QSimHealth
by qsimhealth.com in Other
Healthcare staffing simulator — ED, walk-in clinic, and appointment office DES tools.
https://qsimhealth.com/mcp/v1
Last 30 days
Status and outage history · Atom feed
- Uptime
- 100%
- Response time
- 396 ms typical, 4.1 s slowest 5%
- Last check
- 4 h ago
- Next check
- in 2 h
How to call it
Add it to any MCP client that supports remote servers.
{
"mcpServers": {
"qsimhealth": {
"type": "http",
"url": "https://qsimhealth.com/mcp/v1"
}
}
}7 tools
- explain_ed_queueing
Return 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
- explain_walk_in_clinic
Explain 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_office
Explain 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_types
List 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_facility
Return 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
Run 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-provid
- recommend_md_count
INVERSE 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?'. Linea
Security scan
- No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.
Recent checks
| When | Result | HTTP | Time |
|---|---|---|---|
| 4 h ago | Passed | 200 | 299 ms |
| 14 h ago | Passed | 200 | 311 ms |
| 23 h ago | Passed | 200 | 3.9 s |
| 32 h ago | Passed | 200 | 396 ms |
| 40 h ago | Passed | 200 | 4.1 s |
| 2 days ago | Passed | 200 | 463 ms |
| 2 days ago | Passed | 200 | 4.3 s |
| 3 days ago | Passed | 200 | 343 ms |
| 3 days ago | Passed | 200 | 342 ms |