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Dictionary of Evidence-based Medicine.pdf

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82 <strong>Dictionary</strong> <strong>of</strong> <strong>Evidence</strong>-<strong>based</strong> <strong>Medicine</strong><br />

Impact lag<br />

The impact lag refers to the time it takes for the effects <strong>of</strong> a policy change<br />

to be felt. In monetary policy the impact lag may be close to a year and in<br />

fiscal policy, wide variability in impact lag has been observed (see Implementation<br />

lag and Recognition lag).<br />

Implementation lag<br />

The implementation lag refers to the time delay between identification <strong>of</strong><br />

the need to institute a policy change and its actual implementation. In<br />

health care, for example, the need to change treatment protocol <strong>based</strong> on<br />

high-quality clinical trial evidence (e.g. use <strong>of</strong> thrombolysis in the management<br />

<strong>of</strong> post-myocardial patients) may be followed by guideline development<br />

and then adoption by prescribers, a sequence which is associated<br />

with well-known and reported implementation lags (European Secondary<br />

Prevention Study Group (1996) Translation <strong>of</strong> clinical trials into practice:<br />

a European population-<strong>based</strong> study <strong>of</strong> the use <strong>of</strong> thrombolysis for acute<br />

myocardial infarction. Lancet. 347:1203-7). (See also Impact lag and Recognition<br />

lag).<br />

Inception cohort<br />

In studies designed to investigate prognosis, a group <strong>of</strong> patients at a<br />

common point in the course <strong>of</strong> the disease under investigation is recruited.<br />

Clearly, the earlier the recruitment in the course <strong>of</strong> the disease, the easier it<br />

is to be comprehensive about the prognostic factors. A group <strong>of</strong> patients<br />

recruited as soon as the disease becomes clinically identifiable is referred<br />

to as an inception cohort.<br />

Incidence<br />

The incidence <strong>of</strong> an event (e.g. disease or adverse reaction) refers to the<br />

frequency <strong>of</strong> new cases in the population at risk during a specified time<br />

interval. The prevalence, on the other hand, refers to the frequency <strong>of</strong> all<br />

current cases in the population at risk at a specific time (point prevalence)<br />

or time interval (period prevalence). Mathematically, the prevalence (P) is<br />

approximately equal to the incidence (/) multiplied by the duration (T) <strong>of</strong><br />

the disease (P = I x T). Figure 11 illustrates which cases are included when<br />

calculating incidence and prevalence.

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