An informatics-based approach to reducing heart failure all-cause readmissions: the Stanford heart failure dashboard. (19th December 2016)

• Record Type: Journal Article
• Authors: Banerjee, Dipanjan; Thompson, Christine; Kell, Charlene; Shetty, Rajesh; Vetteth, Yohan; Grossman, Helene; DiBiase, Aria; Fowler, Michael
• Is Part Of: Journal of the American Medical Informatics Association. Volume 24:Number 3(2017:May)
• Page Start: 550
• Page End: 555
• Publication Date: 2016-12-19
• Subjects: Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocw150
• Languages: English
• ISSNs: 1067-5027

Abstract

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. Objectives: 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.