Precision Ecologic Medicine: Integrating Community Vital Signs into Electronic Medical Records to Address Climate Change's Health Impacts

The paper addresses how climate change–induced extreme weather events disproportionately harm frontline communities due to historical and current structural inequities, resulting in greater morbidity and mortality. Social and environmental determinants—such as where people live and work—are shown to influence health outcomes as much or more than medical care or genetics. Current U.S. healthcare systems lack the capability and motivation to tailor care based on patients’ environmental exposures, having focused more on precision medicine and genetics. The authors propose advancing toward “precision ecologic medicine,” embedding geocoded community, ecological, and environmental data (“community vital signs”) into electronic medical records (EMRs) to guide tailored care, referrals, and responses to climate-related events, thereby improving equity and outcomes for those most at risk.

• Concept proposal: Precision ecologic medicine would integrate geocoded community vital signs (e.g., heat exposure, air quality, tree canopy, housing/building characteristics, access to heating/cooling and safe water, crime rates, demographics, walkability, proximity to services) into EMRs to personalize care, referrals, and services.
• Clinical utility: Tailored care teams (e.g., community health workers, navigators, behavioral health specialists) and prescriptions/referrals (e.g., air conditioners/purifiers, heat pumps, transportation, interpretation, cooling centers) can be guided by contextual data and automated decision support.
• Feasibility: EMR platforms and geospatial technologies now allow integration of publicly available community data with lower investment than genomic integration. Federal meaningful use and NASEM recommendations already support capturing social determinants; the authors advocate extending this to climate-related risk data. Payers should consider covering climate-mitigating interventions.
• Primary care focus: Primary care—being the largest delivery platform and central connector to community resources—should be the primary site of investment for deploying precision ecologic medicine and responding to climate events.
• Data portal vision: A community vital signs data portal would automate embedding geo-referenced data into EMRs, enabling clinical decision support, panel management, community referrals, and rapid response to climate events.
• Workforce preparation: Training curricula in medicine, nursing, and residencies are increasingly integrating climate-health education to prepare clinicians for climate adaptation and disaster preparedness.
• Beyond individual care: Healthcare systems can contribute EMR data to population-level surveillance and resilience planning (e.g., Oregon ESSENCE) to proactively protect high-risk communities during events like wildfires, heat waves, and flooding.
• Health system sustainability: Healthcare contributes roughly 7% of U.S. greenhouse gas emissions; green initiatives to reduce waste and pollution in healthcare are necessary alongside precision ecologic medicine.
• Expected impact: Integrating contextual data can mitigate climate-related health impacts, reduce disparities, and potentially lower healthcare costs by reducing disease burden in frontline communities.

Embedding community vital signs into EMRs directly addresses the gap between patients’ environmental risks and clinical decision-making. By providing actionable, geo-referenced context at the point of care, clinicians can tailor prevention, treatment, and referrals, especially for patients in urban heat islands or areas with poor air quality. Automated clinical decision support tied to best practices can prompt timely interventions (e.g., equipment prescriptions, education for extreme heat or wildfire smoke) and facilitate navigation to enabling services. At the population level, combining EMR and community data via geospatial platforms supports surveillance and resource allocation for climate adaptation, guiding policymakers and community leaders to invest in interventions where socio-environmental and medical risks are highest. Training health professionals in climate-health competencies and aligning payment policies to cover climate-mitigating care components are essential to operationalizing this approach, with primary care serving as the central implementation hub.

Socioeconomic and environmental risks substantially influence health outcomes and disproportionately burden frontline communities facing climate change. Precision ecologic medicine—integrating community-level contextual data into EMRs—offers a pathway to personalize care, proactively mitigate climate-related health harms, and reduce inequities. As climate-driven extreme events intensify in coming decades, deploying these interventions will be critical to population health and may alleviate cost pressures by lowering disease burden. Achieving this vision requires clear strategy, technological infrastructure, payment support, healthcare transformation, expanded training, and strong partnerships between primary care teams and community organizations. Without these elements, health systems will fall short in meeting the needs of patients and communities amid escalating climate threats.

• The article is a conceptual commentary without primary empirical evaluation of outcomes for precision ecologic medicine.
• Implementation requires substantial resources, stakeholder coordination, and workflow redesign within EMRs, which may be challenging for underfunded primary care settings.
• Few EMRs currently present climate-related risk information; standardization and data governance for integrating diverse geospatial/contextual datasets remain unresolved.
• Success depends on payer policies to cover climate-mitigating interventions and on widespread workforce training, which may vary across institutions and regions.