Patients with Heart Failure (HF) experience four million hospitalizations per year in the U.S. However, about three million of these hospitalizations annually are for causes other than for HF. Patients with HF hospitalized for other causes are at high risk for post-discharge mortality possibly in part because they are less likely to receive guideline-recommended care than patients that are hospitalized primarily for HF.
Right now, Clinical Decision Support Systems (CDSS) are used to improve care for patients in hospitals and for those specifically hospitalized for heart failure. However, CDSSs have not been developed to apply more broadly to patients with heart failure that are hospitalized for other causes. This has caused a gap in care for the millions of patients with HF who might experience improved outcomes if they were to receive guideline-recommended care.
The purpose of this study taking place 2014-2018 at New York University School of Medicine www.med.nnyu.edu and supported by the Agency for Healthcare Research and Quality (AHRQ) www.ahrq.gov, is going to test a CDSS for hospitalized patients who have HF regardless of the reason for hospitalization.
The first aim for the study is to develop an EHR-based algorithm to identify patients with HF by using a variety of computational techniques including natural language processing. The second aim is to develop a CDSS to support the delivery of guideline-recommended care to hospitalized patients with HF using human computer interaction techniques. The last aim is to implement and test the effectiveness of the CDSS on caring for patients with HF that are hospitalized for other causes.
For more information, contact Saul Blecker M.D at saul.blecker@nyumc.org or call 646-501-2515.