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Emergency physicians’ attitudes toward a clinical prediction rule for the identification and early discharge of low risk patients with chest discomfort

Published online by Cambridge University Press:  21 May 2015

Cameron K. MacGougan
Affiliation:
Queen’s University, Kingston, Ont.
James M. Christenson*
Affiliation:
Department of Emergency Medicine, St. Paul’s Hospital, Vancouver, BC The Centre for Health Evaluation and Outcome Studies (CHEOS), St. Paul’s Hospital, Vancouver, BC
Grant D. Innes
Affiliation:
Department of Emergency Medicine, St. Paul’s Hospital, Vancouver, BC The Centre for Health Evaluation and Outcome Studies (CHEOS), St. Paul’s Hospital, Vancouver, BC
Janet Raboud
Affiliation:
The Centre for Health Evaluation and Outcome Studies (CHEOS), St. Paul’s Hospital, Vancouver, BC
*
Department of Emergency Medicine, St. Paul’s Hospital, 1081 Burrard St., Vancouver BC V6Z 1Y6; [email protected]

Abstract

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Objectives:

To determine Canadian emergency physicians’ estimates regarding the safety and efficiency of chest discomfort management in their emergency department (ED), and their attitudes toward and perception of the need for a chest discomfort clinical prediction rule that identifies very low risk patients who are safe to discharge after a brief ED assessment.

Methods:

300 members of the Canadian Association of Emergency Physicians (CAEP) were randomly selected to receive a confidential mail survey, which invited them to provide information on current disposition of patients with chest discomfort and their opinions regarding the value of a clinical prediction rule to identify patients with chest discomfort who are safe to discharge after a brief (~2 hour) assessment.

Results:

Of the 300 physicians selected, 288 were eligible for the survey and 235 (82%) responded. Only 5% follow discharged patients to measure safe practice. Overall, 165 (70%) felt the proposed prediction rule would be very useful and 43 (18%) felt it would be useful. Almost all (94%) believed a prediction rule would be useful if it identified patients safe for discharge without increasing the current rate of missed acute myocardial infarction (estimated at 2%). Most respondents (59%) believed that a clinical prediction rule should suggest a course of action, while 30% felt it should convey a probability of disease.

Conclusions:

Canadian emergency physicians support the concept of a clinical prediction rule for the early discharge of patients with chest discomfort. Most believe that such a rule would be useful if it identified patients who are safe for discharge after a brief assessment, while maintaining current levels of safety. Future research should be aimed at deriving a clinical prediction rule to identify low risk patients who can be safely discharged after a limited emergency department evaluation.

Type
EM Advances • Progrès De La MU
Copyright
Copyright © Canadian Association of Emergency Physicians 2001

References

1.McCarthy, BD, Beshansky, JR, D’Agostino, RB, Selker, HP.Missed diagnoses of acute myocardial infarction in the emergency department: results from a multicenter. Ann Emerg Med 1993;22:57982.CrossRefGoogle ScholarPubMed
2.Pope, J, Aufderheide, T, Ruthazer, R, Woolard, R, Feldman, J, Beshansky, J, et al. Missed diagnoses of acute cardiac ischemia in the emergency room. N Engl J Med 2000;342:116370.CrossRefGoogle Scholar
3.Gibler, WB, Runyon, JP, Levy, RC, Sayre, MR, Kacich, R, Hattemer, CR, et al. A rapid diagnostic and treatment center for patients with chest pain in the emergency department. Ann Emerg Med 1995;25:18.Google Scholar
4.Farkouh, M, Smars, P, Reeder, G, Zinsmeister, A, Evans, R, Meloy, T, et al. A clinical trial of a chest-pain observation unit for patients with unstable angina. N Engl J Med 1998;339:18828.Google Scholar
5.Dallara, J, Severance, HW, Davis, B, Schulz, G.Differences between chest pain observation service patients and admitted “rule-out myocardial infarction” patients. Acad Emerg Med 1997;4:693.Google Scholar
6.Mikhail, MG, Smith, FA, Gray, M, Britton, C, Frederiksen, SM.Cost-effectiveness of mandatory stress testing in chest pain center patients. Ann Emerg Med 1997;29:8898.CrossRefGoogle ScholarPubMed
7.Gomez, MA, Anderson, JL, Karagounis, LA, Muhlestein, JB, Mooers, FB.An emergency department-based protocol for rapidly ruling out myocardial ischemia reduces hospital time and expense: results of a randomized study (ROMIO). J Am Coll Cardiol 1996;28:2533.Google Scholar
8.Gaspoz, J, Lee, T, Cook, F, Weisberg, M, Goldman, L.Outcome of patients who were admitted to a new short-stay unit to “rule-out” myocardial infarction. Am J Cardiol 1991;68:1459.Google Scholar
9.Hoekstra, JW, Gibler, WB, Levy, RC, Sayre, M, Naber, W, Chandra, A, et al. Emergency-department diagnosis of acute myocardial infarction and ischemia: a cost analysis of two diagnostic protocols. Acad Emerg Med 1994;1:10310.CrossRefGoogle ScholarPubMed
10.Laupacis, A, Sekar, N, Stiell, IG.Clinical prediction rules: a review and suggested modifications of methodologic standards. JAMA 1997;277:48894.CrossRefGoogle Scholar
11.Pozen, M, D’Agostino, R, Mitchell, J, Rosenfeld, M, Guglielmino, J, Schwartz, M, et al. The usefulness of a predictive instrument to reduce inappropriate admissions to the coronary care unit. Ann Intern Med 1980;92:23842.CrossRefGoogle Scholar
12.Pozen, M, D’Agostino, R, Selker, H, Sytkowski, P, Hood, W.A predictive instrument to improve coronary care unit admission practices in acute ischemic heart disease. N Engl J Med 1984;310:12738.CrossRefGoogle ScholarPubMed
13.Selker, H, Beshansky, J, Griffith, J, Aufderheide, T, Ballin, D, Bernard, S, et al. 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. Ann Intern Med 1998;129:84555.Google Scholar
14.Goldman, L, Weinberg, M, Weisberg, M, Olshen, R, Cook, EF, Sargent, RK, et al. A computer-derived protocol to aid in the diagnosis of emergency room patients with acute chest pain. N Engl J Med 1982;307:58896.CrossRefGoogle ScholarPubMed
15.Goldman, L, Cook, E, Brand, D.A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med 1988;318:797803.CrossRefGoogle ScholarPubMed
16.Reilly, B, Durairaj, L, Husain, S, Acob, C, Evans, A, Hu, T, et al. Performance and potential impact of a chest pain decision prediction rule in a large public hospital. Am J Med 1999;106:28591.CrossRefGoogle Scholar
17.Goldman, L, Cook, EF, Johnson, PA, Brand, DA, Rouan, GW, Lee, TH.Prediction of the need for intensive care in patients who come to the emergency departments with acute chest pain. N Engl J Med 1996;334:1498504.Google Scholar
18.Graham, I, Stiell, I, Laupacis, A, O’Connor, A, Wells, G.Emergency physicians’ attitudes toward and use of clinical decision rules for radiography. Acad Emerg Med 1998;5:13440.Google Scholar
19.Dillman, D.Mail and telephone surveys: the total design method. New York: Wiley Interscience Publishing; 1978.Google Scholar
20.Christenson, J.Acute coronary syndromes: we must improve diagnostic efficiency in the emergency department. CJEM 1999;1:225.CrossRefGoogle ScholarPubMed