A Secondary Analysis of the Intensity of Hospice Visits Among Medicare Decedents in the Last Seven Days of Life by Place of Residence

Background In 2016, Medicare finalized the Service Intensity Add-on (SIA) payment policy to increase the intensity of hospice registered nurse (RN) or social worker (SW) visits in the last 7 days of life. The research objective was to compare the intensity of hospice RN or SW visits in the last 7 days of life among older decedents who received a hospice visit, while residing in a traditional home, an assisted living facility, or long-term nursing home. Methods A retrospective analysis using 2016-2018 Medicare data of decedents 65 years or older (n= 2 067 863) related to the Medicare SIA payment policy. Intensity was defined as the number and duration of hospice RN or SW visits in the last 7 days of life using Medicare claims code G0299 and G0155. Results Regression results suggest that decedents who received a SIA related visit while residing in an assisted living facility, had on average a slightly longer duration of hospice RN visits in the last 7 days of life, compared to decedents residing in a traditional home, after controlling for demographics and other factors (P<.0001). The duration of hospice RN visits remained unchanged among decedents who received a SIA visit in 2017 or 2018, when compared to 2016 (P <.0001). Overall the average number of hospice SW visits did not differ by place of residence among decedents who received a SIA visit. Conclusions Among decedents who received a SIA related visit, the duration of hospice RN visits were slightly different by place of residence.

An Exploration of Social Participation Among Older Adults in an Assisted Living Facility

Date Presented 04/200/21 This qualitative study explored the perceptions and social participation experiences of adults residing in an assisted living facility (ALF). Four themes emerged: impressions and social transition, social connections impacting relationships, motivation as key to socialization, and resident-perceived barriers to socialization. Findings implicate the need for change within the ALF setting to best facilitate the social participation and minimize the social isolation of its residents. Primary Author and Speaker: Nicole A. Fidanza Additional Authors and Speakers: Whitney Ogechi Ihezue, J. Rita Park, and Janet Njelesani

Adjustment Strategies of Older Adults Transitioning Into an Assisted Living Facility: Implications for RT Practice

Transitions into an assisted living facility (ALF) may have major impacts on the well-being of older adults, both positively and negatively. The purpose of this study was to explore strategies that older adults are implementing to maintain or improve their well-being during their transition into an ALF. A grounded theory, descriptive approach employed 14 individual, in-person interviews at an ALF in the rural, southeastern U.S. Eight central findings emerged as adjustment strategies used by older adults, catorgizied as active and passive strategies. The five active strategies were identified as importance of health promoting activities (subthemes: promoting physical health and promoting mental health), connections to the outside world (subthemes: community integration outings and community visitors), placing possessions, finding a new routine, and engaging in spiritual practices. Three passive strategies were identified: peer support, staff support, and prior familiarity with the ALF. Implications for recreational therapists working with older adults in ALFs are detailed and future research recommendations are provided.

Computing for Numeracy: How Safe is Your COVID-19 Social Bubble?

The COVID-19 pandemic has led many people to form social bubbles. These social bubbles are small groups of people who interact with one another but restrict interactions with the outside world. The assumption in forming social bubbles is that risk of infection and severe outcomes, like hospitalization, are reduced. How effective are social bubbles? A Bayesian event tree is developed to calculate the probabilities of specific outcomes, like hospitalization, using example rates of infection in the greater community and example prior functions describing the effectiveness of isolation by members of the social bubble. The probabilities are solved for two contrasting examples: members of an assisted living facility and members of a classroom, including their teacher. A web-based calculator is provided so readers can experiment with the Bayesian event tree and learn more about these probabilities by modeling their own social bubble.