Urgent care clinicians manage a high volume of musculoskeletal presentations without on-site orthopedic expertise, immediate radiology interpretation, or a standardized MSK decision framework. AgentMSK combines deterministic clinical logic with targeted AI to deliver structured, higher-quality MSK decision support at the point of care—directly within your existing EMR.
The urgent care environment presents structural challenges that purpose-built clinical infrastructure can address.
Urgent care clinicians evaluate a wide range of MSK conditions without routine access to orthopedic or radiology expertise on site, while working within time-constrained, high-throughput environments.
Radiology reports often become available after the patient has been discharged. Clinical decisions are therefore made based on real-time interpretation of imaging without immediate specialist overread. Clinically significant findings may not be consistently captured in a timely manner.
Claims denials, under-coded E/M levels, missed physical therapy referrals, and uncaptured DME revenue represent a measurable and recoverable financial gap, all of which are dependent upon documentation completeness and consistency of clinical workflows.
AgentMSK is a structured clinical decision support platform that combines a deterministic rules engine with targeted AI capabilities, seamlessly integrated with existing EMR systems. Deterministic logic governs all safety-critical decisions. AI is applied selectively at defined points: natural-language HPI capture, plain x-ray fracture detection, differential diagnosis synthesis and documentation.
AgentMSK governs the process by which clinical decisions are made — enforcing completeness, surfacing risk, and reducing diagnostic gaps before disposition.
No safety-critical decision depends on AI. Reasoning is structured, auditable, and defensible. The deterministic foundation is not a feature — it is the architecture.
Every encounter follows a validated, evidence-based pathway. Each phase builds on a structured clinical context—ensuring complete evaluation, surfacing risk, and generating audit-ready documentation prior to patient disposition.
| Workflow Phase | Engine | Safety Gate | What It Delivers at the Point of Care |
|---|---|---|---|
|
Universal Safety Screen (USS)
|
Deterministic | Always-on | 57 binary criteria across 5 escalation levels. Runs before any clinical module loads. Routes to EMS, ATLS protocol, ED transfer, or clearance. No bypass permitted. |
|
HPI Collection + Ambient Voice Capture
|
Det + AI (AVC) | Locked field sequence | Locked field sequence governs red flag activation at every encounter. Ambient Voice Capture maps natural patient conversation to structured History of Present Illness (HPI). |
|
Triage & Concern Engine
|
Deterministic | Diagnosis-level alert |
ACS Field Triage, ATLS, Ottawa Rules, NEXUS, and clinical prediction rules with full audit trail. The Concern Engine accumulates findings and watches for patterns mapping to high-consequence diagnoses. When a pattern crosses its defined threshold, one consolidated alert fires — naming the diagnosis, the recommended action, and all supporting findings.
One concern. One alert. One action. No alert fatigue.
|
|
Imaging Decision + BoneView
|
Det + AI (BoneView) | Pre-disposition | Evidence-based rules govern imaging necessity. When x-ray is obtained, BoneView by Gleamer (RadNet) — FDA-cleared AI fracture detection — flags potential fractures on plain film for clinician review before the patient is discharged. |
|
Differential Synthesis & Medical Decision-Making (MDM)
|
AI (clinically validated knowledge base) | Attestation gate | AI synthesizes differential diagnosis and structured documentation from validated data collected through prior deterministic phases. AgentMSK-generated AI outputs are derived from a curated, clinically validated knowledge base. Clinician attestation required before finalization. All documentation complete at encounter conclusion. |
The platform's safety architecture is not a clinical protocol layer applied on top of existing workflows. It is a deterministic engine that governs what gets evaluated, in what order, before any AI function is engaged. Safety-critical decisions, triage, imaging, and red flag routing are never delegated to AI.
The same evidence-based clinical decision logic at every location in the network. Quality variation based on which provider or which site a patient visits is replaced by a single, auditable clinical standard. Structured data capture enables network-wide quality analytics and operator-level benchmarking.
Structured documentation supports accurate E/M coding, reduces claims denials, triggers appropriate PT and specialist referrals, and captures DME revenue — without changing the clinical encounter. The financial benefit is a direct consequence of clinical documentation quality, not a separate workflow.
The structured clinical workflow AgentMSK enforces mirrors the same systematic reasoning framework that fellowship-trained specialists apply. For clinicians earlier in their career, the platform serves as an evidence-based scaffold — not replacing clinical judgment, but making specialist-level reasoning transferable at scale. Networks can deploy AgentMSK as both a patient care quality tool and a continuing education resource for their clinical workforce.
Orthopedic surgeon with 30+ years of clinical practice and urgent care consulting experience. Clinical domain architect of AgentMSK. Every protocol, decision rule, and clinical pathway reflects real-world specialist practice.
Investment banking professional focused on strategic business development.
Leads the design and development of AI systems supporting real-world clinical and operational needs across the AgentMSK platform.
Former CMO, Novant Health Urgent Care. UCA Board Member. Dual MD/MBA background. Actively engaged in platform development, clinical strategy, and alignment with urgent care network operations.
Clinical protocol development, case library research, SME validation, and literature review supporting the platform evidence base.
Urgent care experts and fellowship-trained orthopedic sub-specialists for clinical module development and validation.
"Every patient deserves the same quality MSK evaluation, regardless of which clinician they see or which site they visit."
Request a platform demonstration or discuss a pilot partnership. We work directly with CMOs, CIOs, and network operators to tailor the demonstration to your organization's clinical and operational context.
AgentMSK qualifies as a non-device clinical decision support tool under the 21st Century Cures Act — providing evidence-based clinical guidance that supports, but does not replace, clinician judgment.
FDA-cleared AI fracture detection integrated into the AgentMSK imaging workflow. When x-ray is obtained, BoneView flags regions of interest on plain film for immediate clinician review — before the patient is discharged and before the official teleradiology report is available. Clinical determination remains with the treating clinician.
Clinical decision rules and imaging criteria grounded in ACS Field Triage, ATLS, Ottawa-class criteria, ACR Appropriateness Criteria, and established specialty society clinical practice guidelines across the AgentMSK module library.