Optimizing Patient Throughput

**Overview**
Patient flow analytics provide crucial information to identify bottlenecks that create cascading delays throughout the hospital system. Indicators of opportunities for improving patient flow include
- Increased lengths of stay
- Reduced patient satisfaction scores
- Increased operational costs
- Reduced access to critical care resources in a timely manner

**Objective:**
This demonstration notebook provides a preview of how Health Catalyst's advanced analytics platform approaches patient flow optimization.
For this analysis, we will focus specifically on ED boarding solutions, showcasing our predictive analytics capabilities that forecast patient discharges and optimize real-time bed allocation to reduce boarding times and improve patient flow.

**Key Focus Areas**:
- Identify bottlenecks or constraints
- Eliminate or reduce bottlenecks or constraints
- Maximize hospital capacity utilization

**Product details**

**Demo Schema:** *patient_flow_forecasting*
- *patient_throughput_hourly_flow* - Patient hourly flow
- *patient_throughput_encounters* - Patient encounters
- *patient_throughput_bed_metrics* - Bed management metrics

**Hourly Patient Flow (Sample Fields)**
- `timestamp`: Hour timestamp
- `hospital_id`: Hospital identifier
- `unit_code`: Care unit code (ED, ICU, etc.)
- `occupancy_rate`: Current bed occupancy percentage
- `avg_wait_minutes`: Average wait time for the unit

**Patient Encounters (Sample Fields)**
- `encounter_id`: Unique encounter identifier
- `patient_id`: Patient identifier
- `admission_datetime`: Admission timestamp
- `discharge_datetime`: Discharge timestamp
- `unit_sequence`: Path through hospital units
- `ed_boarding_hours`: Time spent boarding in ED

For more details, refer to the embedded notebook.

*This product uses synthetic data and simplified models for illustration purposes. Results shown are not indicative of actual performance. Health Catalyst's production platform includes comprehensive data security, HIPAA compliance, clinical validation, and continuous monitoring that cannot be fully represented in this demonstration environment.*