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Center for Health Sciences
Medical Physiology - Evidence-Based Medicine
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What is EBM?

Patient Care Model
Life-long Learning
Why is EBM Important?
Available Evidence?
EBM Issues

The Well-built Question

The EBM Process
Anatomy of a Question

Finding Evidence

Selecting a Resource
Searching the Resource
Reviewing Search Results
Returning to the Patient

Evaluating Evidence

Evaluating the Validity
Validity Questions


Knowledge Test

Multiple Sclerosis
Case #2
Case #3
Case #4





Absolute Risk Difference is the arithmetic difference between the rates of events in the intervention and control group.

Absolute Risk Reduction refers to the decrease of a bad event as a result of the intervention.

Absolute Benefit Increase refers to the increase of a good event as the result of the intervention.

Confidence Intervals are calculated on the results of the data to show the strength or weakness of the evidence. A 95%CI[range] means that if you were to repeat the same clinical trial a hundred times you can be 95% sure that the data would fall within the calculated range.

Intention to treat analysis of patients with the treatment group to which they were originally assigned, regardless of whether or not they actually received the treatment or not.

Likelihood Ratio indicates the likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without that disorder.

Numbers Needed to Treat (NNT) the number of patients who need to be treated to prevent one bad outcome. The NNT is a useful number when you want to compare the costs and adverse effects of a treatment with its benefits.

Odds Ratio describes the odds of an experimental patient suffering an adverse event relative to a control patient.

P Value refers to the probability that any particular outcome would have arisen by chance. (The smaller the P value the less likely the data was by chance.) Standard scientific practice, usually deems a P value of less than 1 in 20 (expressed as P=.05) as "statistically significant". The smaller the P value the higher the significance. A P value of P=.01 ( less than 1 in 100) is considered "statistically highly significant".

Predictive Value of tests: In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the positive Predictive Value; whereas, the Negative Predictive Value is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.

Relative Risk is the risk of developing a disease in the exposed group divided by the risk of developing the disease in the unexposed group.

Relative Risk Reduction is the proportional difference between the rates of events in the control group and the intervention group. Relative Risk Reduction is usually a larger number than the Absolute Risk Difference and therefore tends to exaggerate the difference.

Sensitivity measures the proportion of patients with the disease who also test positive for the disease.

Specificity measures the proportion of patients without the disease who also test negative for the disease.

A good test is both highly sensitive and highly specific.

See also the Glossary of Terms from Evidence Based Emergency Medicine and the New York Academy of Medicine

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