A predictive instrument for acute ischemic heart disease to improve coronary care unit admission practices: a potential on-line tool in a computerized electrocardiograph.
Each year, 1.5 million patients are admitted to coronary care units (CCUs) for suspected acute ischemic heart disease, but for half of these, the diagnosis is ultimately ruled out. In this study, conducted in the emergency rooms (ERs) of six New England hospitals, the authors sought to develop a diagnostic aid to help ER physicians reduce the numbers of CCU admissions for patients without true acute cardiac ischemia. In phase 1, from data on 2,801 patients, they developed a predictive instrument for use in a handheld programmable calculator, which, based on a mathematical logistic regression formula, computes a patient's probability of having acute cardiac ischemia. In phase 2, a 1-year prospective trial including 2,320 ER patients at the six hospitals, physicians' diagnostic specificity for acute ischemia increased when the probability value determined by the instrument was made available to them (p = 0.002), without a drop in sensitivity. Among patients without acute ischemia, the number of CCU admissions decreased 30% (p = 0.003), without an increase in missed diagnoses of ischemia. The proportion of patients in the CCU without acute ischemia dropped from 44% to 33%. If similar findings were widespread, the use of this predictive instrument could reduce the number of CCU admissions in the United States by more than 250,000 per year. As originally envisioned, the physician could use a pocket-sized programmable calculator to allow quick access to the instrument's probability value, or an ER triage nurse might compute the probability value and write it on the clinical record for the physician's use.(ABSTRACT TRUNCATED AT 250 WORDS)
Selker
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Multicenter Cardiology and Health Services Research Unit, New England Medical Center, Boston, MA 02111.
D'Agostino
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Laks
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D003325:Coronary Care Units; D003327:Coronary Disease / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015337:Multicenter Studies as Topic; D009862:Online Systems; D010343:Patient Admission; D011446:Prospective Studies; D012984:Software