Abstract

Demand for home health services is increasing due to the growing aging population, increasing rates of chronic conditions, and advances in health care that support the provision of many health-related services in patients' homes. Home health agencies must adapt care delivery procedures to meet the needs of diverse and complex patients in order to keep them in their homes for as long as possible. However, it is unknown how home health nurses decide on visit patterns and implement their visit plans within the dynamic and unpredictable home health setting. This qualitative descriptive study was guided by an adapted nurse decision-making model with a superimposed socio-ecological lens and explored the processes that home health nurses use to decide on visit patterns and implement their visit plans for newly admitted patients.

Description

This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 10599268; ProQuest document ID: 1952046329. The author still retains copyright.

Author Details

Elliane Irani, PhD, RN

Sigma Membership

Alpha Mu

Type

Dissertation

Format Type

Text-based Document

Study Design/Type

Descriptive/Correlational

Research Approach

Qualitative Research

Keywords:

Care Planning, Home Health Care, Socio-Ecological

Advisor

Kathryn H. Bowles

Degree

PhD

Degree Grantor

University of Pennsylvania

Degree Year

2017

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

2024-09-09

Full Text of Presentation

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