In an effort to facilitate more accurate disposition decisions and thereby reduce mounting health care costs, several investigators have developed computerized decision aids or computer-based triage protocols for ED patients with chest pain. One well-known computer-derived decision aid, developed by Goldman et al., applied recursive partitioning to clinical and ECG data to derive and prospectively validate an algorithm that could stratify ED patients into groups at variable risk of infarction (Fig. 45-1).l° Although hypothetical testing predicted improved specificity of coronary care unit (CCU) triage decisions, a prospective study did not result in a significant decrease in the rates of CCU admission from the ED. Other methods, such as multivariate analysis and artificial neural networks, have also been used to develop predictive instruments for the detection of acute ischemic heart disease. In a large multicenter prospective trial (as yet unpublished), one of these decision aids, the time-insensitive predictive instrument (TIPI), was shown to decrease CCU admissions by 26 percent and increase ED discharges to home by 48 percent, but this approach has not yet been validated.
FIG. 45-1. Goldman algorithm. (An abridged version. Modified from Ref. 10)
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