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Clinical Epidemiology & Evidence-Based Medicine Glossary

Updated November 02, 2010

Contents:

Introductory Section:

General Terms for Epidemiology & Evidence-based Medicine

General Science Terminology:         (35K)

Terminology Specific to Epidemiology:        (18K)

Clinical Testing          (19K)

Clinical Study Design and Methods Terminology         (29K)

Experimental Design and Statistical Terms          (30K)


Introduction and Usage:

This following words, synonyms, common abbreviations, and complete definitions are for concepts useful to epidemiology, particularly clinical epidemiology and evidence-based medicine. Some differ from common usage, causing confusion. Applying basic clinical epidemiology and evidence-based medicine skills requires understanding these terms within the context of individual patient clinical care. The list the terms is classified into groups according to their usage context and related words rather than being listed alphabetically.

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General Terms for Epidemiology & Evidence-based Medicine:

  1. Critical Appraisal: The concepts and methods of critical thinking used to answer the key question "How good (strong) is the evidence for that?" when evaluating evidence for use in the practice of clinical medicine, whether the evidence is from clinical observations, laboratory results, scientific literature, or other sources (after answering the question "What is the evidence for that?").
  2. Critical Thinking: The disciplined ability and willingness to assess evidence and claims, to seek a breadth of contradicting as well as confirming information, to make objective judgments on the basis of well supported reasons as a guide to belief and action, and to monitor one’s thinking while doing so (metacognition). The thinking process that is appropriate for critical thinking depends on the knowledge domain (e.g.: scientific, mathematical, historical, anthropological, economic, philosophical, moral) but the universal criteria are: clarity, accuracy, precision, consistency, relevance, sound empirical evidence, good reasons, depth, breadth and fairness.
  3. Metacognition: Thinking about one's thinking; the monitoring of one’s thinking for the critical thinking criteria as one is acquiring and assessing new information. For scientific thinking, this means also becoming aware of one’s background knowledge, assumptions, and the auxiliary hypotheses (how observing works) and assessing their validity as well.
  1. Epidemiology: "Epi" - upon, "demos" - the people, "logos" - study of. The logical, systematic approach to understanding the complexities of disease (Torrence, 1997). The logic of observation and the methods to quantify these observations in populations (groups) of individuals. Epidemiology is the study of the distribution of health-related states or events in specified populations and the application of this study to the control of health problems (CDC). Epidemiology includes 1) the methods for measuring the health of groups and for determining the attributes and exposures that influence health; 2) the study of the occurrence of disease in its natural habitat rather than the controlled environment of the laboratory; and 3) the methods for the quantitative study of the distribution, variation, and determinants of health-related outcomes in specific groups (populations) of individuals, and the application of this study to the diagnosis, treatment, and prevention of these states or events. (Last, 1995)
    1. Descriptive (Observational) Epidemiology: The most basic form of epidemiology, which is the description of the patterns of occurrence of health-related states or events in groups; answering the questions of "Who?", "What?" "Where?", and "When?". Descriptive epidemiology is usually one of the first things done at the scene of any disease outbreak.
    2. Analytical Epidemiology: The design, execution and analysis of studies in groups to evaluate potential associations between risk factors and health outcomes to answer the question "Why?".
    3. Clinical Epidemiology: The application of the logical and quantitative concepts and methods of epidemiology to problems (diagnostic, prognostic, therapeutic, and preventive) encountered in the clinical delivery of care to individual patients. The population aspect of epidemiology is present because these individual patients are members of conceptual populations. "A basic science for clinical medicine" (Sackett et al.).
    4. Infectious Disease Epidemiology: Classical epidemiology; the study of epidemics; the study of the dynamic factors involved in the transmission of infectious agents in populations. Some include the products of the application of the methods of this discipline, the natural history of disease (information about how each disease spreads through groups and how a case of that disease develops in an individual).
  2. Belief: The mental act or state of mind of an individual after they accept and internalize an external concept or idea, which then becomes part of further thought processes, often unrecognized, on related issues. Internalized deeply, belief becomes part of intuition. Belief can occur after deliberate, systematic, critical thinking or can occur with immediate, non-reasoned, uncritical acceptance. Once a belief is accepted that is in error, accepting a more correct belief becomes considerably more difficult than if no previous belief were held. The nature of human thinking is to weigh data that is consistent with the mistaken belief heavier and to ignore or discount discordant data, and to limit the search for additional data to that which has the potential of confirming rather than refuting a belief (e.g. selective necropsy to confirm a gross diagnosis). Prior belief biases subjective observation, such as occurs during the diagnostic process or during non-blinded measurement, because it subtly changes perception, particularly of vague or ambiguous characteristics. This bias occurs unbeknownst to the observer and despite their best intentions.
  3. Dogma: Those beliefs held as established or put forth as an authoritative or expert opinion, often contained in a secondary or tertiary source, but that have little or no supportive empirical evidence from primary sources. Medical dogma is usually derived from unevaluated biological hypotheses and uncritical observation or experience without recognition of the effects of chance, natural biological variation, and observer bias. An unknown but significant portion of medical practice falls into this category. Repetition across secondary and tertiary sources or the number of people, whatever their qualifications, that hold this belief does not change the status of such information.
