Presentation
DH12 - Understanding Care Coordination Tasks of Older Adults with Mild Cognitive Impairment and their Care Partners
DescriptionMild Cognitive Impairment (MCI) is a diagnosable state of cognitive aging in which loss of cognitive function is greater than normal aging, but less than those diagnosed with dementia. It impacts approximately 12-18% of those aged 60 and older and progresses to dementia at a rate of approximately 8-15% per year, underscoring the importance of early identification and treatment (Petersen, 2016). Most people diagnosed with MCI (pwMCI) are community-dwelling older adults whose care is coordinated among informal care partner(s), typically spouses but often also adult children, and health care providers. Although pwMCI may experience challenges performing tasks and activities that are complex or require higher cognitive functions, such as medication and financial management (Hedman et al., 2013), they are able to independently engage in activities of daily living such as bathing, dressing, and eating. One important aspect of care for pwMCI is the need to empower the care partner to provide support when needed while allowing the individual to maintain autonomy. It is also critical to empower pwMCI to perform the tasks they are able to reduce care partner burden (Lara-Ruiz et al., 2019).
Many tools and services have been developed to support daily activities for pwMCI and their care partners. However, these solutions can be helpful or challenging, especially depending on the level of effort to personalize the support for specific priorities and preferences. Technology solutions driven by artificial intelligence have the potential to provide individualized support for care coordination tasks such as managing calendar appointments, grocery shopping, household chores, medication management, preparing meals, and facilitating social activities. These solutions can therefore adapt to the preferences and individual experiences of the users. Developing such tools requires a deep understanding of the unique needs, preferences, current practices, and challenges faced by pwMCI and their care partners as they navigate the landscape of arranging for day to day supports in a manner that supports independence and quality of life for the pwMCI and minimizes burden on care partners.The current study was designed to gain this understanding, with the goal of informing the development of future technologies to facilitate informal care coordination for pwMCI and their care partners.
To that end, we conducted semi-structured interviews with both pwMCI and their care partners in order to gain a deeper understanding of day to day care coordination and the associated challenges, as well as the strategies that are currently used to overcome these challenges. We conducted a total of 11 remote interviews; 4 of them with primary care partners of pwMCI and the remaining 7 with dyads consisting of a pwMCI along with their primary care partner. The dyads included spousal pairs, parents and their adult children, and adult siblings.
Interviews were audio recorded and transcribed. Our qualitative analysis of these transcripts focused on three dimensions of the care coordination experience. The first dimension is the “who” of care coordination, including any individual that may be involved and how their involvement (or lack thereof) impacts the coordination of care. The second dimension is the “what” of care coordination, encompassing any activities that care partners and pwMCI engage in that may need to be coordinated on a day to day basis. The third dimension is the “how” of care coordination, grounded in the tools that participants identified as part of their day to day care coordination. These three dimensions were coded for valence (positive/negative) to identify whether a given person, tool, or activity was expressed in a positive way (care coordination facilitators), a negative way (care coordination barriers), or a mixture of both. One researcher coded 11 interviews on the dimensions of “who”, “what”, and “how” with respect to the valence of each code in that dimension. A second researcher reviewed 20% of the coded dimensions and any disagreements were discussed to reach consensus. Both researchers utilized affinity diagrams to create further hierarchical categorization of each dimension. For example, tools were mapped into three groups depending on if they were a facilitator, barrier, or both, and then the codes within each group were organized to identify valence-specific categories.
The present analysis focused specifically on the “how,” or the means and tools of care coordination. Tools with a positive effect on care coordination included those that required little or no technological input (e.g., a handwritten tabletop calendar), those that involved people other than the primary care partner in a care scenario (e.g., a collaborative handwritten activity tracker termed a “diary” by the care partner), and various solutions for managing medications and health data (e.g., using the CVS Simple Dose program and creating written medication reminders). Tools with a negative effect on care coordination included activity trackers such as smart watches, at-home devices that require some level of programming, and various longitudinal support mechanisms that the primary care partner initiated to better coordinate care for the pwMCI. An example of a longitudinal support mechanism included a continuously updated checklist of tasks the care partner identified as needing to do themselves to ensure that the pwMCI had maximum autonomy. This behind-the-scenes effort of constantly keeping track of each of the pwMCI’s needs was described as a burden for the care partner, because the care partner felt that if such a list were not kept up to date, the pwMCI could no longer live independently, which the dyad was strongly opposed to. Some tools were discussed in both positive and negative terms, including care management tools that were both mobile and home-based, voice prompting of either a smart device, phone, or pwMCI, and means of granting consistent respite for primary care partners. In some cases, certain individuals spoke positively of these tools while others spoke of them negatively, but in other cases, participants viewed these tools as an important part of their care coordination efforts that, despite their importance, either proved difficult to use (e.g., voice prompting of a smart device) or created apprehension (e.g., means of granting consistent respite for primary care partners).
The proposed poster will present the findings from our qualitative coding analysis of care coordination tools, including insights surrounding the successes and struggles faced by people diagnosed with MCI and their care partners. These findings have implications for developing future support technologies that meet the needs and preferences of pwMCI and their care networks. The findings can also be used to create use case scenarios for technology developers that are rooted in the lived experiences of pwMCI.
