpose of matching in case-control studies i. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables. 11. Attributable Risk a. Calculate and interpret the attributable risk for an exposed groupanda population. i. Attributable Risk: also known as excess risk, this is the difference in rate of a condition between an exposed population and an unexposed population. 1. Calculation: AR=le-lu a. Once ARis calculated, then percent can be determined i. 100 TIMES (le-lu)/le b. le= Incidence in exposed c. lu=Incidence in unexposed b. Comparison of relative risk and attributable risk i. Relativerisk estimates the magnitude of an association between exposure and disease, based on the incidence of disease in the exposed group relative to the unexposed group. Attributable risk, or risk difference, is the absolute difference in incidence between an exposed and unexposed group. 12. Randomizedtrials a. Internal validity: how well an experiment is done, especially whether it avoids confounding (more than one possible independent variable [cause] acting at the same time). The less chance for confounding in a study, the higher its internal validity is. Generalizability (external validity): the validity of generalized (causal) inferences in scientific research, usually based on experiments as experimental validity. In other words, it is the extent to which the results of a study can be generalized to other situations and to other people. 13. Evaluating Screening Programs a. Sources of bias that must be taken into account in assessing study findings, including referral bias, length-biased sampling, lead-time bias, five-year survival, and over-diagnosis bias. i. Referral Bias: a situation where the chance of exposed cases being admitted to the study is different to exposed controls. This happens frequently when cases are selected in a hospital whose activity is linked to the studied exposure. ii. Length-Biased sampling: a form of selection bias, a statistical distortion of results that can lead to incorrect conclusions about the data. Length time bias can occur when the lengths of intervals are analysed by selecting intervals that occupy randomly chosen points in time or space. iii. Lead-time Bias: the length of time between the detection of a disease (usually based on new, experimental criteria) and its usual clinical presentation and diagnosis (based on traditional criteria). iv. Five-Year Survival: a type of survival rate for estimating the prognosis ofa particular disease, normally calculated from the point of diagnosis. Lead time bias from earlier diagnosis can affect interpretation of the five-year survival rate. v. Over-Diagnosis Bias: the diagnosis of "disease" that will never cause symptoms or death during a patient's ordinarily expected lifetime. Overdiagnosis is a side effect of screening for early forms of disease. 14. Considerations when evaluating individual data a) Are the characteristics of the two groups comparable—demographically, medically, and in terms of factors relating to prognosis? b) Are the measurement methods comparable (e.g., diagnostic methods and the way disease is classified) in both groups? 15. Calculations and interpretations a. Risk ratio: the ratio of the probability of an event occurring (for example, developing a disease, being injured) in an exposed group to the probability of the event occurring in a comparison, non-exposed group. Relative risk: See * Odds ratio: they refer to the ratio of the odds of an event occurring in the exposed group versus the unexposed group . Attributable risk: also known as excess risk, this is the difference in rate ofa condition between an exposed population and an unexposed population. Incidence rate: measurement of the number of new individuals who contract a disease during a particular period of time Disease incidence: conveys information about the risk of contracting the disease Annual mortality rate: or death rate, is a measure of the number of deaths (in general, or due toa specific cause) ina particular population, scaled to the size of that population, per unit of time. Positive predictive value: The probability that subjects with a positive screening test truly have the disease. Sensitivity: identifies the proportion of individuals who truly DO have the disease AND are given a positive test result. Specificity: identifies the proportion of individuals who truly DO NOT have the disease AND were given the correct negative test result. Prevalence: indicates how widespread the disease is Concordance rate: the probability that a pair of individuals will both havea certain characteristic, given that one of the pair has the characteristic.