Throughout the history of modern medicine the observation of patient characteristics, health, and treatment has been driven by a desire to advance knowledge around human health and in turn better inform the practice and administration of healthcare. Captured through both practice and research such observations have provided the foundation on which evidence-based medicine was built. However, the advent of digitized health and wellness data has resulted in a volume of information so large it can no longer be reasonably expected that an individual can consume it. In response healthcare has turned to analytical approaches, combining statistics, machine learning, and computer science methodologies, to foster the growth of a field known as health informatics. Drawing on data collected from entities around the globe, health informatics has successfully delivered the capability to identify and extract “best practices” amid the breadth of data available. Yet these practices alone have often been insufficient in advancing healthcare knowledge, as the utilization of data to apply practices to new individuals and scenarios fulfills only one objective of learning as famously defined by Benjamin Bloom. This dissertation will present the notion that informatics techniques now provide an opportunity to advance health knowledge by providing evidence in a manner that realizes a broader set of Bloom learning objectives from understanding to synthesis.
Accordingly, the work presented in this document is broken into three distinct sections, each examining informatics' role in addressing a grouping of Bloom's learning objectives. It will first highlight the ability of informatics to provide a deeper understanding of health data and models employed in practice and research. It next focuses on the ability of informatics to analyze and apply data, presenting novel models and metrics to augment existing workflows rather than replace them. Finally, it explores how informatics can evaluate current processes and formulate data to not only explain what is observed, but to advance and inform new knowledge around health practices and even the data itself.
|School:||University of Notre Dame|
|Department:||Computer Science and Engineering|
|School Location:||United States -- Indiana|
|Source:||DAI-B 80/06(E), Dissertation Abstracts International|
|Subjects:||Health sciences, Computer science|
|Keywords:||Data science, Health informatics, Modern medicine|
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