The accuracy of an electronic Pulmonary Embolism Severity Index auto-populated from the electronic health record: Setting the stage for computerized clinical decision support

Kaisers Permanente CREST Network

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)318-333
Number of pages16
JournalApplied Clinical Informatics
Volume6
Issue number2
DOIs
StatePublished - 2015

Keywords

  • Clinical decision support systems
  • Data completeness
  • Electronic health record
  • Emergency medicine
  • Pulmonary embolism
  • Risk assessment

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Health Information Management

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