ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2024
A Framework for an Intelligent Social Engagement Support System: Identifying and Addressing Challenges at Multiple Levels to Reduce Health Disparities.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Enhancing Medicaid Social Risk Identification: Comparing Linear and Non-Linear Machine Learning Models with Expert Heuristics.IEEE International Conference on Digital Health. IEEE International Conference on Digital Health · 2026Article
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.
Funding
Abstract
Increasingly managed care organizations (MCOs) - health plans that offer covered health services through networks of healthcare providers and hospitals - are recognizing the role of social drivers of health on both health outcomes and unnecessary healthcare utilization (e.g., emergency department visits) and are taking actions. They are employing social care navigators (SCNs) and screening for social needs such as food, housing, and transportation. However, individuals with social needs can experience barriers to completing the screening and to receiving social care when referred. Additionally, the volume of people with social needs means that SCNs have high caseloads. Without guidance on how to prioritize their efforts, the people who have the highest social needs may not be identified or receive SCN support. To address the many problems, we developed a framework for an intelligent social engagement support system. This framework builds on the Health Care System domain of the National Institutes on Minority Health and Health Disparities' Health Disparities Research Framework as a foundation, leverages learning health system and community-engaged approaches, and incorporates machine learning at key points to create an adaptable, multi-level framework that is intended to have numerous positive outcomes, including reducing health disparities in socially-driven health outcomes. We discuss how we are using this framework and how we envision it could be adapted to different MCO contexts.
Indexed as
Identifiers
41726421PMC12919418What 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.