---
title: Live Inpatient Occupancy Forecast
description: Forecast inpatient bed occupancy to anticipate demand, plan discharges, and improve hospital flow in SystemView.
---
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November 14, 2025
# Live Inpatient Occupancy Forecast
## Forecast upcoming inpatient occupancy to plan capacity and keep hospital flow moving smoothly.
#### **Location in SystemView:** SystemView \> Explore \> Beds \> Inpatient Occupancy Forecaster \> Live Inpatient Occupancy Forecast
**In this article:**
- [What is it?](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#whatisit)
- [Why it matters](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#whyitmatters)
- [How to use it](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#howtouseit)
- [How it works](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#howitworks)
- [Component logic](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#componentlogic)
- [How it helps you](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#howithelpsyou)
- [Best practices](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#bestpractice)
- [Interactive guide](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#interactiveguide)
- [FAQs / Troubleshooting](https://academy.healthcarelogic.com/knowledge/live-inpatient-occupancy-forecaster#faqs)
---
### **What is it?**
The **Live Inpatient Occupancy Forecast** tool predicts hospital bed occupancy for the coming days, enabling you to identify pressure points early and take proactive action to balance demand and capacity.
### **Why it matters**
##### *See tomorrow’s occupancy, today.*
This component empowers hospitals to anticipate bed shortages and plan patient flow with confidence. It helps prevent bottlenecks, improve discharge coordination, and ensure safe and efficient use of inpatient capacity.
**Key benefits:**
- Identify wards forecasted to exceed bed capacity.
- Plan elective admissions around predicted peaks.
- Support timely discharges and reduce access block.
- Improve visibility of demand trends across hospital divisions.
---
### **How to use it**
#### **Filter to focus your view**
Use filters to narrow your forecast to a specific hospital, division, or ward:
- **Facility/Hospital** – Select the facility you want to focus on.
- **Division** – Choose one or more divisions.
- **Ward** – Choose one or more wards.
- **Type** – Filter by bed type (e.g. Standard Beds, Special Purpose Beds).
- **Forecast Days** – Select the number of days ahead to forecast.
- **Current Patient Details** – Click to view current patients and total length of stay.
- **Show Elective Surgery Patients** – Click to view planned admissions and scheduled admission dates
💡 ***Tip:** Combine division and ward filters to zoom in on the areas most likely to face capacity constraints*
#### **Monitor key forecast metrics**
Each tile displays an insight into inpatient demand and capacity:
| **Tile Name** | **What It Shows** |
| --- | --- |
| Occupancy Forecast Metrics | Overview of current and projected occupancy |
| Occupancy Forecast by Start of Day | Forecasted number of inpatients per day vs. the estimated capacity. |
| New Demand by Day and Patient Type | Expected new admissions split by patient type (e.g., scheduled or unscheduled). |
| Future Predicted Discharges by Day and Patient Type | Forecasted discharges to support discharge planning. |
| Occupancy Forecast by Date and Division | Daily forecasted occupancy at division level. |
| Occupancy Forecast by Date and Ward | Daily forecasted occupancy at ward level. |
💡 ***Tip:** Hover or click to view additional patient details within each tile.*
---
### **How it works**
The Live Inpatient Occupancy Forecast combines advanced statistical simulation and machine-learning models to estimate future bed use. It analyses historical patterns in admissions, discharge timing, and length of stay to predict how many beds are likely to be occupied on each future day.
#### **Component logic**
The model draws on multiple predictive techniques developed in collaboration with Bond and Griffith Universities in Queensland, Australia to forecast both scheduled and unscheduled patient activity:
- **Markov Chain modelling:** simulates how unscheduled patients move through wards until discharge, based on typical inpatient pathways.
- **Monte Carlo modelling:** models random arrival patterns for unscheduled admissions to estimate daily demand.
- **Scheduled demand modelling:** incorporates all known elective admissions and their booked lengths of stay, together with estimated additions to waiting lists.
- **Length of stay *XGBoost* model:** a patient-level machine-learning model predicting expected stay duration for each admission, supporting discharge forecasting and flow planning.
