title: Use of the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) to assist with triage of patients with chest pain or other symptoms suggestive of acute cardiac ischemia. A multicenter, controlled clinical trial.
abstract: BACKGROUND
  Approximately 6 million U.S. patients present to emergency departments annually with symptoms suggesting acute cardiac ischemia. Triage decisions for these patients are important but remain difficult.
  
  
  OBJECTIVE
  To test whether computerized prediction of the probability of acute ischemia, used with electrocardiography, improves the accuracy of triage decisions.
  
  
  METHODS
  Controlled clinical trial.
  
  
  METHODS
  10 hospital emergency departments in the midwestern, southeastern, and northeastern United States.
  
  
  METHODS
  10689 patients with chest pain or other symptoms suggestive of acute cardiac ischemia.
  
  
  METHODS
  The probability of acute ischemia predicted by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI), either automatically printed or not printed on patients' electrocardiograms.
  
  
  METHODS
  Emergency department triage to a coronary care unit (CCU), telemetry unit, ward, or home. Other measurements were the bed capacity of the CCU relative to that of the telemetry unit; training or supervision status of the triaging physician; and patient diagnoses and outcomes based on clinical, electrocardiographic, and creatine kinase data.
  
  
  RESULTS
  For patients without cardiac ischemia, in hospitals with high-capacity CCUs and relatively low-capacity cardiac telemetry units, use of ACI-TIPI was associated with a reduction in CCU admissions from 15% to 12%, a change of -16% (95% CI, -30% to 0%), and an increase in emergency department discharges to home from 49% to 52%, a change of 6% (CI, 0% to 14%; overall P=0.09). Across all hospitals, for patients evaluated by unsupervised residents, use of ACI-TIPI was associated with a reduction in CCU admissions from 14% to 10%, a change of -32% (CI, -55% to 3%); a reduction in telemetry unit admissions from 39% to 31%, a change of -20% (CI, -34% to -2%); and an increase in discharges to home from 45% to 56%, a change of 25% (CI, 8% to 45%; overall P=0.008). Among patients with stable angina, in hospitals with high-capacity CCUs, use of ACI-TIPI was associated with a reduction in CCU admissions from 26% to 13%, a change of -50% (CI, -70% to -17%), and an increase in discharges to home from 20% to 22%, a change of 10% (CI, -29% to 71%; overall P=0.02). At hospitals with high-capacity telemetry units, use of ACI-TIPI was associated with a reduction in telemetry unit admissions from 68% to 59%, a change of -14% (CI, -27% to 1%), and an increase in emergency department discharges to home from 10% to 21%, a change of 100% (CI, 22% to 230%; overall P=0.02). Among patients with acute myocardial infarction or unstable angina, use of ACI-TIPI did not change appropriate admission (96%) to the CCU or telemetry unit at hospitals with high-capacity CCUs or telemetry units.
  
  
  CONCLUSIONS
  Use of ACI-TIPI was associated with reduced hospitalization among emergency department patients without acute cardiac ischemia. This result varied as expected according to the CCU and cardiac telemetry unit capacities and physician supervision at individual hospitals. Appropriate admission for unstable angina or acute infarction was not affected. If ACI-TIPI is used widely in the United States, its potential incremental impact may be more than 200000 fewer unnecessary hospitalizations and more than 100000 fewer unnecessary CCU admissions.
authors.affiliation: New England Medical Center/Tufts University School of Medicine, Boston, Massachusetts 02111, USA.
authors.forename: H P
authors.initials: HP
authors.lastname: Selker
authors.forename: J R
authors.initials: JR
authors.lastname: Beshansky
authors.forename: J L
authors.initials: JL
authors.lastname: Griffith
authors.forename: T P
authors.initials: TP
authors.lastname: Aufderheide
authors.forename: D S
authors.initials: DS
authors.lastname: Ballin
authors.forename: S A
authors.initials: SA
authors.lastname: Bernard
authors.forename: S G
authors.initials: SG
authors.lastname: Crespo
authors.forename: J A
authors.initials: JA
authors.lastname: Feldman
authors.forename: S S
authors.initials: SS
authors.lastname: Fish
authors.forename: W B
authors.initials: WB
authors.lastname: Gibler
authors.forename: D A
authors.initials: DA
authors.lastname: Kiez
authors.forename: R A
authors.initials: RA
authors.lastname: McNutt
authors.forename: A W
authors.initials: AW
authors.lastname: Moulton
authors.forename: J P
authors.initials: JP
authors.lastname: Ornato
authors.forename: P J
authors.initials: PJ
authors.lastname: Podrid
authors.forename: J H
authors.initials: JH
authors.lastname: Pope
authors.forename: D N
authors.initials: DN
authors.lastname: Salem
authors.forename: M R
authors.initials: MR
authors.lastname: Sayre
authors.forename: R H
authors.initials: RH
authors.lastname: Woolard
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D002637:Chest Pain / Q000209:etiology*; D003325:Coronary Care Units / Q000706:statistics & numerical data; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D004562:Electrocardiography; D004636:Emergency Service, Hospital; D005260:Female; D006801:Humans; D007396:Internship and Residency; D008297:Male; D008875:Middle Aged; D017202:Myocardial Ischemia / Q000150:complications / Q000175:diagnosis*; D010343:Patient Admission / Q000706:statistics & numerical data; D011336:Probability; D016037:Single-Blind Method; D013686:Telemetry; D014218:Triage / Q000379:methods*