Rationale: Studies of adults presenting to the emergency department (ED) with acute pulmonary embolism (PE) suggest that those who are low risk on the PE Severity Index (classes I and II) can be managed safely without hospitalization. However, the impact of relative contraindications to home management on outcomes has not been described.Objectives: To compare 5-day and 30-day adverse event rates among low-risk ED patients with acute PE without and with outpatient ineligibility criteria. Methods:We conducted a retrospective multicenter cohort study of adults presenting to the ED with acute low-risk PE between 2010 and 2012. We evaluated the association between outpatient treatment eligibility criteria based on a comprehensive list of relative contraindications and 5-day adverse events and 30-day outcomes, including major hemorrhage, recurrent venous thromboembolism, and all-cause mortality.Measurements and Main Results: Of 423 adults with acute lowrisk PE, 271 (64.1%) had no relative contraindications to outpatient treatment (outpatient eligible), whereas 152 (35.9%) had at least one contraindication (outpatient ineligible). Relative contraindications were categorized as PE-related factors (n = 112; 26.5%), comorbid illness (n = 42; 9.9%), and psychosocial barriers (n = 19; 4.5%). There were no 5-day events in the outpatient-eligible group (95% upper confidence limit, 1.7%) and two events (1.3%; 95% confidence interval [CI], 0.1-5.0%) in the outpatient-ineligible group (P = 0.13). At 30 days, there were five events (two recurrent venous thromboemboli and three major bleeding events) in the outpatient-eligible group (1.8%; 95% CI, 0.7-4.4%) compared with nine in the ineligible group (5.9%; 95% CI, 2.7-10.9%; P , 0.05). This difference remained significant when controlling for PE severity class.Conclusions: Nearly two-thirds of adults presenting to the ED with low-risk PE were potentially eligible for outpatient therapy. Relative contraindications to outpatient management were associated with an increased frequency of adverse events at 30 days among adults with low-risk PE.

KeywordsClinical decision support systems; electronic health record; risk assessment; pulmonary embolism; emergency medicine; data completeness Summary Background: The Pulmonary Embolism (PE) Severity Index identifies emergency department (ED) patients with acute PE that can be safely managed without hospitalization. However, the Index comprises 11 weighted variables, complexity that can impede its integration into contextual workflow. Objective: We designed a computerized version of the PE Severity Index (e-Index) to automatically extract the required variables from discrete fields in the electronic health record (EHR). We tested the e-Index on the study population to determine its accuracy compared with a gold standard generated by physician abstraction of the EHR on manual chart review. Methods: This retrospective cohort study included adults with objectively-confirmed acute PE in four community EDs from 2010-2012. Outcomes included performance characteristics of the e-Index for individual values, the number of cases requiring physician editing, and the accuracy of the e-Index risk category (low vs. higher). Results: For the 593 eligible patients, there were 6,523 values automatically extracted. Fifty one of these needed physician editing, yielding an accuracy at the value-level of 99.2% (95% confidence interval [CI], 99.0%-99.4%). Sensitivity was 96.9% (95% CI, 96.0%-97.9%) and specificity was 99.8% (95% CI, 99.7%-99.9%). The 51 corrected values were distributed among 47 cases: 43 cases required the correction of one variable and four cases required the correction of two. At the riskcategory level, the e-Index had an accuracy of 96.8% (95% CI, 95.0%-98.0%), under-classifying 16 higher-risk cases (2.7%) and over-classifying 3 low-risk cases (0.5%). Conclusion: Our automated extraction of variables from the EHR for the e-Index demonstrates substantial accuracy, requiring a minimum of physician editing. This should increase user acceptability and implementation success of a computerized clinical decision support system built around the e-Index, and may serve as a model to automate other complex risk stratification instruments.