Policy Points Federal interoperability networks transport standardized clinical data but do not aggregate, enrich, or analyze the state‐governed data that clinical practice, public health, and Medicaid administration require locally. State‐designated health data utilities fill this structural gap through a cooperative federalism architecture in which states build and operate local data infrastructure and the federal government provides regulatory flexibility and financial incentives. The One Big Beautiful Bill Act requires states to implement twice‐yearly redeterminations beginning in 2027, creating a unified enforcement cycle that no existing infrastructure can absorb at scale. The health data utility offers the most administratively viable architecture for preventing catastrophic procedural disenrollments as state budgets contract. A four‐layer financing model distributes financial risk across state general funds, Medicaid enhanced matching, payer enrichment revenue, and value‐based payment integration. Federal action should formalize a health data utility profile within the Trusted Exchange Framework and Common Agreement and confirm enhanced Medicaid matching for shared infrastructure. Context Federal interoperability initiatives like Trusted Exchange Framework and Common Agreement transport clinical records across boundaries but fail to aggregate and enrich state‐governed datasets, including Medicaid claims, prescription monitoring records, and social service registries. This fragmentation creates fiscal and administrative liability for states, exacerbated by the One Big Beautiful Bill Act's mandate for twice‐yearly Medicaid redeterminations and work verifications beginning in 2027 amidst tightening state budgets. Methods Synthesizing health information exchange literature, existing state operational models (Maryland, Indiana, California, North Carolina), and federal statutory requirements, we propose a cooperative federalism governance model, technical data architecture, and multi‐payer financing strategy for state‐designated health data utilities (HDUs). Findings We propose an HDU architecture that can be adapted across multiple states, designed to directly advance clinical care delivery by functioning as an enrichment layer integrated natively into electronic health record workflows. By synthesizing longitudinal clinical encounters, controlled substance histories, claims, and social needs registries in real time, the proposed utility would deliver actionable predictive risk scores and automated point‐of‐care alerts to prevent avoidable readmissions, curtail redundant advanced imaging, and coordinate cross‐sector interventions for high‐risk patients. Operationally, the model pairs this bedside enrichment with automated eligibility and frailty verification, ensuring high‐need individuals maintain continuous access to essential clinical services. Conclusions Clinical data fragmentation is rooted in governance silos rather than technical barriers. Establishing state‐designated HDUs through a cooperative federalism model bridges bedside clinical practice, public health, and Medicaid administration. HDUs provide the integrated infrastructure necessary to prevent clinical crises, protect vulnerable populations, and improve care delivery at scale across the United States.
Policy Points Starting in the 2000s, state governments began adopting labor market policies, including minimum wage laws, earned income tax credits, paid family and medical leave programs, paid sick leave mandates, and scheduling laws. Evidence suggests that labor market policies can improve earnings and job quality, and some are associated with improved worker health. States interested in evidence‐based policies for improving worker health should consider generous, refundable earned income tax credits; higher minimum wages tied to inflation; greater local government discretion to adopt labor market policies; and paid leave programs or mandates. Context State governments have begun to adopt labor market policies, including minimum wage laws, earned income tax credits, paid family and medical leave programs, paid sick leave mandates, and scheduling laws. The presence (or absence) of these laws can affect the health and well‐being of workers. Methods A review of the existing literature. Findings Emerging evidence indicates that state government actions to increase earnings for those in low‐wage jobs and to improve their job quality can lead to better health. Conclusions Encouraging findings in the literature strongly suggest that policymakers should continue to advance state‐level labor market policies to improve the health outcomes of workers, as well as support efforts by researchers to assess their impact on health.
Policy Points From 2011‐2023, US children's health deteriorated across >170 indicators. Chronic conditions rose from 25.8% to 31%, risk of anxiety tripled, and autism and learning disability more than doubled. Policies based on biomedical models have failed to address these trends. Life course models regard health as a developmental process, with mismatches between children's physical, nutritional, and relational environments and the ones they are evolutionarily calibrated to expect as likely drivers of declining health. State policies can help to overcome mismatches and optimize developmental ecosystems. New Mexico is pioneering and testing an approach linking early childhood policy innovation with population‐level developmental measurement. The health of US children has deteriorated significantly across multiple indicators with trends accelerating since 2007. From 2011‐2023, the prevalence of chronic conditions among 3‐19‐year‐olds rose from 25.8 to 31%, obesity rose from 17 to 20%, and autism and learning disabilities more than doubled. Rates of anxiety, loneliness, depression, early onset of menstruation and trouble sleeping all increased. Biomedically driven policy and practice have improved treatment of certain established medical conditions (e.g., childhood cancers and congenital heart disease), but failed to stem increasing mental health challenges, and neurodevelopmental disorders. Life course models point to fundamental changes in the early developmental ecosystem resulting in profound mismatches between the conditions children are evolutionarily primed and historically calibrated to expect and those they currently experience as primary drivers of these changes. The Industrial Revolution accelerated changes in children's physical, relational, and nutritional environments; temporal rhythms; and cognitive demands. The Digital Revolution further accelerated the speed and degree of change, potentially outpacing children's capacity for adaptive developmental responses. These multiple environmental changes do not act in isolation but interact in multilevel, dynamic, and complex ways to form the developmental ecosystems shaping children's developmental trajectories. In this paper we suggest a reorientation of child health policy and resulting interventions—expanding the focus beyond isolated social risks and behavioral deficits to address ecosystem‐level influences and shift population outcomes by altering health development trajectories. We also suggest a suite of actionable state‐level policy solutions geared to improve the configuration of these developmental ecosystems. We highlight state policy innovations such as New Mexico's comprehensive portfolio of early childhood policy changes and infrastructure upgrades along with ongoing population‐level measurement of children's health development to monitor policy impact.
