Evidence map›Paper›PMID 33301019›Full record

ArticleJAMA network open2020

Evaluation of Neighborhood Socioeconomic Characteristics and Advance Care Planning Among Older Adults.

Sarah Nouri, Courtney R Lyles, Anna D Rubinsky, Kanan Patel, Riya Desai, Jessica Fields, Mindy C DeRouen, Aiesha Volow, Kirsten Bibbins-Domingo, Rebecca L Sudore

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  10. 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 · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sarah NouriDivision of Palliative Medicine, Department of Medicine, University of California, San Francisco.
Courtney R LylesUCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California.
Anna D RubinskyDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Kanan PatelDivision of Geriatrics, Department of Medicine, University of California, San Francisco.
Riya DesaiUCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California.
Jessica FieldsUCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California.
Mindy C DeRouenDepartment of Epidemiology and Biostatistics, University of California, San Francisco.
Aiesha VolowDivision of Geriatrics, Department of Medicine, University of California, San Francisco.
Kirsten Bibbins-DomingoUCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California.
Rebecca L SudoreUCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California.

Funding

VARC CoreP30AG044281 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Alexander Keliimoeanu Smith · 2013 to 2026
$19.9M
Unnecessary and Harmful Medication Use in Older Adults with DementiaP01AG066605 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MELISSA Diane ALDRIDGE · 2020 to 2026
$17.7M
Mentoring Researchers in Advance Care Planning for Underrepresented Older Adults at Risk for Alzheimer’s Disease and Related Dementias and Their CaregiversK24AG054415 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI REBECCA L SUDORE · 2017 to 2026
$1.7M
NIA NIH HHS P01 AG066605NIA NIH HHS P30 AG044281
6 · The paper itself

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.

Indexed as

CensusesPatient Acceptance of Health CareSocial ClassAdvance Care PlanningAgedCaliforniaCorrelation of DataElectronic Health RecordsEthnicityFemaleHumansMaleResidence Characteristics

Identifiers

PMID33301019
PMCPMC7729427

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.