Clinical Decision Support to Efficiently Identify Patients Eligible for Advanced Heart Failure Therapies

J Card Fail. 2017 Oct;23(10):719-726. doi: 10.1016/j.cardfail.2017.08.449. Epub 2017 Aug 16.

Abstract

Background: Patients who need and receive timely advanced heart failure (HF) therapies have better long-term survival. However, many of these patients are not identified and referred as soon as they should be.

Methods: A clinical decision support (CDS) application sent secure email notifications to HF patients' providers when they transitioned to advanced disease. Patients identified with CDS in 2015 were compared with control patients from 2013 to 2014. Kaplan-Meier methods and Cox regression were used in this intention-to-treat analysis to compare differences between visits to specialized and survival.

Results: Intervention patients were referred to specialized heart facilities significantly more often within 30 days (57% vs 34%; P < .001), 60 days (69% vs 44%; P < .0001), 90 days (73% vs 49%; P < .0001), and 180 days (79% vs 58%; P < .0001). Age and sex did not predict heart facility visits, but renal disease did and patients of nonwhite race were less likely to visit specialized heart facilities. Significantly more intervention patients were found to be alive at 30 (95% vs 92%; P = .036), 60 (95% vs 90%; P = .0013), 90 (94% vs 87%; P = .0002), and 180 days (92% vs 84%; P = .0001). Age, sex, and some comorbid diseases were also predictors of mortality, but race was not.

Conclusions: We found that CDS can facilitate the early identification of patients needing advanced HF therapy and that its use was associated with significantly more patients visiting specialized heart facilities and longer survival.

Keywords: Advanced heart failure; clinical decision support; patient surveillance; survival.

MeSH terms

  • Aged
  • Decision Support Systems, Clinical / standards*
  • Decision Support Systems, Clinical / trends
  • Female
  • Heart Failure / diagnostic imaging*
  • Heart Failure / therapy*
  • Humans
  • Male
  • Middle Aged
  • Patient Selection*
  • Referral and Consultation / standards*
  • Referral and Consultation / trends
  • Retrospective Studies