Your First Day as a Healthcare Data Analyst
An original Wumtech simulation using a fictional health network and synthetic data. No real patient data or PHI is used anywhere in this environment.
Network Overview
Patients
| MRN | Name | Age | Sex | Department | Status |
|---|---|---|---|---|---|
| SYN-10234 | R. Alvarez | 41 | F | Emergency | Waiting |
| SYN-10891 | J. Mensah | 67 | M | Cardiology | Admitted |
| SYN-11002 | P. Nguyen | 29 | F | Emergency | In Treatment |
| SYN-11187 | D. Okafor | 54 | M | Orthopedics | Discharged |
Patient Profile — SYN-10234
- Arrival08:14 — Emergency
- Triage08:31 — ESI Level 3
- VitalsHR 92 · BP 128/82 · Temp 98.9°F
- Labs orderedCBC, BMP
- Provider seen09:48 — Dr. R. Falade
Encounters
| Encounter ID | MRN | Type | Department | Arrival | Wait |
|---|---|---|---|---|---|
| ENC-88213 | SYN-10234 | ED Visit | Emergency | 08:14 | 77m |
| ENC-88214 | SYN-11002 | ED Visit | Emergency | 09:02 | 64m |
| ENC-88219 | SYN-10891 | Inpatient | Cardiology | 07:40 | 18m |
| ENC-88231 | SYN-11187 | Outpatient | Orthopedics | 10:15 | 12m |
Labs
| Order ID | MRN | Test | Status | Ordered |
|---|---|---|---|---|
| LAB-5521 | SYN-10234 | CBC | Pending | 08:35 |
| LAB-5522 | SYN-10234 | BMP | Pending | 08:35 |
| LAB-5498 | SYN-10891 | Troponin | Complete | 07:55 |
Medications
| MRN | Medication | Dose | Route | Status |
|---|---|---|---|---|
| SYN-10891 | Aspirin | 81mg | PO | Administered |
| SYN-11002 | Ibuprofen | 400mg | PO | Administered |
Diagnoses
| MRN | Code | Description |
|---|---|---|
| SYN-10891 | I20.9 | Angina, unspecified |
| SYN-11187 | S93.4 | Sprain of ankle |
Providers
| Provider | Department | Role | Active Patients |
|---|---|---|---|
| Dr. R. Falade | Emergency | Attending | 9 |
| Dr. S. Kim | Cardiology | Attending | 6 |
| Dr. A. Byrne | Emergency | Resident | 7 |
Departments
| Department | Patients | Avg. Wait | Change |
|---|---|---|---|
| Emergency | 612 | 54m | ↑ 18% |
| Cardiology | 203 | 21m | ↑ 2% |
| Orthopedics | 178 | 17m | ↓ 1% |
| Primary Care | 340 | 14m | ↓ 3% |
| Radiology | 96 | 22m | ↑ 1% |
Analytics Workspace
Wait times climb sharply from 12pm and peak between 2–4pm — worth checking against staffing schedules and arrival volume for the same window.
Department breakdown
| Department | Patients | Avg. Wait | Change |
|---|---|---|---|
| Emergency | 612 | 54m | ↑ 18% |
| Cardiology | 203 | 21m | ↑ 2% |
| Orthopedics | 178 | 17m | ↓ 1% |
Data dictionary (excerpt)
- Avg. WaitArrival → provider-seen, in minutes
- EncounterOne visit record, one department
- ESI LevelEmergency Severity Index, 1 (most urgent) – 5
Analyst Assignments
ED Wait Time Investigation
ED wait times have increased 18%. Leadership needs to understand why — and what to do about it.
Readmission Risk Review
Unlocks after your first submitted findings.
Staffing & Volume Forecast
Unlocks after your first submitted findings.
Use the Analytics tab to look at the hourly wait-time chart and department breakdown before you write up your findings below.
All names, patients, encounters and metrics on this page are synthetic and generated for demonstration purposes. Wumtech Health Network is a fictional organization. No real patient data or protected health information (PHI) is used or stored anywhere in this environment.
This simulation is the first mission in Wumtech Academy.
Future missions add readmission-risk analysis, staffing forecasts, and a portfolio you can show employers.