Evidence-driven data science for public health innovation and policy impact.
R2ML delivers rigorous epidemiological analysis, advanced machine learning, and real-world evidence (RWE) to federal, state, and local public health agencies. We transform complex healthcare data into actionable insights that drive policy, improve outcomes, and save lives.
With 15+ years of experience in health data science, we partner with public health systems, government agencies, and health organizations to solve the most pressing epidemiological and health services challenges facing communities today.
R2ML is a specialized health data science organization with deep expertise in epidemiology, real-world evidence analytics, and health services research. Our team brings together biostatisticians, epidemiologists, data engineers, and health policy experts with extensive experience in military health systems, public health surveillance, behavioral health research, and health policy evaluation.
We operate at the intersection of academic rigor and practical application, delivering solutions that bridge research methodology with implementation science. Our work directly informs policy decisions, improves clinical operations, and drives measurable impact across healthcare delivery systems.
Design and audit public health surveillance systems. Conduct epidemiologic studies on disease patterns, injury prevention, and population health trends.
Transform EHR, claims, and registry data into actionable insights. Analyze healthcare utilization, patient outcomes, and health disparities.
Develop risk stratification models, disease prediction algorithms, and machine learning solutions for population health management.
Quantify the effectiveness of public health policies, clinical guidelines, and health system interventions using rigorous causal inference methods.
Analyzed comorbidity patterns across 41 conditions in 250K+ TBI patients, identifying prescribing gaps and establishing MHS-wide clinical operations metrics that improved care coordination across 51 hospitals.
Developed machine learning models achieving 15% improvement in risk stratification for high-cost chronic disease populations by integrating social determinants of health with claims data.
Designed and deployed real-time dashboards for nation's 2nd largest health system, accelerating deployment by 50% and enabling continuous monitoring of 11.2M service members' health metrics.
Quantified measurable policy effects: helmet laws reducing TBI hospitalizations 12% across 40 states; in-person licensing reducing dementia-related crashes by 37-38%.
Conducted population-level incidence analysis of 1.9M+ person-years of surveillance data, identifying 91% higher TBI incidence in deployed vs. non-deployed military settings.
Built centralized data warehouse integrating 6+ military health databases, reducing query time by 500% and enabling standardization of 10+ data streams across the MHS.
R2ML delivers evidence-driven solutions to federal, state, and local health organizations across multiple sectors:
DoD, VA, HHS, CDC, AHRQ
Public health departments, health agencies
Integrated delivery networks, hospitals
Universities, research centers
Management consulting, health services
Real-world evidence generation
We apply rigorous epidemiological methodology, advanced statistical techniques, and peer-reviewed best practices to ensure validity and reproducibility of our analyses.
We translate complex analyses into clear, actionable recommendations that inform policy decisions, operational improvements, and clinical initiatives.
We maintain strict HIPAA compliance, secure Data Use Agreements, and implement robust data governance to protect sensitive health information.
We work closely with clinical teams, administrators, and policy makers to ensure our solutions align with organizational needs and drive sustainable impact.
Partner with R2ML to drive evidence-based health innovation.
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