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Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke.

Publication ,  Journal Article
Navar-Boggan, AM; Rymer, JA; Piccini, JP; Shatila, W; Ring, L; Stafford, JA; Al-Khatib, SM; Peterson, ED
Published in: Am Heart J
January 2015

BACKGROUND: There is no universally accepted algorithm for identifying atrial fibrillation (AF) patients and stroke risk using electronic data for use in performance measures. METHODS: Patients with AF seen in clinic were identified based on International Classification of Diseases, Ninth Revision(ICD-9) codes. CHADS(2) and CHA(2)DS(s)-Vasc scores were derived from a broad, 10-year algorithm using IICD-9 codes dating back 10 years and a restrictive, 1-year algorithm that required a diagnosis within the past year. Accuracy of claims-based AF diagnoses and of each stroke risk classification algorithm were evaluated using chart reviews for 300 patients. These algorithms were applied to assess system-wide anticoagulation rates. RESULTS: Between 6/1/2011, and 5/31/2012, we identified 6,397 patients with AF. Chart reviews confirmed AF or atrial flutter in 95.7%. A 1-year algorithm using CHA(2)DS(2)-Vasc score ≥2 to identify patients at risk for stroke maximized positive predictive value (97.5% [negative predictive value 65.1%]). The PPV of the 10-year algorithm using CHADS(2) was 88.0%; 12% those identified as high-risk had CHADS(2) scores <2. Anticoagulation rates were identical using 1-year and 10-year algorithms for patients with CHADS(2) scores ≥2 (58.5% on anticoagulation) and CHA(2)DS(2)-Vasc scores ≥2 (56.0% on anticoagulation). CONCLUSIONS: Automated methods can be used to identify patients with prevalent AF indicated for anticoagulation but may have misclassification up to 12%, which limits the utility of relying on administrative data alone for quality assessment. Misclassification is minimized by requiring comorbidity diagnoses within the prior year and using a CHA(2)DS(2)-Vasc based algorithm. Despite differences in accuracy between algorithms, system-wide anticoagulation rates assessed were similar regardless of algorithm used.

Duke Scholars

Published In

Am Heart J

DOI

EISSN

1097-6744

Publication Date

January 2015

Volume

169

Issue

1

Start / End Page

39 / 44.e2

Location

United States

Related Subject Headings

  • Stroke
  • Sensitivity and Specificity
  • Risk Assessment
  • Middle Aged
  • Male
  • Humans
  • Female
  • Cardiovascular System & Hematology
  • Atrial Fibrillation
  • Anticoagulants
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Navar-Boggan, A. M., Rymer, J. A., Piccini, J. P., Shatila, W., Ring, L., Stafford, J. A., … Peterson, E. D. (2015). Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke. Am Heart J, 169(1), 39-44.e2. https://doi.org/10.1016/j.ahj.2014.09.014
Navar-Boggan, Ann Marie, Jennifer A. Rymer, Jonathan P. Piccini, Wassim Shatila, Lauren Ring, Judith A. Stafford, Sana M. Al-Khatib, and Eric D. Peterson. “Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke.Am Heart J 169, no. 1 (January 2015): 39-44.e2. https://doi.org/10.1016/j.ahj.2014.09.014.
Navar-Boggan AM, Rymer JA, Piccini JP, Shatila W, Ring L, Stafford JA, et al. Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke. Am Heart J. 2015 Jan;169(1):39-44.e2.
Navar-Boggan, Ann Marie, et al. “Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke.Am Heart J, vol. 169, no. 1, Jan. 2015, pp. 39-44.e2. Pubmed, doi:10.1016/j.ahj.2014.09.014.
Navar-Boggan AM, Rymer JA, Piccini JP, Shatila W, Ring L, Stafford JA, Al-Khatib SM, Peterson ED. Accuracy and validation of an automated electronic algorithm to identify patients with atrial fibrillation at risk for stroke. Am Heart J. 2015 Jan;169(1):39-44.e2.
Journal cover image

Published In

Am Heart J

DOI

EISSN

1097-6744

Publication Date

January 2015

Volume

169

Issue

1

Start / End Page

39 / 44.e2

Location

United States

Related Subject Headings

  • Stroke
  • Sensitivity and Specificity
  • Risk Assessment
  • Middle Aged
  • Male
  • Humans
  • Female
  • Cardiovascular System & Hematology
  • Atrial Fibrillation
  • Anticoagulants