This glossary seeks to define and explain some of the concepts used in Evidence-Based Medicine and Information Mastery. Entries were adapted from a number of sources and sometimes lean toward treatment definitions as opposed to, for example, those used in epidemiology.
ARR (Absolute Risk Reduction): The arithmetic difference between the outcome rates of the control group (CER) and the outcomes rates of the experimental group when the experimental intervention prevents harm occurring to more patients than the control intervention: CER – EER.
CER: Control event rate.
Clinical Jazz: a mixture made by harmonizing the best available evidence with the clinical experience needed to understand what each individual patient needs.
Clinical Significance: The benefit to people receiving an intervention (i.e., whether the intervention makes a real difference—symptoms improve, mortality rates decrease, etc.—in the everyday life of the patient) compared to the control group, being great enough to warrant the intervention. This is “significance” in the informal sense vs. the statistical sense. For example, if 5000 personas are enrolled in a trial to assess the benefit of a medication for the common cold and 3% of those receiving the drug reduce the duration of symptoms by 12 hours, the results are statistically significant, but few people will find the results clinically significant.
Confidence Interval (CI): The range around a study's result within which we would expect the true value to lie. CIs account for the sampling error between the study population and the wider population the study is supposed to represent.
DOE (Disease-oriented Evidence): Study outcome information aimed at increasing understanding of a disease process—etiology, prevalence, pathophysiology, prognosis, etc. They are usually laboratory/test centered (e.g., blood glucose levels).
EER: Experimental event rate.
Filtered Resources: Resources that appraise the quality of studies and often make recommendations for practice. Examples include systematic reviews/meta analyses, critically appraised topics, critically appraised individual articles.
Foraging Tool: a tool that alerts you to new information that is well-validated and relevant to your practice. Foraging, as opposed to hunting, is browsing/scanning for information to stay up-to-date, without a particular patient question in mind.
Hunting Ttool: a searching tool for finding information (or finding it again) quickly and effectively when you need it, usually to answer clinical questions.
LOE (Level of Evidence): a hierarchy based on the belief that some research designs provide a stronger level of evidence than others based on their inherent characteristics and ability to protect against bias. There is no one universally accepted hierarchy, but randomized controlled trials (RCTs) or systematic reviews and meta-analyses of randomized controlled trials are considered to be the highest level. The hierarchy is often depicted using a pyramid.
NNH (Number Needed to Harm): The number of patients undergoing a particular intervention for one additional adverse outcome compared to patients who receive the control treatment.
NNT (Number Needed to Treat): The number of patients who need to undergo a particular intervention in order to benefit (or to prevent one additional bad outcome such as a stroke) compared to patients in the control group.
Both are calculated in the same way using numbers of positive and negative events in groups respectively.
NNT or NNH = 1/AAR with AAR being the Absolute Risk Reduction.
Odds Ratio: Used to assess the risk of a particular outcome (or disease) if a certain factor (or exposure) is present (variable group). The odds ratio is a relative measure of risk, i.e., how much more likely it is that someone who is exposed to the factor under study will develop the outcome as compared to someone who is not exposed (control group). The ratio of the probability of something occurring to two different groups. The formula is
(a/b) / (c/d)
Where a is the number of people in the variable group who experience the outcome,
b is the number of people in the control group who experience the outcome
c is the number of people in the variable group who experience no outcome
d is the number of people in the control group who experience no outcome
P Value: A statistical value that measures the probability that the difference between groups occurred by chance alone. For example, a P value of 0.05 (or 1 chance in every 20 tries) indicates that there is only a 5% probability that the results observed between treatments in the sample happened by chance. The P value is the key defining point of clinical trials, its value determining whether one treatment can be considered to have a statistically significant advantage over another. In general, clinical trials are powered to show statistical significance between treatments when 1 treatment shows a P value of 0.05 or less. P=values provide a cut-off beyond which we can assert that the findings are “statistically significant” (by convention, this is p<0.05).
POEM (Patient-Oriented evidence that Matters): POEMs information that addresses a clinical problem or clinical question that a practitioner encounters often in his/her practice (i.e., has the porential to change clinical practice) and that has outcomes that helps patient live longer and better (i.e., lengthens life, decreases symptoms, and/or improves quality of life).
Relative Risk Ratio: A measure of the strength of association between a risk factor and the outcome of interest, often a disease. It is calculated as the ratio of incidence of the outcome in outcomes in those exposed to the risk factor, compared to the incidence of disease in those not exposed to the risk factor. A ratio greater than one suggests increased risk, less than one a protective effect, and a ratio of one no additional risk. Relative Risk Ratio is the ratio of two risks: the risk of the event in one group divided by the risk of the event in the other group
Where a is the number of people in the risk exposure group who experience the outcome
b is the number of people in the risk exposure group who do not experience the outcome
c is the number of people in the control group who experience the outcome
d is the number of people in the control group who do not experience the outcome
Relative Risk Reduction: The percentage reduction in events in the treated group event rate (EER) compared to the control group event rate (CER); the proportion of adverse events that would have occurred in the treated group that are avoided by the intervention. The formula is
RRR = (CER - EER) / CER
Relevance: Focuses on what should be the ultimate destination--finding information on how to help
patients live long, functional, satisfying, pain- and symptom-free lives. Relevant information is applicable to one’s practice and is also focused on patient-oriented evidence that matters.
Sensitivity: The proportion of people with a target condition who have a positive test/sign/symptom.
Specificity: The proportion of people with a target condition who have a negative test/sign/symptom.
Statistical Significance: Measures how likely that any apparent differences in outcome between treatment and control groups are real and not due to chance. Statistical significance isn’t about therapies/interventions. It is a description of the data and its variance—compared compared to some benchmark, what is the probability that the data being looked at is just a chance variation on the benchmark?
p Values and confidence intervals (CI) are the most commonly used measures of statistical significance. The p values give the probability that any particular outcome would have arisen by chance with the assumption that the new and the control treatments are equally effective as the null hypothesis. CI estimate the range within which the real results would fall if the trial is conducted many times.
STEPS: An approach to making drug therapy decisions developed by Sheldon Preskorn. The STEPs mnemonic stands for safety, tolerability, effectiveness, price, and simplicity.
Safety - major events including death or severe life-threatening complications that can occur with drugs
Tolerability - bothersome side effects – nausea, drowsiness, etc.
Effectiveness -- effect of the therapy on patient-oriented outcomes
Price – not just the comparison of the cost of two drugs, but the total cost of managing the disease
Simplicity - comparing things such as once-a-day versus three times a day dosing, or a liquid that tastes good and kids will actually take it
Usefulness Equation: A formula developed by David Slawson and Allen Shaughnessy which describe a relationship between three characteristics of information. To be useful, information should be relevant to everyday practice, valid (correct) and not much work (easy to obtain).
Usefulness = Relevance x Validity
Validity: The extent to which a variable or intervention measures represents the “truth”; that is, measures what it is supposed to measure or accomplishes what it is supposed to accomplish. The internal validity of a study refers to the integrity of the experimental design. The external validity of a study refers to the appropriateness by which its results can be applied to non-study patients or populations.
Work: The negative attribute one must consider when evaluating the usefulness of information. It is the time, energy, and money required to find needed information.
YODA (Your Own Data Analyzer): The best expert in your community. A mentor / Someone who can take the best information available, analyze it to determine whether it is valid, and interpret it within the context of clinical practice.
These tools will help you to interpret the clinical and statistical significance of data reported in clinical research. They should be used as a guide only and should NOT be the sole basis for decision making.