Abstract
Heart failure is the most rapidly growing cardiovascular disease in the U. S. (Boxer et al., 2010) and is the most common cause for hospital readmission (Fang et al., 2008; Heidenreich et al., 2013; Jencks et al., 2009) with a 30-day readmission rate of 24.8% (Centers for Medicare and Medicaid, 2012). Currently, many heart failure patients are discharged quickly from the hospital without adequate skills and knowledge to perform self-care tasks. Moreover, home health nurses provide the same care for all heart failure patients and have limited knowledge on what clinical health indicators might affect readmission. As a result, home health nurses are not able to design and implement tailored interventions to each heart failure patient.
Sigma Membership
Chi Tau
Lead Author Affiliation
The State University of New York at Delhi, Delhi, New York, USA
Type
Dissertation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Heart Failure, Home Health, Self-Care, Readmissions
Advisor
Mary Ann Swain
Second Advisor
Serdar Atav
Third Advisor
Susan Seibold-Simpson
Degree
PhD
Degree Grantor
The State University of New York at Binghamton
Degree Year
2015
Recommended Citation
Murphy, Jamie, "Predicting heart failure readmission using home health clinical indices" (2023). Dissertations. 1667.
https://www.sigmarepository.org/dissertations/1667
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
All permission requests should be directed accordingly and not to the Sigma Repository.
All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
None: Degree-based Submission
Acquisition
Proxy-submission
Date of Issue
2023-02-17
Full Text of Presentation
wf_yes
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 3713607; ProQuest document ID: 1708672839. The author still retains copyright.