Improving patient flow in acute coronary syndromes in the face of hospital crowding.
BACKGROUND
The current paradigm for the evaluation of patients with suspected acute coronary syndromes (ACS) in the emergency department (ED) is focused on the identification of patients with active underlying coronary disease. The majority of patients evaluated in the ED setting do not have active underlying cardiac disease.


OBJECTIVE
To measure the effect of bedside point-of-care (POC) cardiac biomarker testing on telemetry unit admissions from the ED. Furthermore, to evaluate the effect telemetry admissions have on ED length of stay (LOS) and overall hospital LOS.


METHODS
Primary data were collected over two 6-month periods in an urban teaching hospital ED. This was an observational cohort study conducted pre- and post-availability of a POC testing platform for cardiac biomarkers. Major measures included number of overall telemetry admissions, ED LOS, hospital LOS, and disposition. Patients were followed at 30 days for significant cardiac events, repeat ED visit or admission, and death.


RESULTS
In the post-implementation period there was a 30% (95% confidence interval [CI] 36-44%) reduction in admissions to telemetry with a 33% (95% CI 26-39%) reduction in ED LOS and a 20% (95% CI 7-34%) reduction in hospital LOS. There was a 62% reduction in overall mortality between the pre-implementation period and the post-implementation period (p=0.001).


CONCLUSIONS
The focused use of a rapid cardiac disposition protocol can dramatically impact resource utilization, expedite patient flow, and improve short-term outcomes for patients with suspected ACS.
Department of Medicine, Weill Cornell Medical College, New York, New York, USA.
Robert H
RH
Birkhahn
Wendy
W
Wen
Paris A
PA
Datillo
William M
WM
Briggs
Amisha
A
Parekh
Alp
A
Arkun
Bethany
B
Byrd
Theodore J
TJ
Gaeta
D054058:Acute Coronary Syndrome / Q000097:blood* / Q000175:diagnosis / Q000401:mortality; D000368:Aged; D015415:Biomarkers / Q000097:blood; D052279:Creatine Kinase, MB Form / Q000097:blood; D019091:Critical Pathways / Q000458:organization & administration; D003441:Crowding; D017598:Efficiency, Organizational; D004636:Emergency Service, Hospital / Q000458:organization & administration* / Q000706:statistics & numerical data; D005260:Female; D006295:Health Resources / Q000706:statistics & numerical data; D006760:Hospitalization / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009211:Myoglobin / Q000097:blood; D010343:Patient Admission / Q000706:statistics & numerical data; D019095:Point-of-Care Systems; D011237:Predictive Value of Tests; D013686:Telemetry / Q000706:statistics & numerical data; D019210:Troponin I / Q000097:blood; D019037:Urban Health Services / Q000706:statistics & numerical data
D015415:Biomarkers; D009211:Myoglobin; D019210:Troponin I; D052279:Creatine Kinase, MB Form