Optimizing the Collection and Use of Patient-Generated Health Data
By: Meghan J. Reading
Publisher: [publisher not identified]
Published: 2018
Place of publication: [New York, N.Y.?]
Language: eng
Description: This dissertation aims to examine the collection and use of digital patient-generated health data (PGHD) in real-world settings, including existing barriers from the perspectives of patients and healthcare providers, and possible approaches to optimizing the process. In Chapter One, the potential of PGHD to improve health and wellness, particularly for individuals with chronic conditions, as well as known barriers to PGHD collection and use, are described. One chronic condition in particular, atrial fibrillation (AF), is then introduced as a use case for PGHD. Chapter Two contains an integrative review synthesizing findings from eleven studies reporting patients’ and providers’ needs when collecting and using PGHD, and identifying convergence and divergence between needs. Chapter Three contains a quantitative evaluation of sustained engagement, currently a major barrier to collection of PGHD, in a group of adults self-monitoring AF, as well as predictors and moderators of engagement that come from an adapted version of the Unified Theory of Acceptance and Use of Technology (UTAUT).

These individuals were previously enrolled in the randomized, controlled trial, the iPhone® Helping Evaluate Atrial Fibrillation Rhythm through Technology (iHEART). In Chapter Four, the adapted UTAUT model is explored in more detail through a qualitative investigation of sustained engagement with patients, healthcare providers, and research coordinators involved in the iHEART trial. Chapter Five summarizes the findings of this dissertation, including strengths and limitations, and elicits implications for the intersection of health policy and clinical practice, design, nursing, and future research from the findings.
Notes: Department: Nursing.

Thesis advisor: Jacqueline A. Merrill.

Thesis (Ph.D.)--Columbia University, 2018.