Proposal to Design a Chest Pain Assessment Unit
Carey Sim
Athabasca University
, CHEST PAIN ASSESSMENT UNIT
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Proposal to Design a Chest Pain Assessment Unit
Chest pain is one of the most common reasons for emergency department (ED) visits in
developed countries (Ko et al., 2018). In the United States, the Center for Disease Control and
Prevention (CDC) reports that more than six million patients are evaluated with chest pain in
emergency departments each year. A significant number of these patients are considered low risk
for acute coronary syndrome (ACS) and present a great disposition challenge for emergency
room physicians (Ko et al., 2018). The recommend assessment for ACS, from the American
College of Cardiology and American Heart Association, is to obtain cardiac biomarkers and
electrocardiograms (ECGs) on all probable ACS patients. If results are negative, guidelines
recommend provocative cardiac testing before discharge or within seventy-two hours (Ko et al.,
2018). This, holding of patients, places a capacity burden on the ED or inpatient cardiology
units, with patients who are required to stay for investigations lasting between three to twenty-
four hours.
My proposal for dealing with short stay, low-risk ACS patients is the development of a
chest pain assessment unit (CPU). CPUs have been successfully developed and implemented in
many centers throughout the United States, and provide standardized care for patients who
present with acute non-traumatic chest pain, which remains undiagnosed after an initial
assessment, ECG and chest x-ray (CXR) (Vibhakar & Mattu, 2015). Sixty to sixty-five percent
of patients have an eventual diagnosis of non-cardiac chest pain, and our current traditional
method of chest pain diagnosis is time-consuming and expensive (Quin, 2000).
Why Admit to a Chest Pain Unit
As mentioned previously, chest pain is one of the most common reasons for ED visits
every year. To adequately determine if a patient with non-traumatic chest pain is safe for
discharge can take between three to twenty-four hours. Statistical evaluation of patients