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56 Cards in this Set
- Front
- Back
Why is EBM needed?
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-lots of junk science in the market place for medical info
-need to make the best possible clinical decisions often in the absence of a single, definitive best course of action -problems have led the medical community to develop and emphasize: small area variations analysis, outcomes research, clinical practice guidelines |
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Define EBM
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conscientious explicit, and judicious use of current best evidence in making decisions about the care of individual patients
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Arguments for EBM
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-de-emphasizes the institution, unsystematic clinical evidence, and pathophysiological rationale as sufficient grounds for decision making
-many therapies used by physicians not backed by solid evidence -to much potential for fraud in the medical marketplace |
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Arguments against EBM
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-proponents are antagonistic
-no evidence that EBM works -individual patient should not be looked at as aggregate data -may cause conditional compassion |
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define paradigm
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a combination of a set of methods and a phylisophical approach
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what is the guiding paradigm
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best available science at a point in time
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what is clinical epidemiology
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study of the distribution and determinants of health and disease frequency in human populations
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what is the basic tenet of clinical epidemiology
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disease does not happen at random and is quantifiable
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what is clinical epidemiologies aims
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to profile typical and atypical patients, determine history and patterns, surveillance, search for causes, and test new treatments
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list criteria for causality
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-establish a link between drug X and effect Y
-strength of the association -consistency of the observed evidence -specificity of the relationship -temporality of the relationship -dose-response relationship -biological plausibility -coherence of the evidence -experimental conformation -reasoning by analogy |
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characteristics of descriptive studies
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-goal is to record events, observations, and/or activity
-does not provide info about causes or clinical efficacy -does provide initial picture of some clinical phenomenon, and suggests areas of more in-depth research |
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examples of descriptive studies
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-case reports
-case series (cluster reports) -clinical series -population (prevalence) studies/surveys -course/program description |
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characteristics of explanatory studies
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-goal is to compare and explain differences between things, and to shed light on etiology or prognosis of disease
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what are the names of the two approaches to explanatory studies
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-experimental
-observational |
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experimental study characteristics
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-known as control trials, clinical trials, RCT, or intervention studies
-primary feature is that investigator controls intervention, and methods in great detail -most powerful in terms of causal inferences |
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observational study characteristics
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-investigator is passive observer
-study natural course of health events, gather data, classify and sort them -through making comparisons across groups, investigators try to provide insight as to causes and effects -less than perfect approach -never as good as a RCT |
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differences between cases and controls
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-a case can be a subject who has the outcome of interest when doing a case-control study
-sometimes a group of people (cohort) that share a characteristic are watched for development of outcomes (cohort/follow-up study) -key is the directionality of the study - |
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differences between retrospective and prospective
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-retro studies begin and end in the present, but consist of looking back in time for data collection.
-prospective studies begin in the present and measure outcomes that lie in the future -use retro and pro to describe the time frame for collection of data only |
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define validity
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validity refers to the degree to which a measurement represents the true value
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define reliability
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reliability relates to the reproducibility of measurements
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define unsystematic variability
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-errors that ocurr unpredictably and are minor
-they do decrease reliability and validity of a study -random variations tend to even out (regression to the mean) |
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types of unsystematic variability
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-subject variation
-observer variations |
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define systematic error
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-more serious than unsystematic variability
-predictable variation known as bias |
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types of systematic error
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-investigator/interviewer bias
-subject bias |
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define investigator/interviewer bias
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those doing the study are looking for an outcome or may have different approaches to asking subjects questions
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define subject bias
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-pre-existing beliefs
-social desirability bias -recall bias -hawthorne effect -test-retest bias -rebound bias |
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list ways to control measurement error
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-best way is to keep subjects and investigators blind
-establish clear standards for measuement -train observers -use multiple observers or data sources, then assess inter-rater reliability (IRR) or to what extent the observers agree (between 0-1)(kappa=correlation coefficient which accounts for chance agreement) |
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define a target population
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population of people that a study tries to generalize a hypothesis about (all pediatric patients)
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define an accessible population
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portion of target population from which information is attainable from (pediatric patients admitted to hospitals in US between 1995 and 2005)
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define sample population
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portion of accessible population that is used for study (200 pediatric patients from 5 different hospitals throughout US)
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what are 3 basic sampling methods
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-systematic
-random -convenience |
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define systematic sampling
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picking every nth person
