Epidemiology of public transportation use among older adults in the United States.

BACKGROUND: Attending healthcare appointments and participating in social activities are important for older adults, but these activities are often limited by transportation barriers. Public transportation may bridge these gaps, but little is known about older public transportation users. This study compares the characteristics of older adults who use public transportation to those who do not. DESIGN: Cross-sectional analysis of data from Round 5 of the National Health and Aging Trends Study (NHATS). We identified 5696 urban community dwelling older adults, and calculated national estimates of those who reported public transportation use in the last month and those who used transit to see their regular doctor. We evaluated the age and sex-adjusted associations between economic and clinical characteristics and recent use of public transportation using survey-weighted logistic regression. RESULTS: Nearly 1 in 10 (n = 555/5696, weighted n = 3,122,583) urban-dwelling older adults in the United States reported use of public transportation in the last month, and over 20% of users (weighted n = 658,850) relied on transit to see their regular doctor. Compared to non-users, those who reported using transit were significantly more likely to be younger and identify as non-Hispanic Black or Hispanic. Financially strained older adults were more likely to have recently relied on public transportation (adjusted odds ratio [aOR] 1.62, 95% confidence interval [CI] 1.07-2.44), but frailty (aOR = 0.61, 95% CI 0.41-0.91) and living in an area with cracked or broken sidewalks (aOR = 0.35, 95% CI 0.27-0.46) were both associated with lower odds of public transportation use. CONCLUSION: More than 3 million older adults in the United States reported recently using public transportation, with over 600,000 relying on these services to visit their doctor. With increasing investment in public infrastructure on the horizon, centering the unique medical, economic, and social needs of older transit users is critical to ensure urban communities remain age-friendly.

A review of caregiver costs included in cost-of-illness studies.

INTRODUCTION: Economic evaluations typically focus solely on patient-specific costs with economic spillovers to informal caregivers less frequently evaluated. This may systematically underestimate the burden resulting from disease. AREAS COVERED: Cost-of-illness (COI) analyses that identified costs borne to caregiver(s) were identified using PubMed and Embase. We extracted study characteristics, clinical condition, costs, and cost methods. To compare caregiver costs reported across studies, estimated a single 'annual caregiver cost' amount in 2021 USD. EXPERT OPINION: A total of 51 studies met our search criteria for inclusion with estimates ranging from $30 - $86,543. The majority (63%, 32/51) of studies estimated caregiver time costs with fewer studies reporting productivity or other types of costs. Caregiver costs were frequently reported descriptively (69%, 35/51), with fewer studies reporting more rigorous methods of estimating costs. Only 27% (14/51) of studies included used an incremental analysis approach for caregiver costs. In a subgroup analysis of dementia-focused studies (n = 16), we found the average annual cost of caregiving time for patients with dementia was $30,562, ranging from $4,914 to $86,543. We identified a wide range in annual caregiver cost estimates, even when limiting by condition and cost type.

A more practical guide to incorporating health equity domains in implementation determinant frameworks.

BACKGROUND: Due to striking disparities in the implementation of healthcare innovations, it is imperative that researchers and practitioners can meaningfully use implementation determinant frameworks to understand why disparities exist in access, receipt, use, quality, or outcomes of healthcare. Our prior work documented and piloted the first published adaptation of an existing implementation determinant framework with health equity domains to create the Health Equity Implementation Framework. We recommended integrating these three health equity domains to existing implementation determinant frameworks: (1) culturally relevant factors of recipients, (2) clinical encounter or patient-provider interaction, and (3) societal context (including but not limited to social determinants of health). This framework was developed for healthcare and clinical practice settings. Some implementation teams have begun using the Health Equity Implementation Framework in their evaluations and asked for more guidance. METHODS: We completed a consensus process with our authorship team to clarify steps to incorporate a health equity lens into an implementation determinant framework. RESULTS: We describe steps to integrate health equity domains into implementation determinant frameworks for implementation research and practice. For each step, we compiled examples or practical tools to assist implementation researchers and practitioners in applying those steps. For each domain, we compiled definitions with supporting literature, showcased an illustrative example, and suggested sample quantitative and qualitative measures. CONCLUSION: Incorporating health equity domains within implementation determinant frameworks may optimize the scientific yield and equity of implementation efforts by assessing and ideally addressing implementation and equity barriers simultaneously. These practical guidance and tools provided can assist implementation researchers and practitioners to concretely capture and understand barriers and facilitators to implementation disparities.