AI Preventive Care analyzes population health data, identifies at-risk patients before symptoms appear, and automatically generates personalized care recommendations—closing care gaps and improving outcomes while reducing costly emergency interventions.
47
Patients need immediate outreach
128
Due for preventive screening
1,247
Compliant & on track
Patient Robert Chen (ID: 4582) showing early markers for Type 2 Diabetes based on recent vitals and family history.
Advanced population health intelligence that transforms fragmented patient data into actionable prevention strategies—automatically identifying who needs care before they get sick.
AI Preventive Care aggregates data from EHRs, claims, labs, and patient-reported outcomes to build comprehensive risk profiles for every patient in your population. Machine learning models analyze thousands of data points to predict health events 6-12 months in advance with clinical-grade accuracy.
Unlike traditional reactive care models, our AI continuously monitors your population, automatically stratifies risk tiers, identifies care gaps against HEDIS and quality measures, and generates personalized outreach recommendations—ensuring no patient falls through the cracks.
1. Aggregate Population Data
EHR, labs, claims, social determinants
2. Analyze Risk Factors
ML models score clinical & social risks
3. Identify Care Gaps
Missing screenings & quality measures
4. Predict Health Events
Forecast adverse events before onset
5. Generate Outreach
Personalized patient communications
6. Improved Population Outcomes
Reduced costs, better care quality
Transform from reactive sick-care to proactive health management—improving outcomes while reducing total cost of care
Identify high-risk patients before acute events occur. Clients report 34% reduction in ER visits through early intervention and care gap closure.
Automatically detect missing screenings, overdue labs, and lapsed certifications. Ensure HEDIS compliance and quality measure excellence.
AI-generated personalized communications reach the right patients at the right time—reducing staff burden while increasing engagement rates by 3x.
ML models identify patients likely to develop diabetes, heart disease, or other conditions 6-12 months before onset—enabling true prevention.
Real-time dashboards show risk distribution across your entire panel. Identify trends, track outcomes, and demonstrate value to payers.
Hit quality benchmarks, reduce readmissions, and capture risk adjustment opportunities—improving financial performance in value-based contracts.
A seamless six-step intelligence workflow that transforms data into healthier populations
Connect EHRs, claims databases, lab systems, and patient portals. AI ingests structured and unstructured clinical data, social determinants, and behavioral health indicators.
Machine learning models analyze clinical history, genetic factors, lifestyle data, and social determinants to build comprehensive risk profiles for every patient.
AI continuously monitors against HEDIS measures, quality benchmarks, and clinical guidelines—automatically flagging missing screenings, overdue labs, and lapsed certifications.
Predictive models forecast likelihood of diabetes, heart failure, COPD exacerbations, and other adverse events—enabling intervention before symptoms appear.
AI drafts customized patient communications—SMS, email, or portal messages—tailored to risk level, preferred language, and communication history.
Monitor campaign effectiveness, measure clinical outcomes, and let AI learn which interventions work best for different patient populations.
Syncing Data Sources
Connected to 4 systems...
AI Processing
Analyzing 1,422 patient records for risk factors and care gaps...
Five integrated views that transform population health management from reactive to predictive
47
High Risk
128
Medium Risk
312
Low Risk
935
Healthy
Everything you need to know about AI Preventive Care
Our AI models achieve 85-92% accuracy in predicting diabetes onset, heart failure admissions, and COPD exacerbations 6-12 months in advance. Models are trained on over 10 million patient encounters and continuously validated against outcomes. Each prediction includes a confidence score so providers can prioritize high-confidence alerts.
Yes, AI Preventive Care integrates seamlessly with Epic, Cerner, athenahealth, and most major EHRs via HL7 FHIR APIs. Data syncs bidirectionally—clinical data flows into our AI engine, and risk scores, care gaps, and recommendations appear directly in your EHR interface or Healeo dashboard.
All data is encrypted at rest (AES-256) and in transit (TLS 1.3). We are HIPAA compliant, SOC 2 Type II certified, and HITRUST certified. Patient data is never used to train general AI models—each client's data remains isolated in their secure environment. Complete audit logs track all AI recommendations and access.
Absolutely. While our base models are pre-trained on diverse populations, they adapt to your specific patient demographics, geographic factors, and social determinants within 30-60 days of deployment. Enterprise clients can also define custom risk factors and thresholds specific to their value-based contracts or clinical protocols.
Most clients see measurable improvements in care gap closure rates within 30 days, and clinical outcome improvements (reduced ER visits, better HbA1c control) within 90 days. Full ROI, including value-based contract bonuses and reduced total cost of care, typically manifests within 6-12 months. We provide dedicated customer success support to ensure rapid value realization.
No—AI Preventive Care augments your care team. It handles the data analysis, risk stratification, and initial outreach at scale, allowing your coordinators to focus on high-touch interventions for the patients who need it most. Clients report their care coordinators become 3x more effective when armed with AI-prioritized patient lists and recommended interventions.
See how AI Preventive Care can reduce ER visits by 34% and close critical care gaps across your patient population.
No credit card required • 14-day free trial • Full feature access