ArticleThe Permanente journal2020
The Application of Community-Based Information from the American Community Survey in a Large Integrated Health Care Organization.
Article in The Permanente journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Social Risk Phenotypes Are Strongly Associated With Hepatocellular Carcinoma Outcomes: A Statewide Cohort Study Using Latent Class Analysis.Clinical and translational gastroenterology · 2026Article
- Associations of Place-Based Factors with Service Use and Consumer-Reported Unmet Service Needs Among Older Adults Using Publicly Funded Home- and Community-Based Services in the United States.International journal of environmental research and public health · 2025Article
- Symptoms of Asthma Extracted Through Natural Language Processing and Their Associations With Acute Asthma Exacerbation in Adults With Mild Asthma.The journal of allergy and clinical immunology. In practice · 2025Article
- Fracture risk by cortisol excess status in patients with adrenal incidentalomas: a population-based cohort study.JBMR plus · 2025Article
- Neighborhood Deprivation and Crime on Asthma Exacerbations and Utilization in Mild Adult Asthma.The journal of allergy and clinical immunology. In practice · 2024Article
- A machine-learning prediction model to identify risk of firearm injury using electronic health records data.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Risk Factors for Acute Asthma Exacerbations in Adults With Mild Asthma.The journal of allergy and clinical immunology. In practice · 2024Article
- National Trends in the Incidence of Sporadic Malignant Colorectal Polyps in Young Patients (20-49 Years): An 18-Year SEER Database Analysis.Medicina (Kaunas, Lithuania) · 2024Article
- Research data warehouse: using electronic health records to conduct population-based observational studies.JAMIA open · 2023Article
- A Multi-Level Analysis of Individual and Neighborhood Factors Associated with Patient Portal Use among Adult Emergency Department Patients with Multimorbidity.International journal of environmental research and public health · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe American Community Survey (ACS) is the largest household survey conducted by the US Census Bureau. We sought to describe the community-level characteristics derived from the ACS among enrollees of Kaiser Permanente Southern California (KPSC), evaluate the associations between ACS estimates and selective individual-level health outcomes, and explore how using different scales of the census geography and the linearity assumption affect the associations.
methodsWe examined the associations between track-level and block group-level ACS 5-year estimates and 4 individual-level Healthcare Effectiveness Data and Information Set (HEDIS) outcome measures (comprehensive diabetes care, postpartum care, antidepressant medication management, and childhood immunization status) using multilevel generalized linear models. Odds ratios and their 95% confidence intervals were estimated for every 10% increase in ACS measures.
results6,357,841 addresses were successfully geocoded to at least the tract level. The community-level demographic, socioeconomic, residential, and other ACS measures varied among KPSC health plan enrollees. A majority of these ACS measures were associated with the selected HEDIS health outcomes. The directions of the effects were consistent across health outcomes; however, the magnitudes of the effect sizes varied. Within each HEDIS health outcome, the relative size of the effects appeared to remain similar. Differences between the census tract- and block group-level estimates were minor, especially for measures related to race/ethnicity, education, income, and occupation.
conclusionThese findings support the use of many ACS measures at neighborhood levels to predict health outcomes. The geographic units might have little effect on the results. The linearity assumption should be made with caution.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.