Location in SystemView: Explore > Outpatients > Wait Times > Summary Report
In this article:
- What it is
- Why it matters
- How to use it
- How it works
- How it helps you
- Best practices
- FAQs & Troubleshooting
What it is
The Wait Times Summary Report provides a real-time overview of outpatient waiting list performance across hospitals and specialties. It combines key metrics and detailed wait time data to help users understand demand, delays, and overall system pressure.
Why it matters
Managing outpatient waiting lists effectively is critical to reducing clinical risk and improving patient outcomes.
This report helps teams to:
- Identify patients waiting beyond recommended timeframes (over target)
- Detect growing demand and capacity gaps
- Monitor performance trends over time
- Support timely and data-driven decision-making
How to use it
Apply Filters
Use the filter bar to focus on specific:
- Hospitals or regions
- Specialties
- Categories (Urgent, Semi-Urgent, Routine)
- Wait status or patient cohorts
Review Key Metrics
Start with the headline figures:
- Current waiting list size
- Weekly change
- Average demand (YTD and 13-week rolling)
Analyse the Table
Scan the table to:
- Identify specialties with high Over Target counts
- Compare median vs long wait times
- Spot areas with high weekly additions
Take Action
Use insights to:
- Prioritise long-wait patients
- Adjust clinic capacity
- Escalate high-risk specialties
Step-by-step workflow:
- Open Outpatients → Wait Times → Summary Report
- Apply relevant filters (e.g. specialty or hospital)
- Review top-level metrics for demand trends
- Scan table for high Over Target values
- Drill into specialties requiring action
- Use Patient List to prioritise bookings
How it works
The report aggregates outpatient data from source systems and presents it in a structured format:
- Waiting list data is grouped by hospital and specialty
- Wait times are calculated in days (median, 90th percentile, maximum)
- Over Target patients are identified based on clinically recommended timeframes
- Demand metrics (additions) are tracked weekly and averaged over time
Data is refreshed regularly, with a timestamp displayed on the report.
How it helps you
- Quickly identify pressure points
Pinpoint specialties with long waits or growing demand - Improve patient flow
Focus on patients most at risk of delays - Support planning and forecasting
Use trends to anticipate future demand - Enable proactive management
Act early before delays escalate into larger backlogs
Best practices
How often should I use it
| What to do | How often | Who it’s for | Why it helps |
|---|---|---|---|
| Review headline metrics (waiting list size, weekly change, demand trends) | Daily / Weekly | Service Managers, Admin Teams | Quickly identify shifts in demand and emerging pressures |
| Monitor Over Target patients and long waits | Daily | Clinical & Scheduling Teams | Reduces clinical risk by prioritising patients exceeding timeframes |
| Analyse specialty-level performance | Weekly | Operational Managers | Highlights areas requiring additional capacity or intervention |
| Compare rolling averages and weekly additions | Weekly / Monthly | Performance & Planning Teams | Supports trend analysis and forward planning |
| Validate data and review anomalies | As needed | All users | Ensures decisions are based on accurate and reliable data |
Pair with these components
Use this report alongside:
-
🔗 Waiting List > Patient list
To identify and prioritise individual patients for booking -
🔗 Waiting List > Risks & Projections
To understand future demand and patients at risk of breaching -
🔗 Waiting List > Dynamics
To analyse demand vs capacity (additions vs removals) -
🔗 Waiting List > Trends
To monitor long-term waiting list performance and growth
Tips for success
-
Focus on Over Target patients first to reduce risk
-
Use filters to narrow down to actionable cohorts (e.g. specialty, category)
-
Look beyond totals - review percentiles and maximum waits for hidden delays
-
Track weekly changes to spot early signs of pressure
-
Combine insights with operational actions (e.g. adding clinics, reallocating capacity)
-
Regularly review data with clinical and operational teams to align priorities
FAQs / Troubleshooting
Why has the waiting list suddenly increased or decreased?
This may reflect a change in weekly additions/removals, data updates, or operational activity such as clinics being added or cancelled.
What does “Over Target” mean?
Patients who have exceeded their clinically recommended waiting time and may be at increased clinical risk.
Why does the data refresh time vary?
Data refresh depends on source system updates and integration timing.
What should I do if data looks incorrect?
- Check filters are applied correctly
- Confirm with source system data
-
Escalate if discrepancies persist