Turning Compliance Into Action: An Augmented Intelligence–Enabled Framework for Advocacy Organizations to Drive Population Health Improvement.
Community Health Needs Assessments (CHNAs), mandated by the Affordable Care Act for tax-exempt hospitals, represent an underutilized yet rich data source for disease-specific advocacy. This commentary proposes a novel framework in which disease advocacy organizations—such as Alzheimer's Los Angeles,...
| Publicado en: | Population Health Management Vol. 29; no. 5; pp. 340 - 345 |
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| Autor principal: | |
| Formato: | Journal Article |
| Publicado: |
Mary Ann Liebert, Inc.
Oct2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=196416177&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 196416177 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 19427891 8765 jtl: Population Health Management issn: 19427891 maglogo: N pubinfo: dt: Oct2026 vid: 29 iid: 5 pid: 1365 pub: Mary Ann Liebert, Inc. place: New Rochelle, New York artinfo: ui: 196416177 196416177 196416177 10.1177/19427891261450800 196416177 ppf: 340 ppct: 5 formats: tig: atl: Turning Compliance Into Action: An Augmented Intelligence–Enabled Framework for Advocacy Organizations to Drive Population Health Improvement. aug: au: Stefanacci, Richard G. affil: College of Population Health, Thomas Jefferson University, Philadelphia, Pennsylvania, USA. sug: subj: Population Health Artificial Intelligence Community Health Services Needs Assessment Accountability Quality Improvement Organizational Compliance Dementia Alzheimer's Disease Data Collection Methods Natural Language Processing Ethics, Medical Hospitals Health Services Needs and Demand ab: Community Health Needs Assessments (CHNAs), mandated by the Affordable Care Act for tax-exempt hospitals, represent an underutilized yet rich data source for disease-specific advocacy. This commentary proposes a novel framework in which disease advocacy organizations—such as Alzheimer's Los Angeles, the American Heart Association, and the National Alliance on Mental Illness—deploy artificial intelligence (AI) agents to systematically analyze CHNAs, identify gaps in condition-specific care, generate personalized outreach to hospital leadership, and publicly score health systems on their responsiveness to identified needs. Using Alzheimer's disease and dementia care in Los Angeles County as a primary case example, this article describes how AI-driven automation of data collection, natural language processing of CHNA documents, and coordinated advocacy campaigns can transform the current passive CHNA cycle into an active mechanism for population health improvement. The framework combines reputational accountability through public scorecards with constructive, evidence-based recommendations, creating a "carrot-and-stick" dynamic that existing literature on public performance reporting suggests can achieve engagement rates of 40%–70% and meaningful institutional change in 30%–60% of targeted systems. This approach is adaptable across chronic conditions and disease advocacy organizations, wherever publicly reported community needs data intersect with organized patient advocacy. Implications for population health management, health system quality improvement, and the responsible integration of AI in public health advocacy are discussed. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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