References:
Hedman, A., Nygård, L., Almkvist, O., & Kottorp, A. (2013). Patterns of functioning in older adults with mild cognitive impairment: A two-year study focusing on everyday technology use. Aging & Mental Health, 17(6), 679–688. https://doi.org/10.1080/13607863.2013.777396
Lara-Ruiz, J., Kauzor, K., Gonzalez, K., Nakhla, M. Z., Banuelos, D., Woo, E., Apostolova, L. G., & Razani, J. (2019). The functional ability of MCI and Alzheimer’s patients predicts caregiver burden. GeroPsych, 32(1), 31–39. https://doi.org/10.1024/1662-9647/a000200
Petersen, R. C. (2016). Mild Cognitive Impairment. CONTINUUM: Lifelong Learning in Neurology, 22(2, Dementia), 404–418. https://doi.org/10.1212/con.0000000000000313
Many tools and services have been developed to support daily activities for pwMCI and their care partners. However, these solutions can be helpful or challenging, especially depending on the level of effort to personalize the support for specific priorities and preferences. Technology solutions driven by artificial intelligence have the potential to provide individualized support for care coordination tasks such as managing calendar appointments, grocery shopping, household chores, medication management, preparing meals, and facilitating social activities. These solutions can therefore adapt to the preferences and individual experiences of the users. Developing such tools requires a deep understanding of the unique needs, preferences, current practices, and challenges faced by pwMCI and their care partners as they navigate the landscape of arranging for day to day supports in a manner that supports independence and quality of life for the pwMCI and minimizes burden on care partners.The current study was designed to gain this understanding, with the goal of informing the development of future technologies to facilitate informal care coordination for pwMCI and their care partners.
To that end, we conducted semi-structured interviews with both pwMCI and their care partners in order to gain a deeper understanding of day to day care coordination and the associated challenges, as well as the strategies that are currently used to overcome these challenges. We conducted a total of 11 remote interviews; 4 of them with primary care partners of pwMCI and the remaining 7 with dyads consisting of a pwMCI along with their primary care partner. The dyads included spousal pairs, parents and their adult children, and adult siblings.
Interviews were audio recorded and transcribed. Our qualitative analysis of these transcripts focused on three dimensions of the care coordination experience. The first dimension is the “who” of care coordination, including any individual that may be involved and how their involvement (or lack thereof) impacts the coordination of care. The second dimension is the “what” of care coordination, encompassing any activities that care partners and pwMCI engage in that may need to be coordinated on a day to day basis. The third dimension is the “how” of care coordination, grounded in the tools that participants identified as part of their day to day care coordination. These three dimensions were coded for valence (positive/negative) to identify whether a given person, tool, or activity was expressed in a positive way (care coordination facilitators), a negative way (care coordination barriers), or a mixture of both. One researcher coded 11 interviews on the dimensions of “who”, “what”, and “how” with respect to the valence of each code in that dimension. A second researcher reviewed 20% of the coded dimensions and any disagreements were discussed to reach consensus. Both researchers utilized affinity diagrams to create further hierarchical categorization of each dimension. For example, tools were mapped into three groups depending on if they were a facilitator, barrier, or both, and then the codes within each group were organized to identify valence-specific categories.
The present analysis focused specifically on the “how,” or the means and tools of care coordination. Tools with a positive effect on care coordination included those that required little or no technological input (e.g., a handwritten tabletop calendar), those that involved people other than the primary care partner in a care scenario (e.g., a collaborative handwritten activity tracker termed a “diary” by the care partner), and various solutions for managing medications and health data (e.g., using the CVS Simple Dose program and creating written medication reminders). Tools with a negative effect on care coordination included activity trackers such as smart watches, at-home devices that require some level of programming, and various longitudinal support mechanisms that the primary care partner initiated to better coordinate care for the pwMCI. An example of a longitudinal support mechanism included a continuously updated checklist of tasks the care partner identified as needing to do themselves to ensure that the pwMCI had maximum autonomy. This behind-the-scenes effort of constantly keeping track of each of the pwMCI’s needs was described as a burden for the care partner, because the care partner felt that if such a list were not kept up to date, the pwMCI could no longer live independently, which the dyad was strongly opposed to. Some tools were discussed in both positive and negative terms, including care management tools that were both mobile and home-based, voice prompting of either a smart device, phone, or pwMCI, and means of granting consistent respite for primary care partners. In some cases, certain individuals spoke positively of these tools while others spoke of them negatively, but in other cases, participants viewed these tools as an important part of their care coordination efforts that, despite their importance, either proved difficult to use (e.g., voice prompting of a smart device) or created apprehension (e.g., means of granting consistent respite for primary care partners).
The proposed poster will present the findings from our qualitative coding analysis of care coordination tools, including insights surrounding the successes and struggles faced by people diagnosed with MCI and their care partners. These findings have implications for developing future support technologies that meet the needs and preferences of pwMCI and their care networks. The findings can also be used to create use case scenarios for technology developers that are rooted in the lived experiences of pwMCI.
References:
Hedman, A., Nygård, L., Almkvist, O., & Kottorp, A. (2013). Patterns of functioning in older adults with mild cognitive impairment: A two-year study focusing on everyday technology use. Aging & Mental Health, 17(6), 679–688. https://doi.org/10.1080/13607863.2013.777396
Lara-Ruiz, J., Kauzor, K., Gonzalez, K., Nakhla, M. Z., Banuelos, D., Woo, E., Apostolova, L. G., & Razani, J. (2019). The functional ability of MCI and Alzheimer’s patients predicts caregiver burden. GeroPsych, 32(1), 31–39. https://doi.org/10.1024/1662-9647/a000200
Petersen, R. C. (2016). Mild Cognitive Impairment. CONTINUUM: Lifelong Learning in Neurology, 22(2, Dementia), 404–418. https://doi.org/10.1212/con.0000000000000313
Event Type
Poster Presentation
TimeMonday, March 254:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives