Evidence-based medicine (EBM) Glossary

Evidence-based medicine (EBM)

The conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients. The practice of evidence-based medicine requires the integration of individual clinical expertise with the best available external clinical evidence from systematic research and our patient’s unique values and circumstances.

Evidence-based health care

Extends the application of the principles of evidence-based medicine (see below) to all professions associated with health care, including purchasing and management.

Cost-benefit analysis

Assesses whether the cost of an intervention is worth the benefit by measuring both in the same units; monetary units are usually used.

Cost-effectiveness analysis

Measures the net cost of providing an intervention as well as the outcomes obtained. Outcomes are reported in a single unit of measurement.

Cost-minimization analysis

If health effects are known to be equal, only costs are analyzed and the least costly alternative is chosen.

Cost-utility analysis

Converts health effects into personal preferences (or utilities) and describes how much it costs for some additional quality gain (e.g. cost per additional quality-adjusted life-year, or QALY).

Treatment effects

The evidence-based journals (Evidence Based Medicine and ACP Journal Club) have achieved consensus on some terms they use to describe both the good and bad effects of therapy. We will bring them to life with a synthesis of three randomized trials in diabetes which individually showed that several years of intensive insulin therapy reduced the proportion of patients with worsening retinopathy to 13% from 38%, raised the proportion of patients with satisfactory hemoglobin A1c levels to 60% from about 30%, and increased the proportion of patients with at least one episode of symptomatic hypoglycemia to 57% from 23%. Note that in each case the first number constitutes the “experimental event rate” (EER) and the second number the “control event rate” (CER).

We will use the following terms and calculations to describe these effects of treatment: When the experimental treatment reduces the probability of a bad outcome (worsening diabetic retinopathy)

RRR (relative risk reduction). The proportional reduction in rates of bad outcomes between experimental and control participants in a trial, calculated as |EER – CER|/CER, and accompanied by a 95% confidence interval (CI). In the case of worsening diabetic retinopathy, |EER – CER|/CER = |13% – 38%|/38% = 66%.

ARR (absolute risk reduction). The absolute arithmetic difference in rates of bad outcomes between experimental and control participants in a trial, calculated as |EER – CER|, and accompanied by a 95% CI. In this case, |EER – CER| =|13% – 38%| = 25%. (This is sometimes called the risk difference)

NNT (number needed to treat). The number of patients who need to be treated to achieve one additional favorable outcome, calculated as 1/ARR and accompanied by a 95% CI. In this case, 1/ARR = 1/25% = 4.

When the experimental treatment increases the probability of a good outcome (satisfactory hemoglobin A1c levels):

RBI (relative benefit increase). The proportional increase in rates of good outcomes between experimental and control patients in a trial, calculated as |EER – CER|/CER, and accompanied by a 95% confidence interval (CI). In the case of satisfactory hemoglobin A1c levels, |EER – CER|/CER =|60% – 30%|/30% = 100%.

ABI (absolute benefit increase). The absolute arithmetic difference in rates of good outcomes between experimental and control patients in a trial, calculated as |EER – CER|, and accompanied by a 95% confidence interval (CI). In the case of satisfactory hemoglobin A1c levels, |EER – CER| = |60% – 30%| =30%

NNT (number needed to treat). The number of patients who need to be treated to achieve one additional good outcome, calculated as 1/ARR and accompanied by a 95% CI. In this case, 1/ARR = 1/30% = 3.

When the experimental treatment increase the probability of a bad outcome (episodes of hypoglycemia):

RRI (relative risk increase). The proportional increase in rates of bad outcomes between experimental and control patients in a trial, calculated as |EER – CER|/CER, and accompanied by a 95% confidence interval (CI). In the case of hypoglycemic episodes, |EER – CER|/CER = |57% – 23%|/23% = 148%. (RRI is also used in assessing the impact of “risk factors” for disease.)

ARI (absolute risk increase). The absolute arithmetic difference in rates of bad outcomes between experimental and control patients in a trial, calculated as |EER – CER|, and accompanied by a 95% confidence interval (CI). In the case of hypoglycemic episodes, |EER – CER| = |57% – 23%| = 34%. (ARI is also used in assessing the impact of “risk factors” for disease.)

NNH (number needed to harm). The number of patients who, if they received the experimental treatment, would result in one additional patient being harmed, compared with patients who received the control treatment, calculated as 1/ARI and accompanied by a 95% CI.
In this case, 1/ARI = 1/34% = 3.

For additional EBM terms go to:
http://www.cebm.utoronto.ca/glossary/index.htm#m

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