Despite many interventions to promote medication adherence in older adults, we know little about how medication adherence has improved as a result of such interventions. The purpose of this study was to examine the long-term program impacts on medication adherence from participating in the Chronic Disease Self-Management Program (CDSMP). Secondary data used for this study included the CDSMP participants' sociodemographic characteristics and their baseline and 6- and 12-month follow-up assessments on health-related indicators, including medication adherence, self-rated health, depression, and patient communication skills. This study included those who were 65 years or older, had one or more chronic conditions, and attended at least the first or second session. Linear mixed models were used to analyze the impacts of short-term (6 months) changes in health-related indicators on long-term (12 months) changes in medication nonadherence. The subset analyses were performed among participants with self-rated major depression at baseline. This study included 687 participants. Self-reported medication adherence did not improve significantly at 6-month follow-up assessment but significantly improved at 12-month follow-up assessment. Among those with self-reported major depression at baseline assessment, the short-term improvements in depression and self-rated health were associated with long-term changes in medication adherence. The long-term impacts of the CDSMP on medication adherence were influenced by the short-term program impacts on health-related indicators. More targeted interventions are needed for patients with major depression, and programs such as the CDSMP can be particularly helpful among the population.

Introduction

Cost-related medication nonadherence (CRN) can negatively affect chronic disease prevention and management in an aging population. Limited data are available on the interacting influences among such factors as availability of financial resources, attitudes and beliefs of patients, and CRN. The objective of this study was to examine the causal paths among financial resource availability, patient attitudes and beliefs, and CRN.

Methods

We used a nationally representative sample (n = 4,818) from the 2015 National Health Interview Survey; selected respondents were aged 65 or older, had a diagnosis of hypertension or diabetes or both, and were prescribed medication for at least 1 of these conditions. We performed structural equation modeling to examine whether perceived medication affordability, access to health care, and patient satisfaction influenced the effects of financial resource availability on CRN (skipped doses, took less medicine, or delayed filling a prescription to save money).

Results

Six percent of respondents reported CRN in the previous 12 months. The model showed a good to fair fit, and all paths were significant (P < .05) except for age. The effects of financial resource availability on CRN was mediated through perceived medication affordability, access to health care, and patient satisfaction with health care services.

Conclusion

This study suggests that patients' attitudes and beliefs can mediate the effects of financial resource availability on CRN. We call for senior-friendly public health interventions that can address these modifiable barriers to reduce CRN among older adults with chronic conditions.

The Fit & Strong! program is an evidence-based, multi-component program promoting physical activity among older adults, particularly those suffering from lower-extremity osteoarthritis. The primary purpose of the study is to examine if the Fit & Strong! program translated into a lay-leader model can produce comparable outcomes to the original program taught by physical therapists and/or certified exercise instructors. A single-group, pre-post study design was employed, and data were collected at the baseline (n = 136 participants) and the intervention conclusion (n = 71) with both baseline and post-intervention data. The measurements included socio-demographic information, health- and behavior-related information, and health-related quality of life. Various statistical tests were used for the program impact analysis and examination of the association between participant characteristics and program completion. As in the original study, there were statistically significant (p < 0.05) improvements in self-efficacy for exercise, aerobic capacity, joint stiffness, level of energy, and amount and intensity of physical activities. The odds of completing the program were significantly lower for the participants from rural areas and those having multiple chronic conditions. Successful adaptation of the Fit & Strong! program to a lay-leader model can increase the likelihood of program dissemination by broadening the selection pool of instructors and, hence, reducing the potential issue of resource limitation. However, high program attrition rates (54.1%) emphasize the importance of adopting evidence-based strategies for improving the retention of the participants from rural areas and those with multiple chronic conditions.

The growing population of older adults has attracted concern from policymakers due in part to the fact that they are at higher risk of costly and potentially injurious falls. Responding to this concern, this study investigated fall-related hospitalizations among those aged 65 and older. Hospitalizations rose from 49,299 to 58,931, with charges and costs (estimated based on charges) increasing from $2.5 billion to $3.6 billion and under $900 million to over $1.1 billion, respectively. The intraclass correlation coefficients from linear mixed-effect models (with charges and costs serving as dependent variables) indicated differences in hospitals accounted for nearly half or more of medical cost variation among older adults suffering a fall-related hospitalization. Nonmetropolitan residence, being aged 65-69 (versus older), and higher risk-of-mortality on admission indicated higher costs. Identifying trends of fall-related hospitalizations over time allows for key stakeholders to not only track the burden of falls among older adults but to also use this information to attract funding for fall prevention strategies from policy makers at various levels (e.g., locally, at the state). Further, identifying characteristics of individuals (e.g., age, race, sex) and places (e.g., rural areas) that carry a higher relative cost can serve to inform the targeted allocation of finite resources including local, state, or federal funding, but also existing evidence-based practices such as community and clinical interventions.