Georgia Tech
Providing care for an individual diagnosed with Mild Cognitive Impairment in an informal setting is an experience characterized by the unique needs and preferences of the person diagnosed with MCI as well as the person(s) providing their care. In order to ground the development of potential future care supports in the current lived experiences of people diagnosed with MCI and their care partners, the study I am currently conducting leverages qualitative interviews with these two demographics to gain a deeper understanding of how informally coordinated care is arranged in day-to-day life, as well as any challenges faced in these arrangements, and what strategies are used to overcome the challenges that may arise. This rich, qualitative information serves as the starting point for using inductive coding to determine who is part of these informal care networks, what activities are coordinated around, and how those activities are coordinated. The ultimate goal of this process is to create a codified system for understanding the elements of care coordination that facilitate care, as well as those that may act as a barrier to the provision of care. This system will allow for the development and deployment of use case scenarios that base future work in this field on real-world user experiences.
The high-level insights derived from our preliminary efforts toward qualitatively coding this data include that the various aspects of activity coordination and care provision can act as either facilitators - wherein the pwMCI and CP find success in the implementation of a particular coordination strategy - or barriers - wherein the pwMCI and CP find challenges through either the unsuccessful implementation of a strategy or the inability to implement a particular strategy. These insights provide a foundational understanding of what does and does not work when providing informal care for someone diagnosed with MCI, and establishing this baseline knowledge will allow for the data we synthesize to frame and present opportunities for AI-systems to support informal care coordination in MCI.