title: An informatics-based approach to reducing heart failure all-cause readmissions: the Stanford heart failure dashboard.
abstract: BACKGROUND
  Reduction of 30-day all-cause readmissions for heart failure (HF) has become an important quality-of-care metric for health care systems. Many hospitals have implemented quality improvement programs designed to reduce 30-day all-cause readmissions for HF. Electronic medical record (EMR)-based measures have been employed to aid in these efforts, but their use has been largely adjunctive to, rather than integrated with, the overall effort.
  
  
  OBJECTIVE
  We hypothesized that a comprehensive EMR-based approach utilizing an HF dashboard in addition to an established HF readmission reduction program would further reduce 30-day all-cause index hospital readmission rates for HF.
  
  
  METHODS
  After establishing a quality improvement program to reduce 30-day HF readmission rates, we instituted EMR-based measures designed to improve cohort identification, intervention tracking, and readmission analysis, the latter 2 supported by an electronic HF dashboard. Our primary outcome measure was the 30-day index hospital readmission rate for HF, with secondary measures including the accuracy of identification of patients with HF and the percentage of patients receiving interventions designed to reduce all-cause readmissions for HF.
  
  
  RESULTS
  The HF dashboard facilitated improved penetration of our interventions and reduced readmission rates by allowing the clinical team to easily identify cohorts with high readmission rates and/or low intervention rates. We significantly reduced 30-day index hospital all-cause HF readmission rates from 18.2% at baseline to 14% after implementation of our quality improvement program ( P  = .045). Implementation of our EMR-based approach further significantly reduced 30-day index hospital readmission rates for HF to 10.1% ( P for trend = .0001). Daily time to screen patients decreased from 1 hour to 15 minutes, accuracy of cohort identification improved from 83% to 94.6% ( P  = .0001), and the percentage of patients receiving our interventions, such as patient education, also improved significantly from 22% to 100% over time ( P  < .0001).
  
  
  CONCLUSIONS
  In an institution with a quality improvement program already in place to reduce 30-day readmission rates for HF, an EMR-based approach further significantly reduced 30-day index hospital readmission rates.
authors.affiliation: Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Dipanjan
authors.initials: D
authors.lastname: Banerjee
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Christine
authors.initials: C
authors.lastname: Thompson
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Charlene
authors.initials: C
authors.lastname: Kell
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Rajesh
authors.initials: R
authors.lastname: Shetty
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Yohan
authors.initials: Y
authors.lastname: Vetteth
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Helene
authors.initials: H
authors.lastname: Grossman
authors.affiliation: Palo Alto Medical Foundation, Palo Alto, CA, USA.
authors.forename: Aria
authors.initials: A
authors.lastname: DiBiase
authors.affiliation: Stanford HealthCare, Stanford, CA, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Fowler
mesh_terms: D000368:Aged; D002140:California; D057286:Electronic Health Records; D006333:Heart Failure; D006761:Hospitals / Q000592:standards*; D006801:Humans; D006278:Medicare; D010359:Patient Readmission / Q000706:statistics & numerical data / Q000639:trends; D058996:Quality Improvement; D014481:United States; D014584:User-Computer Interface