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LO016: Can we use administrative data to define an emergency department population at risk for pulmonary embolism? Development and validation of an algorithm to identify a research population

Published online by Cambridge University Press:  02 June 2016

K. Burles
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
D. Wang
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
D. Grigat
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
E. Lang
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
J. Andruchow
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
G. Innes
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB
A. McRae
Affiliation:
Cumming School of Medicine, University of Calgary, Calgary, AB

Abstract

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Introduction: Pulmonary embolism (PE) is a potentially life-threatening condition that is in the differential diagnosis of many emergency department (ED) presentations. However, no diagnostic code for suspected PE exists. Thus, identifying the population of patients undergoing PE workup from administrative data for use as a denominator in clinical research and quality improvement can be difficult. To overcome this, we used standardized triage complaint codes and investigations to develop search algorithms useful to identify patients undergoing PE workup from an administrative dataset. Our objective was to quantify the sensitivity, specificity, and case yield of these search algorithms in order to identify a superior search strategy. Methods: Hospital administrative data for adult patients (age ≥18 years), which included standardized triage complaint codes and ICD-10 diagnostic codes for PE, were obtained from four urban EDs between July 2013 to January 2015. Standardized triage complaint codes were evaluated for the proportion of patients diagnosed with PE. Combinations of high-yield presenting complaints, in combination with D-dimer testing or imaging orders, were evaluated for sensitivity, specificity, and predictive values for PE. Results: Of 479,937 patients presenting with 174 different complaints, 1,048 were diagnosed with PE. The best-performing search strategy was the combination of standardized CEDIS complaints of Cardiac Pain, Chest Pain (Cardiac Features), Chest Pain (Non-Cardiac Features), Shortness of Breath, Syncope/Pre-syncope, Hemoptysis, and Unilateral Swollen Limb/Pain, along with with D-dimer testing and/or CTPA, or V/Q scan. This combination captured 808 PE diagnoses for a sensitivity of 77.1% (95%CI 74.4-79.5%) and specificity of 86.8% (95%CI 86.7-86.6%). Conclusion: We identified a high-yield combination of presenting complaints and test ordering that can be used to define an ED population with suspected PE. This population of patients can be used as a denominator in research or quality improvement work that evaluates the utilization of diagnostic testing for PE.

Type
Oral Presentations
Copyright
Copyright © Canadian Association of Emergency Physicians 2016