A Pilot Study Exploring Treatment Burden in a Skilled Nursing Population

Abstract

Purpose: This study aimed to measure treatment burden in adults diagnosed with multiple chronic conditions transitioning from a skilled nursing facility to home.Design: Prospective, two-time point, cohort design utilizing convenience sampling from one skilled nursing facility in Northeast, Ohio.Methods: Seventy-four men and women participated answering self-report questions measuring treatment burden at two time points: prior to discharge and 30 days after discharge.Results: t-test analysis determined treatment burden was not statistically different between time points (p > .05). Multivariate analysis explained 23% of treatment burden's variance, with the severity of multiple chronic conditions and the presence of a caregiver predicting treatment burden (p < .05). Conclusion:Findings were contrary to our hypothesis of this population being at risk for high treatment burden.Clinical Relevance: Moderate, fluctuating levels of treatment burden suggest that it is possible to estimate demands of treatment prior to discharge from the skilled nursing facility to better inform discharge planning. KeywordsGeriatrics; multiple chronic conditions; patient transfer; self-management; treatment burden The care of individuals diagnosed with one or more chronic health conditions is one of the most challenging and complex issues facing the U.S. healthcare system today. Chronic health conditions are defined as medical conditions lasting greater than 1 year and requiring ongoing medical attention and/or limiting activities of daily living (Hwang, Weller, Ireys, & Anderson, 2001). One in four Americans are diagnosed with multiple chronic conditions (MCCs), which are defined as two or more chronic conditions (Ward, Schiller, & Goodman, 2014), and recent data suggest that MCCs are a major contributor to poor health outcomes

Examining the Association between Item Specific Treatment Burden and Adherence in People Living with HIV

“…These findings indicate that medication and physical activity aspects of treatment burden are important, measurable concepts contributing to medication and physical activity adherence independent of other known correlates of adherence. These findings also support the previous treatment burden literature (Dobler et al, 2018; Eton et al, 2017; Sav et al, 2016; Schreiner & Daly 2018), which advocated for treatment burden screening in chronic condition populations in order to identify individuals at risk for suboptimal self-management adherence. Results also confirm previous findings (Schreiner & Daly, 2018; Schreiner et al, 2019) suggesting that high levels of burden in a single item may indicate areas of specific non-adherence.…”

“…This finding suggests that higher levels of perceived burden associated with exercise leads to decreased physical activity independent of a PWH’s current physical level of function, even though physical function was also predictive of time spend in moderate to physical activity. This finding also supports the need for treatment burden screening in the clinical setting in order to determine the risk of physical activity non-adherence in PWH (Dobler et al, 2018; Eton et al, 2017; Sav et al, 2016; Schreiner & Daly 2018). Additionally, our finding of participants who reported no MVPA bouts, using validated cut-points (Sasaki et al, 2011), supports Matthews et al’s (2018) suggestion that the use of established cut-points underestimates overall MPVA in various adult populations.…”

“…Increasing self-management demands increase the risk for not only task-specific burden but also financial and emotional burden, all of which cumulatively increase the potential for non-adherence (Sav et al, 2013; Sav, Salehi, Mair, & McMillan, 2017). Increased treatment burden is associated not only with the number of co-morbid conditions but also with the severity of the chronic condition (Schreiner & Daly, 2018. )…”

“…The risk for suboptimal adherence to self-management is not limited to high aggregate or total level of treatment burden. In some cases, high burden in one area, such as medication-taking associated with ingesting many pills multiple times a day, may contribute to non-adherence only to this specific task, while the total aggregate level remains low (Schreiner & Daly 2018; Schreiner, Schreiner, & Daly 2019).…”

“…Several treatment burden scales (Eton et al, 2017; Tran et al, 2014) have been used to measure treatment burden in multi-morbid populations. Treatment burden screening could be integrated into clinical practice guidelines in order to improve health care outcomes in chronic condition populations, especially among those diagnosed with multiple chronic conditions (Dobler et al, 2018; Eton et al, 2017; Sav et al, 2016; Schreiner & Daly 2018). Despite increased emphasis on measuring treatment burden in various populations and a call for the integration of treatment burden screening into clinical care, this area of research has not quantified the impact of treatment burden on specific areas of self-management, such as medication, physical activity, and diet adherence.…”