Past Disparities in Advance Care Planning Across Sociodemographic Characteristics and Cognition Levels in the United States.
Zahra RahemiJuanita-Dawne R BacsuSophia Z ShalhoutMorteza SabetDelaram SiriziMatthew Lee SmithSwann Arp AdamsPublished in: medRxiv : the preprint server for health sciences (2024)
We aimed to examine past advance care planning (ACP) in U.S. older adults across different sociodemographic characteristics and cognition levels. We established the baseline trends from 10 years ago to assess if trends in 2024 have improved upon future data availability. We considered two legal documents in the Health and Retirement Study 2014 survey as measures for ACP: a living will and durable power of attorney for healthcare (DPOAH). Logistic regression models were fitted with outcome variables (living will, DPOAH, and both) stratified by cognition levels (dementia/impaired cognition versus normal cognition). Predictor variables included age, gender, ethnicity, race, education, marital status, rurality, everyday discrimination, social support, and loneliness. Age, ethnicity, race, education, and rurality were significant predictors of ACP (having a living will, DPOAH, and both the living will and DPOAH) across cognition levels. Participants who were younger, Hispanic, Black, had lower levels of education, or resided in rural areas were less likely to complete ACP. Examining ACP and its linkages to specific social determinants is essential to understanding disparities and educational strategies needed to facilitate ACP uptake among different population groups. Accordingly, this study aimed to examine past ACP disparities in relation to specific social determinants of health and different cognition levels. Future studies are required to evaluate whether existing disparities have improved over the last 10 years when 2024 data is released. Addressing ACP disparities among diverse populations, including racial and ethnic minorities with reduced cognition levels, is crucial for enhancing health equity and access to care.
Keyphrases
- healthcare
- mild cognitive impairment
- social support
- white matter
- mental health
- public health
- advance care planning
- depressive symptoms
- quality improvement
- multiple sclerosis
- electronic health record
- affordable care act
- risk assessment
- health information
- machine learning
- cross sectional
- cognitive impairment
- big data
- current status
- pain management
- artificial intelligence