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A predictive instrument for acute ischemic heart disease to improve coronary care unit admission practices: a
H P Selker1, R B D'Agostino, M M Laks
1Multicenter Cardiology and Health Services Research Unit, New England Medical Center, Boston, MA 02111.
Insights
A new diagnostic tool helps emergency room physicians accurately identify acute cardiac ischemia. This reduces unnecessary coronary care unit admissions by 30%, improving patient care and resource allocation.
Area of Science:
- Cardiology
- Emergency Medicine
- Medical Informatics
Background:
- Annually, 1.5 million patients are admitted to coronary care units (CCUs) with suspected acute ischemic heart disease.
- Half of these admissions are ultimately diagnosed as not having acute cardiac ischemia, indicating a need for improved diagnostic accuracy in emergency settings.
Purpose of the Study:
- To develop and validate a predictive instrument for emergency room (ER) physicians to aid in the diagnosis of acute cardiac ischemia.
- To reduce unnecessary CCU admissions for patients without confirmed acute cardiac ischemia.
Main Methods:
- Phase 1: Developed a predictive instrument using logistic regression on data from 2,801 ER patients.
- Phase 2: Conducted a 1-year prospective trial with 2,320 ER patients, assessing physician diagnostic accuracy with and without the instrument's probability value.
Main Results:
- Physician diagnostic specificity for acute ischemia increased significantly (p = 0.002) when using the predictive instrument, without compromising sensitivity.
- CCU admissions for patients without acute ischemia decreased by 30% (p = 0.003), with no increase in missed diagnoses.
- The proportion of CCU patients without acute ischemia dropped from 44% to 33%.
Conclusions:
- The developed predictive instrument effectively enhances diagnostic accuracy for acute cardiac ischemia in the ER setting.
- Widespread implementation could potentially decrease annual CCU admissions in the US by over 250,000.
- The instrument, usable via a handheld calculator or by triage nurses, offers a practical solution for optimizing CCU utilization.
Abstract:
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)