AI in Primary Care: Bridging Access Gaps with Intelligent Triage

Mass General Brigham’s AI-supported Care Connect program has launched an AI screening and routing system that triages symptom reports, directs patients to virtual‑first visits, and routes referrals to in‑person care to address primary care shortages and accelerate access.

The system replaces manual intake with structured digital symptom collection and algorithmic routing to appropriate visit types, aiming to relieve scheduling backlogs while preserving clinician oversight. Care Connect intends to shorten time‑to‑evaluation for urgent primary care needs and improve front‑line access pathways; measurable outcomes such as wait times, same‑day visit rates, and virtual‑resolution rates should be tracked to confirm real‑world impact.

Traditional phone-based appointment triage depends on scheduler judgment; AI-enabled screening automates symptom intake, generates a clinician‑facing summary, and routes patients to virtual encounters or in‑person referrals based on preset pathways. This shifts part of the workload from scheduling teams to virtual clinicians and centralized intake staff—a reallocation of scarce human resources toward higher‑acuity visits at a time of workforce constraints and rising telehealth demand.

The program is designed to manage common urgent problems and mild‑to‑moderate mental‑health concerns with remote clinician review and 24/7 access to care recommendations and clinician‑mediated follow‑up. Those features aim to ease clinic scheduling bottlenecks and reduce pressure on primary care panels. Systems deploying this model typically report—or aim for—shorter waits, higher virtual‑resolution rates, and improved triage accuracy for directing patients to the right level of care, shifting patient flow toward virtual channels during peak demand and decreasing routine scheduling strain on in‑person panels.

Key operational and ethical considerations for deployment include EHR integration and single‑sign‑on for clinicians; explicit clinician oversight with clear escalation paths to in‑person or specialty care; ongoing monitoring for algorithmic bias and equity across patient subgroups; robust data governance and privacy safeguards; and a defined metric set for continuous evaluation covering access, safety, continuity, and equity.

Key Takeaways:

• AI-enabled triage programs are being used as front‑door filters to route patients to virtual‑first or in‑person care.
• Who’s affected: Primary care panels, access managers, and patients seeking urgent primary care or mental‑health support.
• Systems will need to pair AI triage with EHR integration, explicit escalation protocols, and equity monitoring before broad rollout.