ArticleJAMA network open2020
Evaluation of Neighborhood Socioeconomic Characteristics and Advance Care Planning Among Older Adults.
Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Health Atlas: Tutorial of a Visualization Tool and Data Resource for Place-Based Social and Structural Determinants of Health.Journal of medical Internet research · 2026Article
- Advance Directive Completion Among Community-Dwelling Adults with Decompensated Cirrhosis.Digestive diseases and sciences · 2026Article
- Community-based health-focused longitudinal aging studies in East and Southeast Asia: landscape and future directions.The Lancet regional health. Western Pacific · 2026Review
- Effect of nurse-led enhanced recovery care program on short-term postoperative outcomes of older patients undergoing lumbar fusion surgery.BMC surgery · 2026Article
- Participant Perceptions of a Trauma-Informed Advanced Care Planning Intervention: A Qualitative Study.Journal of palliative medicine · 2026Article
- Enhancing Advance Directive Completion Among Older Adults in the Geriatrics Clinic in Indiana, USA: A Quality Improvement Initiative.Healthcare (Basel, Switzerland) · 2025Article
- Advance Care Planning Motivators Among Adults With Serious Illness.JAMA network open · 2025Article
- Decomposition and comparative analysis of urban-rural disparity in attitude towards advance care planning among Chinese adults: A nationwide study.BMC public health · 2025Article
- Acceptance level of advance care planning and its associated factors among the public: A nationwide survey.BMC palliative care · 2024Article
- Life-Stage and Contextual Factors of Advance Care Planning Among Older Adults With Limited Income.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2024Article
- Area Socioeconomic Status is Associated with Refusal of Recommended Surgery in Patients with Metastatic Bone and Joint Disease.Annals of surgical oncology · 2024Article
- Using the Age-Friendly Environment Framework to Assess Advance Care Planning Factors Among Older Adults With Limited Income: A Cross-Sectional, Descriptive Survey Study.The Gerontologist · 2024Article
- End-of-Life Planning and the Influence of Socioeconomic Status among Black Americans: A Systematic Review.Journal of hospice and palliative care · 2024Article
- Article
- Online Forums as a Tool for Broader Inclusion of Voices on Health Care Communication Experiences and Serious Illness Care: Mixed Methods Study.Journal of medical Internet research · 2023Article
- Neighborhood-Level Socioeconomic Status and Prescription Fill Patterns Among Patients With Heart Failure.JAMA network open · 2023Article
- "At the End I Have a Say": Engaging the Chinese Community in Advance Care Planning.Journal of pain and symptom management · 2023Article
- Quality and Satisfaction With Advance Care Planning Conversations Among English- and Spanish-Speaking Older Adults.Journal of palliative medicine · 2023Article
- "Advocating for what we need": A CBPR approach to advance care planning in the Latinx older adult community.Journal of the American Geriatrics Society · 2023Article
- "We've Got to Bring Information to Where People Are Comfortable": Community-Based Advance Care Planning with the Black Community.Journal of general internal medicine · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Importance: Advance care planning (ACP) is low among older adults with socioeconomic disadvantage. There is a need for tailored community-based approaches to increase ACP, but community patterns of ACP are poorly understood. Objective: To examine the association between neighborhood socioeconomic status (nSES) and ACP and to identify communities with both low nSES and low rates of ACP. Design, Setting, and Participants: This cross-sectional study examined University of California San Francisco electronic health record (EHR) data and place-based data from 9 San Francisco Bay Area counties. Participants were primary care patients aged 65 years or older and living in the San Francisco Bay Area in July 2017. Statistical analysis was performed from May to June 2020. Exposures: Patients' home addresses were geocoded and assigned to US Census tracts. The primary factor, nSES, an index combining area-level measures of income, education, poverty, employment, occupation, and housing or rent values, was divided into quintiles scaled to the distribution of all US Census tracts in the Bay Area (Q1 = lowest nSES). Covariates were from the EHR and included health care use (primary care, outpatient specialty, emergency department, and inpatient encounters in the prior year). Main Outcomes and Measures: ACP was defined as a scanned document (eg, advance directive), ACP Current Procedural Terminology code, or ACP note type in the EHR. Results: There were 13 104 patients included in the cohort-mean (SD) age was 75 (8) years, with 7622 female patients (58.2%), 897 patients (6.8%) identified as Black, 913 (7.0%) as Latinx, 3788 (28.9%) as Asian/Pacific Islander, and 748 (5.7%) as other minority race/ethnicity, and 2393 (18.3%) self-reported that they preferred to speak a non-English language. Of these, 3827 patients (29.2%) had documented ACP. The cohort was distributed across all 5 quintiles of nSES (Q1: 1426 patients [10.9%]; Q2: 1792 patients [13.7%]; Q3: 2408 patients [18.4%]; Q4: 3330 patients [25.4%]; Q5: 4148 patients [31.7%]). Compared with Q5 and after adjusting for health care use, all lower nSES quintiles showed a lower odds of ACP in a graded fashion (Q1: adjusted odds ratio [aOR] = 0.71 [95% CI, 0.61-0.84], Q2: aOR = 0.74 [95% CI, 0.64-0.86], Q3: aOR = 0.81 [95% CI, 0.71-0.93], Q4: aOR = 0.82 [95% CI, 0.72-0.93]. A bivariable map of ACP by nSES allowed identification of 5 neighborhoods with both low nSES and ACP. Conclusions and Relevance: In this study, lower nSES was associated with lower ACP documentation after adjusting for health care use. Using EHR and place-based data, communities of older adults with both low nSES and low ACP were identified. This is a first step in partnering with communities to develop targeted, community-based interventions to meaningfully increase ACP.
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