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define random sampling
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base picks from a computerized random number chart
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define convenience sampling
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volunteers or recruits
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define fundamental principles of case series
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-share experiences, new observations
-provides the intial steps toward sophisticated research -generates testable research hypothesis -initial (crude) quantification of incidence rates -prototypical descriptive methods |
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define fundamental principles of case-control studies
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-begin with an outcome of interest and look back in time to compare similarities between subjects
-normally done all retrospectively |
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application of case reports and series
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-exceptions to the rule
-natural history of disease -health services planning -therapy: OK for feasibility, or potential effectiveness. NOT OK for efficacy or effectiveness statement UNLESS there is a dramatic (slam-bang) effect |
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problems with case reports and series
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-"n of 1" is anecdotal info
-no controls of any kind -small possibility of sampling variation explaining observed outcome (chance) -investigator may have been looking for the cause (bias) -alternative explanations (confounders) |
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Advantages of case-control studies
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-relatively easy and quick
-inexpensive -good for studying rare diseases or outcomes -good for studying multiple exposures -analysis of results is straight forward |
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Disadvantages of case-control studies
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-sampling method employed
-normally only supplies suggestive, and not definitive causal information -diagnostic bias -reporting bias -case definition (needs to be clear and specific) -any source of control selection can be problematic and often need to use multiple control groups -possibility to over match -ascertaining exposure subject to bias (recall and social desiribility) -researcher bias as information bias -data sources may not be valid and/or reliable |
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what is the structure of a cross-sectional study design
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-investigator makes all measurements at a single point in time
-well suited to the goals of describing variables, their distribution patterns, and correlates -useful for examination of association, but is difficult to choose/specify which variable is the cause and which is the effect |
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what are predictor variables
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constitutional factors such as age, gender, race
thse cannot be changed or altered by other variables |
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what are outcome variables
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variable that you believe might be influenced or modified by some treatment or exposure.
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what are the stengths of X-S studies
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-fast and inexpensive
-no problem with loss to follow up -gives estimate of the prevalence of one or more risk factor -convenient for initial investigation of networks of causal links -good first step to cohort study |
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what are some disadvantages to X-S studies
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-sampling
-questioning biases -response biases-non-responders may differ in some way that is related to the outcome -time order problems -not good for studying rare diseases; if small sample of population is used |
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what is the structure of a cohort study design
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-involves classifying subjects by exposure status
-follow them in groups over time -two goals are to describe incidence of certain outcomes over time, and to analyze associations between risk factors and those outcomes -may be done retro or prospectively |
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what are the 6 steps in designing a case-control study
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step 1: specify research question
step 2: specify (sample) cases step 3: draw sample of controls step 4: measure predictor variables step 5: compare cases and controls (prior exposure patterns) step 6: draw appropriate conclusions |
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what are the 6 steps in designing a X-S study
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step 1: specify research question
step 2: specify target and accessible (research) population step 3: draw samples step 4: measure predictor and outcome variables step 5: analysis: prevalence (absolute or relative) step 6: draw appropriate conclusions |
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what are the 6 steps in designing a cohort study design
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step 1: specify research question
step 2: assemble suitable cohort step 3: measure predictor variables step 4: follow cohort and measure outcomes step 5: analysis: incidence, relative risks (within, across cohort(s)) step 6: draw appropriate conclusions |
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strengths of cohort study design
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-good for quantifying incidence and investigating potential causes of a condition
-good for studying rare exposures and/or multiple outcomes -times-sequence is clearly established -if prospective: maximum control over measurement, historical data problems (recall bias, time-sequence issues, missing data) minimized |
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disadvantages of cohort studies
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-selection of subjects may not represent your population
-LTFU -subjects may change status over time -surveillance bias -often require large sample sizes (especially if studying rare or fatal outcomes) -association found in cohorts may be due to confounding -prospective ones are costly and time consuming -retrospectively done ones contain historical problems, and time-sequencing questions |
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how do you minimize LTFU
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-make repeated contacts with subjects
-trying to track down lost subjects -reporting LTFU rate and assessing impact on results |
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when do you use a cohort study design
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-best design for accurately describing incidence and natural history of condition
-often only way to establish time sequence -only way to study some fatal diseases (survivor bias enters into X-S study) -multiple, even previously unseen or unknown outcomes can be studied (if pro design) |
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probability sampling types (4)
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-simple random-table of random numbers
-systematic- every nth person -stratified-devide list into groups (by race, gender, age) then draw random samples from each stratum -cluster- random sampling of population groupings, then within groupings (random sampling of counties, then RPH's within the counties |
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non-probability sampling types (3)
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-consecutive sampling- all eligible subjects over a period of time
-convenience sampling- most easily available members of research population -judgemental sampling- hand-picking from research population those subjects deemed most appropriate for the study |
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which sampling method is best
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-depends on research question, goals, resources
-consecutive sampling OK in clinical research (if not feasible-draw a random sample of subjects from a consecutive series, or use another method -when possible preferable to use probability sampling methods |