01/ Dynamic Heat-Risk Scoring Per Patient – FQHCs lacked a single source of truth. Patient records were spread across EHRs, manual logs, and Medicaid systems, making care coordination inefficient. TechVariable deployed SyncMesh to harmonize data pipelines as well as clean, standardize, and store usable patient profiles for clinical workflows.
02/ Suboptimal Chronic Disease Management – Patients with hypertension, diabetes, and COPD weren’t being consistently followed up due to lack of structured disease plans and alerting systems. TechVariable introduced customizable disease management plans, allowing FQHCs to create patient-specific protocols including screenings, lifestyle tracking, medication alerts, and referrals.
03/ Limited Insight into Care Gaps – FQHCs could not easily identify patients overdue for screenings or vaccinations. Using our RAG agent accelerator, the team deployed ML-based cohort creation for risk stratification and surfaced unscreened patients directly within dashboards, allowing for phone follow-ups, intervention scheduling, and timely reimbursements.
01/ Medicaid-Focused Cohorting – With AI models trained on a blend of clinical data and social determinants (e.g., income, zip code, education levels), TechVariable’s cohorting engine formed meaningful patient groups. These groups were prioritized for screenings and wellness checks, directly tied to reimbursement pathways for the FQHCs.
02/ Unified Dashboard for Multi-Site Oversight – The platform introduced a centralized command center showing:
HEDIS measure performance across clinics
Gaps in screenings or chronic care protocols
Drill-downs into each FQHC’s compliance trends
This visibility helped executives monitor multiple centers simultaneously and realign care teams accordingly.
03/ GenAI-Powered Clinical Alerts – Our RAG agent offered intelligent summaries and care suggestions to nurse managers, enabling non-technical users to act on gaps without waiting for IT teams or external analysts. Queries like “Show me diabetic patients with missed screenings in the past 6 months” became instantly answerable, right from the dashboard.
Through this initiative, TechVariable didn’t just improve metrics — it enabled compassionate, data-driven care for those most at risk of being overlooked. The platform supported:
FQHC teams could now dedicate more time to care, less to admin, while ensuring Medicaid compliance and revenue optimization.
Building on the success of integrating and optimizing care management across FQHCs, TechVariable is now focused on expanding the solution’s utility and adaptability across three strategic dimensions — interoperability, community health integration, and mobile care delivery. These future initiatives aim to deepen the platform’s value for Medicaid providers while reinforcing health equity across underserved communities.
01/ HIE Integrations for 360° Patient Visibility – Most FQHCs still struggle to access complete patient records across health systems. To close this gap, TechVariable is integrating the platform with regional and state-level Health Information Exchanges (HIEs) to:
02/ Social Determinants of Health (SDOH) Partnership Layer – To address non-clinical barriers to care (transportation, housing, food insecurity), TechVariable will enable our clients and in turn FQHCs to:
03/ Mobile Outreach & Remote Care Modules – Understanding the access limitations of Medicaid patients — especially in rural and high-need urban zones — the platform’s next frontier includes:
These features will empower care teams to extend their reach beyond clinic walls, especially in communities with low digital penetration or transportation challenges.
04/ NCQA & PCMH Aligned Performance Monitoring – TechVariable will also work with the client to evolve the reporting framework to align with:
NCQA’s Population Health Management standards
Patient-Centered Medical Home (PCMH) transformation goals
By automating audit-readiness dashboards and quality improvement metrics, FQHCs can demonstrate performance and secure certifications more efficiently.
05/ Multi-FQHC Benchmarking and Peer Learning – As more FQHCs come onboard, the platform will introduce:
This will turn the solution into a shared intelligence engine — helping FQHC networks learn from one another and elevate outcomes across geographies.
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