Date of Award

January 2015

Document Type

Thesis

Degree Name

Doctor of Nursing Practice (DNP)

Department

Yale University School of Nursing

First Advisor

Ruth McCorkle

Abstract

The goal of consistent, predictable, improved outcomes has continued to elude the scientific community in the thirty years since lung transplantation became the procedure of choice for patients with terminal, non-malignant lung disease. Background: Though there is a consensus regarding disease-specific indications for a lung transplant, ambiguity remains regarding how patient-specific attributes should influence lung transplant candidacy. This project had three aims: 1) to establish the missing domains of the interdisciplinary assessment of the lung transplant candidate, 2) to have these domains validated by an international panel of lung transplant experts, and 3) to recommend the next step for inclusion of these domains into the lung transplant candidate selection process. Methods: Three levels of evidence were reviewed. A search for standards and guidelines, a systematic literature review and a validation of domains by experts were conducted. Results: Seven domains of patient attributes were identified as relevant to lung transplant patient selection: cognitive performance, frailty, psychological factors, self-efficacy, social support, quality of life, and sociodemographic factors. Within each domain, several elements to be incorporated in the process of patient assessment were identified. Conclusions: Assessment of the missing domains and elements should be incorporated into the interdisciplinary lung transplant evaluation process. Standardized recognition and reporting of the patient-specific attributes will inform the work of individual transplant programs and the international transplant community. Further study is needed to better understand how nurses assess lung transplant candidates, how they communicate their findings within interdisciplinary settings, and how those findings relate to transplant outcomes.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 02/22/2019

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