Defense Date
11-2-2017
Graduation Date
Fall 1-1-2017
Availability
One-year Embargo
Submission Type
dissertation
Degree Name
PhD
Department
Health Care Ethics
School
McAnulty College and Graduate School of Liberal Arts
Committee Chair
Gerard Magill
Committee Member
Henk ten Have
Committee Member
Joris Gielen
Keywords
organizational, ethics, genetics, gene, individual, privacy, population health
Abstract
The American culture holds the right to privacy as one of the most esteemed rights for individuals. As such, the culture adamantly defends the right to privacy to ensure individuals have the opportunity to live freely. In the American healthcare system, the right to privacy is critical for individual autonomy. However, genetic science has pushed this boundary as it emphasizes the interdependency between individual and population health. Genetic technologies for healthcare have been increasing at an exponential rate since the early 2000s. Their implantation into clinical care has been a slower process due to ethical dilemmas. Specifically, ethical dilemmas revolve around the use of individual genetic information for population benefit and future research. Ethical discourse on these dilemmas is typically from either the individual or population health perspective. This dissertation presents a healthcare organization’s perspective of ethical dilemmas when integrating genetic technologies into the organization. Specifically, this dissertation develops an organizational ethics framework to address the tensions between individuals and populations when implementing genetic technologies. The framework integrates three recurring and related ethical concepts in discussions about genetics: consent, conflict, compromise. The proposed framework is intended for organizational use to balance individual privacy and population benefits in both clinical care and research settings.
Language
English
Recommended Citation
Trani, C. (2017). An Organizational Ethics Framework to Balance Individual Privacy and Population Interests Regarding Genetic Technologies (Doctoral dissertation, Duquesne University). Retrieved from https://dsc.duq.edu/etd/227