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Grade BproductionSource date Oct 17, 2026· Last verified Oct 17, 2026

How did MDCS Dermatology use voice AI agents for scheduling?

MDCS Dermatology · Hospitals & Health Systems

Header image: Surgical instruments arranged on a blue drape

MDCS Dermatology (New York and New Jersey) uses Assort Health voice AI agents for patient calls. Assort reports 460 staff hours saved monthly, doubled labor capacity, 29% appointment volume growth supported, and 95% accuracy by the practice's own audit.

Reported outcomes

staff hours saved
460 per month
Source [1] · self-reported
appointment volume growth supported
29%
Source [1] · self-reported
accuracy (practice audit)
95%
Source [1] · self-reported

Outcomes are reported exactly as stated by the source; we have not independently audited them.

How it works

  1. Agents pre-loaded with specialty scheduling patterns and routing logic.
  2. Practice protocols and EHR data converted into live workflows.

Risks & compliance

  • PHI handling (HIPAA); EHR write access
  • Escalation rules needed for clinically urgent requests
  • Vendor-published results; not independently audited

Healthcare cases cover operational and commercial workflows. Nothing here is medical advice or a claim about a device's or drug's efficacy.

Build this yourself

Tools mentioned & how to build it

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Tools mentioned

  • Assort Health (Assort Health)
    Voice AI patient-access agents for specialty practices.

Build a version yourself

  • Retell AI
    Build and deploy phone agents for scheduling, intake and call routing.
  • Zapier
    The default app-to-app automation layer, now with AI agents and AI steps.
  • Make
    Visual no-code automation with AI agents; good for intake, routing and follow-up flows.

All tools by category →

Sources

[1]Assort Health· vendor customer story· Undated (accessed Oct 17, 2026)
“reaching 95% accuracy by the practice's own audit within weeks of go-live”
MDCS Dermatology Doubles Labor Capacity and Saves 460 Staff Hours Monthly

Grade rationale: Named organization with a quantified outcome from the vendor or the organization itself (self-reported). Automated check on Oct 17, 2026: 1/1 quotes and 3/3 outcome claims matched the source. Compiled by the Agent Casefile research desk (AI-assisted; see methodology). Spot an error? Request a correction.

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