  4. Evidence: That which tends to support something or show that something is the case. Depending on how it was obtained, evidence varies greatly in strength. Note that a set of evidence can be correct but the underlying theory that the promoters allege the evidence supports can still be wrong.
    1. Empirical Evidence (Facts): Knowledge obtained by looking rather than reasoning or feeling. In the scientific sense, that knowledge comprised of the objective findings (but not broad interpretation) derived from analysis of objective data obtained from formal observational or experimental procedures that are potentially repeatable (verifiable) and that meet currently accepted standards of design, execution, and analysis. The strongest empirical evidence is obtained from rigorous methods incorporated into an experiment designed to have a clear, unequivocal supporting or refuting outcome. Empirical evidence is weakened by the opportunity for other explanations, due to weakness in methods, to account for the findings. As the opportunity for independent verification and for assessment of strength of evidence is a key component, the methods used to acquire the evidence must be described or referenced sufficiently that this verification and assessment can be done by independent investigators. As presented even in the refereed primary scientific journals, this evidence must be critically appraised by the reader because, depending on the methods used, it varies from strong and useful to weak, wrong, or irrelevant. Note that a set of evidence can be correct (e.g., the sun "rises" regularly) but the underlying theory that the promoters allege the evidence supports is wrong (e.g., the sun moves around the earth).
    2. Analogical Evidence: Evidence based on reasoning by analogy, which is concluding from comparing known similarities between two systems that a relationship shown to exist in one system but unknown in the other also exists in the other. For example, if drug X has been shown to be effective against disease Y in a species Z then perhaps the same relationship exists between similar drug or similar disease or similar species. Evidence based on analogical reasoning is common in medicine, as it is a necessary basis for action when empirical evidence is lacking. Detailed mechanisms of action for particular processes are often established in laboratory species (rodents) and extrapolated to other species in which direct investigation is impractical. However, analogical evidence is susceptible to unavoidable error because of the likelihood that different and unknown factors are operating in the two systems, which weaken the analogy. Because it is inherently a weaker form of evidence than is empirical evidence, it is likely the source of much unexamined dogma and is better used as a basis for generating hypotheses that are then empirically evaluated.
    3. Anecdotal Evidence (Case report): The description of the occurrence of single unique event, such as a miraculous medical recovery. Even if the occurrence of the event itself is without doubt, the reason that it occurred is often promoted as being due to an unusual therapy applied to the case and thus validating the theory that selection of the therapy was based upon. The probability of apparently unusual events is often considerably higher than we expect by intuition and other unrecognized factors (confounders) may have invalidated the initial prediction of demise, thus making the event not that unusual. As an anecdote is extremely weak evidence in support of a theory, an accumulation of similar anecdotes does not significantly increase support and at best may serve as a justification for a scientific experiment to empirically test the theory.
  5. Evidence-based (population-based) medicine (EBM): "An approach to practice in which the clinician is aware of the evidence in support of their clinical practice and the strength of that evidence" (McMaster). EBM is the use of: systematic observation of the clinical patient and the rules for empirical evidence to critically appraise and interpret information from clinical research (causation, prognosis, diagnostic tests, and treatment strategies) to apply to that individual patient. The goal of EBM is to increase the likelihood of a better clinical outcome for an individual patient because of making better clinical decisions and doing so in a more efficient, cost-effective manner. EBM goes beyond the traditional focus on reasoning based on microbiology, pathophysiology, and pharmacology, beyond the traditional reliance on authority or expert opinion (dogma) and beyond the traditional use of uncritically and unsystematically evaluated clinical experience (JAMA 268:2420-2425 (1992), BMJ 310:1122-1126 (1995), J Royal Soc Med 88:620-624(1995)).
  1. Population: An aggregation or group of individuals defined by a set of common characteristics.
    1. Physical Population: All individuals residing in a defined area, the common definition of population.
    2. Conceptual Population: A population defined by a set of common characteristics other than location of residence (e.g., common set of presenting clinical signs, common intrinsic attributes (age, breed, sex, ...), practice clientele, ...). Understanding this notion of population is crucial to understanding the logic of inferring from the results of a published study to what should be done to an individual patient in the clinical setting.
      1. When considering the generalizability (external validity) of a clinical study (such as a drug trial), the conceptual population is that group of patients to which the study results apply and is based on the relevant characteristics of the actual population of patients in which the study was done. The question the clinician must answer is whether the patient at hand is likely a member of that population (study results may apply) or not (study results do not apply).
      2. When considering the diagnostic performance of tests, two conceptual populations are of concern to the clinician: 1) that conceptual population representing those patients with the event (a given disease, risk factor or health outcome) being tested for that are typically seen by the clinician and 2) that population of patients without this event that are likely to be confused with the first population at some point in the diagnostic process (e.g. similar clinical signs) and that the clinician must distinguish from the first by using the test.
      3. When considering statistics from samples, the conceptual population is those individuals that were eligible for sampling and from which the sample was taken. The sample statistics are the estimates of the parameters characterizing this population (e.g., mean, standard deviation, standard error of the mean, ...).

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