Abstract
This study aimed at evaluating four existing models, comprising he Zarich’s model [1], the flowchart model [2, 3], and the Heart Broken Index (HBI) model [4], for triaging potential acute coronary syndrome (ACS) patients who presented at the emergency department. The 793 clinical cases, randomly selected from 7,962 clinical cases that applied the HBI in the ED of the Far Eastern Memorial Hospital in Taiwan, were used for the model testing. The results showed that although the chest-pain and HBI models had high sensitivity (both 99.24%), they had very low specificity (3.93% and 4.08%), whereas the Zarch’s and flowchart models had relatively higher specificity (14.98% and 17.25%), but they had lower sensitivity (96.97% and 93.18%). To increase specificity and maintain high sensitivity while triaging suspected ACS patients, future research can focus on using systematic methods to develop more effective ACS triage models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zarich SW, Sachdeva R, Fishman R, Werdmann MJ, Parniawski M, Bernstein L, Dilella M (2004) Effectiveness of a multidisciplinary quality improvement initiative in reducing door-to-balloon times in primary angioplasty. J Interv Cardiol 17(4):191–195
Sánchez M, López B, Bragulat E, Gómez-Angelats E, Jiménez S, Ortega M, Coll-Vinent B, Alonso JR, Queralt C, Miró Ò (2007) Triage flowchart to rule out acute coronary syndrome. Am J Emerg Med 25(8):865–872
López B, Sánchez M, Bragulat E, Jiménez S, Coll-Vinent B, Ortega M, Gómez-Angelats E, Miró Ò (2010) Validation of a triage flowchart to rule out acute coronary syndrome. Emerg Med J 28:841–846
Hsu J-C, Chen K-C, Cheng I-N, Li A-H (2011) Using heart broken index to improve the diagnostic accuracy of patient with STEMI and shorten door-to-balloon time on emergency department. Paper presented at the American Heart Association 2011 Scientific Sessions, Orlando, Florida
Wright RS, Anderson JL, Adams CD, Bridges CR, Casey DE, Ettinger SM, Fesmire FM, Ganiats TG, Jneid H, Lincoff AM (2011) 2011 ACCF/AHA focused update incorporated into the ACC/AHA 2007 guidelines for the management of patients with unstable angina/non–ST-elevation myocardial infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol 57(19):e215–e367
Hess EP, Brison RJ, Perry JJ, Calder LA, Thiruganasambandamoorthy V, Agarwal D, Sadosty AT, Silvilotti MLA, Jaffe AS, Montori VM (2012) Development of a clinical prediction rule for 30-day cardiac events in emergency department patients with chest pain and possible acute coronary syndrome. Ann Emerg Med 59(2):115–125
Pope JH, Aufderheide TP, Ruthazer R, Woolard RH, Feldman JA, Beshansky JR, Griffith JL, Selker HP (2000) Missed diagnoses of acute cardiac ischemia in the emergency department. N Engl J Med 342(16):1163–1170
Rosenfeld AG, Knight EP, Steffen A, Burke L, Daya M, DeVon HA (2015) Symptom clusters in patients presenting to the emergency department with possible acute coronary syndrome differ by sex, age, and discharge diagnosis. Heart Lung J Acute Crit Care 44(5):368–375
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lin, R.F., Lee, C., Tsai, KC. (2019). Comparison of Triage Models of Suspected ACS Patients: A Case Study of the Far Eastern Memorial Hospital. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 818. Springer, Cham. https://doi.org/10.1007/978-3-319-96098-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-96098-2_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-96097-5
Online ISBN: 978-3-319-96098-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)