Healthcare Application Maintenance Case Study | Orthopedic Care
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Read Case StudyHow a U.S.-based nonprofit community health network used AI consulting, generative AI, referral intelligence, and workflow automation to route patient referrals faster, reduce manual eligibility review, prioritize outreach, and give program leaders clearer visibility into patient-navigation workloads and community health programs.
The client is a regional nonprofit community health network supporting uninsured and underserved patients through primary-care access, chronic-care navigation, preventive screening programs, maternal-health support, behavioral-health referrals, transportation assistance, and community resource coordination.
Patient referrals arrived from clinics, community partners, outreach events, web forms, call-center teams, and social-service organizations. Eligibility information, outreach history, care-navigation notes, appointment status, and program data were spread across the CRM, EHR-connected workflows, spreadsheets, email, and reporting tools. Navigators spent too much time assembling context before they could support the patient.
JanBask designed and deployed CAREBRIDGE AI β a nonprofit healthcare intelligence solution combining generative AI, referral classification, governed knowledge retrieval, workflow automation, and program analytics. It helps navigation teams understand referral context faster, identify incomplete information, prioritize outreach, and surface program insights while keeping patient-support and clinical decisions in human hands.
A governed AI assistant that lets patient navigators ask questions about referral status, prior outreach, program requirements, missing information, and approved community resources in plain English β with responses grounded in authorized data.
AI classifies incoming referrals by program, service need, completeness, urgency indicators, referral source, and next-step requirements so navigation teams can route administrative work faster while preserving human review.
Combines referral details with approved program criteria to flag likely matches, missing eligibility information, and documentation gaps before a navigator completes the final eligibility review.
Summarizes open referrals, outreach attempts, pending documents, appointment status, and overdue follow-ups so navigation teams can prioritize work without manually reviewing every record.
Analyzes referral age, missed outreach, appointment status, and program activity to surface administrative follow-up gaps for navigator review β without making clinical diagnoses or treatment decisions.
Connects CRM, EHR-linked data, partner referrals, outreach workflows, and reporting tools so authorized teams can work from a more consistent operational view of patient-navigation activity.
Performance was measured against pre-implementation patient-navigation workflows, including referral review, eligibility checks, navigator assignment, follow-up prioritization, and program reporting.
An enterprise-grade AI and data architecture designed for nonprofit healthcare, governed information retrieval, referral workflows, patient-navigation operations, secure data access, program analytics, and scalable community-health support. AI outputs were designed to support administrative and navigation workflows β not replace licensed clinical judgment or patient-care decisions.
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