QSimHealth

com.qsimhealth/public · v1.0.0 · productivity

QSimHealth is healthy: it completed an MCP handshake in 1731 ms and exposes 7 tools.

Healthcare staffing simulator — ED, walk-in clinic, and appointment office DES tools.

Endpoint: https://qsimhealth.com/mcp/v1 (streamable-http)

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Facts

Users (last 30 days)0
HandshakeHealthy
Auth neededNone
Tool count7
Latency1731 ms
Last checked (UTC)2026-10-14T21:20:53.975Z

Health history

Checked (UTC)StatusLatencyError
2026-10-14T21:20:53.975ZHealthy1731

Tools (7)

explain_ed_queueingReturn a textbook-level explanation of Emergency Department queueing dynamics — what plain M/M/c can't model (triage breaks FIFO, patients leave LWBS, peaks dominate), and what real ED staffing decisions need (acuity-tiered metrics, abandonment curves, hourly schedules). Use this when the user asks
explain_walk_in_clinicExplain how walk-in clinics differ from EDs structurally — terminating systems, MD/PA mix as the primary lever, short patient patience, peak-hour coverage instead of 24-hour load. Use when the user describes a walk-in clinic, urgent care, or retail health setting.
explain_appointment_officeExplain appointment-based scheduling dynamics — no-show rates as the dominant variance, buffer time as the trade-off lever, double-booking strategy, treatment-time variance by visit type. Use for primary care, specialty clinics, dental, or any scheduled-arrival setting.
list_facility_typesList the four healthcare facility archetypes QSimHealth speaks to: ED, urgent care, walk-in clinic, appointment office. Returns one-line descriptions. Call describe_facility for detail on one type, or simulate_ed_demo to run a generic simulation.
describe_facilityReturn detailed info on one facility type: typical arrival pattern, MD/PA mix, common pain points, what a sim with simulate_ed_demo would teach you about it, and what a CUSTOM facility model from ChiAha would add (your actual data, real schedules, abandonment curves). Use before simulate_ed_demo to
simulate_ed_demoRun a 7-day MD-only demo simulation of an ED, urgent care, walk-in clinic, or appointment-office staffing scenario. Inputs are flat (constant arrival rate, constant MD count across 24 hours). Returns hourly metrics, average wait, total served, utilization. This is a single-provider-type TEACHING dem
recommend_md_countINVERSE of simulate_ed_demo — given an arrival rate and a target average wait, returns the smallest MD count meeting the target. Use when the user asks 'how many MDs do I need to keep wait under N minutes?' or 'what's the minimum staffing that hits a service-level target?'. Linear scan from 1 to max