Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2025
Incorporating Informal Caregiving Time Into Cost-Effectiveness Analysis for Adults Aged 50 and Older: Estimating From Health-Related Quality of Life and Functional Status.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Jiao Boshen, Lu Xinran, Lakdawalla Darius N, Padula William V, Geng Fangli
Аннотация
OBJECTIVES: Informal caregiving, often provided by family and friends, is essential for supporting individuals with functional impairments. However, these caregiving costs are frequently excluded from cost-effectiveness analyses (CEAs), potentially biasing the evaluation of medical interventions dependent on informal caregiving. Although guidelines recommend including these costs in CEA from a societal perspective, implementation has been inconsistent because of limited data. To address this gap, we developed US-based models estimating informal caregiving time by linking it to health-related quality of life (HrQoL) of care recipients.
METHODS: Using data from the 2010 to 2018 waves of the Health and Retirement Study, a nationally representative survey of Americans aged 50+, we focused on individuals with limitations in activities of daily living (ADLs) or instrumental ADLs (IADLs). We performed regression analyses to estimate the association between informal caregiving time and HrQoL, developing separate models with and without ADL/IADL predictors. Additionally, we created models with both preference-based health utility scores from the Health Utilities Index Mark 3 and visual analog scale scores as the HrQoL measures.
RESULTS: The models demonstrated strong predictive accuracy based on cross-validation. Findings from the models using HrQoL as the primary predictor indicate that lower Health Utilities Index or visual analog scale scores are associated with increased caregiving time. The models incorporating the number of ADL and IADL limitations as additional predictors further highlight the growing demand for informal caregiving as functional impairments worsen.
CONCLUSIONS: These models provide practical tools to facilitate the inclusion of informal caregiving costs in US-based CEAs.
METHODS: Using data from the 2010 to 2018 waves of the Health and Retirement Study, a nationally representative survey of Americans aged 50+, we focused on individuals with limitations in activities of daily living (ADLs) or instrumental ADLs (IADLs). We performed regression analyses to estimate the association between informal caregiving time and HrQoL, developing separate models with and without ADL/IADL predictors. Additionally, we created models with both preference-based health utility scores from the Health Utilities Index Mark 3 and visual analog scale scores as the HrQoL measures.
RESULTS: The models demonstrated strong predictive accuracy based on cross-validation. Findings from the models using HrQoL as the primary predictor indicate that lower Health Utilities Index or visual analog scale scores are associated with increased caregiving time. The models incorporating the number of ADL and IADL limitations as additional predictors further highlight the growing demand for informal caregiving as functional impairments worsen.
CONCLUSIONS: These models provide practical tools to facilitate the inclusion of informal caregiving costs in US-based CEAs.