These techniques generate **two linked forecasts**:
1. **Total future occupancy:** includes both current and expected new admissions (scheduled and unscheduled).
2. **Scheduled-only occupancy:** limited to currently booked admissions, enabling users to understand how changes to bookings or capacity would affect demand.
The model continuously recalibrates daily as new admissions, discharges, and schedule updates occur.
**In simple terms:**
SystemView looks at how patients typically move through your hospital, how many are admitted each day, how long they usually stay, and when they’re discharged. It combines this with known upcoming bookings and current patient data to predict how many beds will be occupied on each future day. The forecast updates daily as new admissions, discharges, or bookings occur, giving you a live view of likely bed pressure before it happens.
---
### **How it helps you**
- **Plan ahead with confidence:** Anticipate bed demand before bottlenecks occur.
- **Stay in control of flow:** Adjust discharge planning and admissions in response to upcoming peaks.
- **Make data-driven decisions:** Rely on accurate forecasts backed by advanced predictive modelling.
- **Support collaboration:** Give operational, clinical, and executive teams a single source of truth on future capacity.
- **Reduce last-minute pressure:** Avoid reactive bed management by planning resourcing and patient movements early.
---
### **Best practices**
#### **How often should I use it?**
| What to Do | How Often | Who Should Do It | Why It Helps |
| --- | --- | --- | --- |
| Review occupancy forecasts for upcoming days | **Daily** | Bed Managers, Patient Flow Coordinators | Identify early capacity risks and prepare proactive bed management strategies. |
| Cross-check forecasts with Scheduled Demand | **Weekly** | Hospital Operations Managers, Bed Managers | Align elective admissions with forecasted capacity to prevent overbooking or overflow. |
| Review ward-level occupancy trends | **Weekly** | NUMs / Ward Leaders | Anticipate ward-level demand to plan staffing and discharge priorities. |
| Share key insights from forecasts with leadership teams | **Weekly** | Hospital Operations Managers, Patient Flow Leads | Support executive decision-making and enhance visibility of system pressures. |
#### **Pair with these components**
- **🔗 [Inpatient Occupancy Forecaster \> Historical Analysis](https://academy.healthcarelogic.com/knowledge/inpatient-occupancy-forecaster-historical-analysis):** Review how accurate past forecasts were to assess model performance and improve confidence in future predictions
- **🔗 [Inpatient Demand \> Scheduled Demand](https://academy.healthcarelogic.com/knowledge/beds-inpatient-demand-scheduled-demand):** Review detailed elective admission schedules to see how future planned activity affects forecasted occupancy.
- **🔗 [LoS Trends & Ward Dynamics](https://academy.healthcarelogic.com/knowledge/beds-los-trends-and-ward-dynamics):** Compare forecasted trends with historical length of stay and occupancy patterns.
- **🔗 [Bed Capacity Monitor](https://academy.healthcarelogic.com/knowledge/beds-bed-capacity-monitor):** Confirm capacity data is current and aligned with forecasted demand.
#### **Tips for success**
- Check the **Occupancy Forecast Metrics** tile daily to spot early pressure points.
- Use **Forecast Days** to explore both short-term and longer-term capacity risks.
- Combine forecast data with **Current Patient Details** to prioritise potential discharges.
- Review ward-level forecasts regularly before peak periods or public holidays.
---
### **Take a quick tour**
Click through the interactive guide below to see how the Live Inpatient Occupancy Forecast tool works in action.
---
### **❓FAQs / Troubleshooting**
**Q:** **Why can’t I view all facilities?**
**A:** The component supports one district and one facility/hospital selection at a time.
**Q:** **Why are some wards missing?**
**A:** Only *Main Ward Groups* are included. Day-case or specialty wards are excluded from forecasting.
**Q:** **Why can I only see forecasts for up to 10 days ahead?**
**A:** The forecast horizon depends on how far in advance your site schedules inpatient activity. Some hospitals only schedule admissions up to 7–10 days ahead, so forecasts beyond that may not be available or reliable. Sites that plan further in advance will see longer forecast ranges.
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