Defense Date

12-15-2022

Graduation Date

Spring 5-5-2023

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

Joris Gielen

Committee Member

Gerard Magill

Committee Member

Peter Osuji

Keywords

ethics, governance, data analytics, healthcare, artificial intelligence, technology, information management, big data, distributive justice, genomics

Abstract

Recent literature and studies on data governance usually focus on data ethics and governance from a specific country or industry, which has been mostly business, without considering the larger global impact that is affected. Data is a worldwide asset; thus, its implications and considerations should be viewed as such. Hence, this dissertation attempts to incorporate this view by weaving together topics in healthcare, such as the blending of finance and delivery, data governance at the micro and macro levels, data analytics in healthcare, ethics of AI and information management, and technology’s impact on end-of-life practices. Through highlighting these areas of healthcare, the dissertation explores characteristics of the healthcare landscape nationally and globally. As the use of data analytics in healthcare increases, the outcomes and their derivatives from these technologies increase proportionally.

Ethical governance of data analytics is focused on applying ethics to all aspects of data analytics, from beginning concepts to ending enforcement stages. This approach aims to take data governance throughout the “three P’s” of an organization: policies, processes, and procedures. This type of governance is crucial since it ensures that data analytics is safe and secure to utilize but also takes ethical principles into the foundation of the whole cycle of data. By reprioritizing ethics at the forefront of governance, those involved with these technologies will be able to produce and maintain ethical data analytics. Thus, each chapter will attempt to look at the past, present, and future issues surrounding the governance of data analytics. Understanding the ethical concerns within these issues will provide a forum for those issues that have yet to be addressed by data experts. Further, by locating the commonalities between these ethical implications, it becomes more feasible to formulate and recommend solutions. This dissertation identifies many ethical concerns and provides recommended solutions through frameworks for data governance. While these global issues are often significant, usually a concrete solution will not always work practically in all countries. Therefore, a framework for ethical data governance will help organizations and systems worldwide to build and utilize a more ethical data governance for its stakeholders.

Language

English

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