title: Validation of an automated electronic algorithm and "dashboard" to identify and characterize decompensated heart failure admissions across a medical center.
abstract: BACKGROUND
  We aim to validate the diagnostic performance of the first fully automatic, electronic heart failure (HF) identification algorithm and evaluate the implementation of an HF Dashboard system with 2 components: real-time identification of decompensated HF admissions and accurate characterization of disease characteristics and medical therapy.
  
  
  METHODS
  We constructed an HF identification algorithm requiring 3 of 4 identifiers: B-type natriuretic peptide >400 pg/mL; admitting HF diagnosis; history of HF International Classification of Disease, Ninth Revision, diagnosis codes; and intravenous diuretic administration. We validated the diagnostic accuracy of the components individually (n = 366) and combined in the HF algorithm (n = 150) compared with a blinded provider panel in 2 separate cohorts. We built an HF Dashboard within the electronic medical record characterizing the disease and medical therapies of HF admissions identified by the HF algorithm. We evaluated the HF Dashboard's performance over 26 months of clinical use.
  
  
  RESULTS
  Individually, the algorithm components displayed variable sensitivity and specificity, respectively: B-type natriuretic peptide >400 pg/mL (89% and 87%); diuretic (80% and 92%); and International Classification of Disease, Ninth Revision, code (56% and 95%). The HF algorithm achieved a high specificity (95%), positive predictive value (82%), and negative predictive value (85%) but achieved limited sensitivity (56%) secondary to missing provider-generated identification data. The HF Dashboard identified and characterized 3147 HF admissions over 26 months.
  
  
  CONCLUSIONS
  Automated identification and characterization systems can be developed and used with a substantial degree of specificity for the diagnosis of decompensated HF, although sensitivity is limited by clinical data input.
authors.affiliation: Department of Pharmacy Practice, Lipscomb University College of Pharmacy, Nashville, TN; Department of Pharmacy, Vanderbilt University Medical Center, Nashville, TN. Electronic address: zachary.l.cox@vanderbilt.edu.
authors.forename: Zachary L
authors.initials: ZL
authors.lastname: Cox
authors.affiliation: Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN.
authors.forename: Connie M
authors.initials: CM
authors.lastname: Lewis
authors.affiliation: Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN.
authors.forename: Pikki
authors.initials: P
authors.lastname: Lai
authors.affiliation: Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Lenihan
mesh_terms: D000368:Aged; D000465:Algorithms; D004232:Diuretics / Q000627:therapeutic use; D057286:Electronic Health Records; D005260:Female; D006333:Heart Failure / Q000175:diagnosis*; D006760:Hospitalization; D006801:Humans; D007262:Infusions, Intravenous; D008297:Male; D008875:Middle Aged; D020097:Natriuretic Peptide, Brain / Q000097:blood; D012680:Sensitivity and Specificity; D062606:Tertiary Care Centers
chemical_list: D004232:Diuretics; D020097:Natriuretic Peptide, Brain