Policy Points Population health science that uses large data sets to study health inequalities increasingly draws on intersectionality, the idea that overlapping forms of disadvantage shape health inequalities. This approach is essential to the pursuit of health equity because it provides a more complete and sound evidence base for population health policy. As this approach has gained traction, it has drifted from intersectionality's founding ideas about social power and justice. This Perspective develops a framework of justice for the field that consists of a multidimensional account of unjust power relations and an egalitarian standard to guide population health research and interventions. Context Research that examines multiple forms of marginalization simultaneously, referred to herein as quantitative intersectional analysis, is an important trend in population health science. This approach can identify otherwise hidden health inequalities and a fuller array of social drivers, creating a more complete evidence base for intervention. The practice of quantitative intersectional analysis, however, has strayed from intersectionality's founding ideas about interconnecting power relations and social justice. Some researchers have called for the rebuilding of those connections. Methods This Perspective interprets and adapts key features of Nancy Fraser's critical theory with the aim of developing a framework of justice and illustrating its value as an ethical resource for quantitative intersectional analysis and population health policy. [Correction added on 21 October 2026, after first online publication: The word “adapt” was changed to “adapts” in this Methods section] Findings The proposed framework is well suited to quantitative intersectional analysis in three respects. First, it's critical vantage point foregrounds precisely the kinds of power relations and social structures that are well‐documented drivers of health inequalities, including maldistribution in economic relations, misrecognition in cultural relations, and misrepresentation in political relations. Second, the framework is adaptable and can be extended, as recommended here, to include care relations. Third, the framework articulates a positive standard of justice—participatory parity—that can be interpreted to provide both moral justification for the view that some health inequalities constitute health inequities and ethical guidance for population health policy. Conclusions The proposed framework of justice supports deep engagement with ideas about social power and justice in four ways. It expands the social categories and systems of inequality typically subject to analysis, enhances conceptual clarity and theorization about the nature of the harms under study, identifies health inequalities that merit investigation, and provides an ethical standard for population health policy that protects against the use of stigmatization as a policy tool and supports a broad and inclusive concept of health equity.
Policy Points Primary care, when done well, is the country's most cost‐effective solution to runaway costs and widening health outcome gaps. Primary care is increasingly starved for resources, with associated reductions in relational continuity and comprehensiveness that collectively increase the risk of losing patient trust. The 2021 National Academies of Sciences, Engineering, and Medicine report, Implementing High‐Quality Primary Care: Rebuilding the Foundation of Health Care , supported a cascade of federal initiatives to strengthen, coordinate, and create accountability for primary care strategies, and although several derailed, they remain options for improving health and health care. The 2021 National Academies of Sciences, Engineering, and Medicine report, Implementing High‐Quality Primary Care: Rebuilding the Foundation of Health Care , spurred a cascade of federal payment, access, and accountability initiatives, but inconsistent federal leadership has derailed several of them. Congressional and HHS health goals would benefit from reviving stalled primary care infrastructure projects, establish outcome accountability for graduate medical education investment, and build on state models in Maryland, Rhode Island, Vermont, and California. Context Primary care is the foundation of a high‐functioning health system, yet it has been weakened for decades, and the consequences for patients, population health, and costs are increasingly apparent. The 2021 National Academies of Sciences, Engineering, and Medicine (NASEM) report offered 16 recommendations across five objectives for rebuilding primary care through payment, access, workforce training, health information technology, and accountability. Methods This Perspective reviews federal and state policy developments since the NASEM report against its five‐objective framework, examining payment demonstration models, minimum primary care spend legislation, graduate medical education financing, and federal data infrastructure initiatives to assess where reform has taken hold, stalled, or been abandoned amid shifting administration priorities. Findings Partial payment successes, including the Advanced Primary Care Management code, the AHEAD model, and minimum‐spend policies in nearly a dozen states, demonstrate that reform is feasible. Yet inconsistent federal leadership has undermined progress: the Making Care Primary model was abruptly terminated, and several near‐complete Agency for Healthcare Research and Quality initiatives—a primary care dashboard, Healthcare Extension Cooperatives, and a clinician/practice database—were lost amid the agency's proposed dissolution. Meanwhile, cuts to Affordable Care Act subsidies and Medicaid threaten to disrupt care for millions and widen mortality gaps. States are increasingly serving as policy laboratories, with Maryland, Rhode Island, Vermont, and California offering replicable models for payment and accountability reform. Conclusions The technical solutions needed to strengthen primary care largely already exist. What is missing is durable, coordinated federal and state investment paired with accountability. Securing primary care's future requires treating it as essential public infrastructure.
