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Historic Breach Analysis

Understand when and where ED access target breaches occur over time to identify patterns and performance gaps.

Location in SystemView: Emergency Department > Historic Breach Analysis

In this article

What it is

The Historic Breach Analysis component shows Emergency Department (ED) performance against time-based access targets over a selected historical period. It focuses on when breaches occur, how frequently they happen, and how performance trends over time.

It provides both volume (number of breaches) and performance (% achieved within KPI) views, with the ability to analyse results by arrival date, breach date, triage category, and stage of the ED journey.

Why it matters

Identify patterns in ED breaches to better understand performance over time.

This component helps teams move beyond real-time monitoring to understand historical trends and recurring pressure points.

  • Track how often ED patients exceed the selected KPI (for example, 6-hour PET).
  • Compare performance by arrival date versus breach date to understand flow dynamics.
  • Identify which triage categories or patient groups are most impacted.
  • Support retrospective review, reporting, and service planning.

How to use it

Filter to focus your view

Use the filter bar to refine the analysis:

  • Health Region / Hospital: Select the organisation or facility to analyse.
  • Timeframe: Define the historical period (for example, last 3 months).
  • Breach Type: Choose the stage of the ED journey to analyse against KPI:
    • Total PET
    • Waiting for Triage
    • Waiting to be Seen
  • KPI: Select the time threshold (for example, 6 hours). This defines what constitutes a breach.
  • Date: Filter to specific dates if required.
  • Age Group: Focus on Adult, Paediatric, Aged 75+, or all patients.
  • Admitting Specialty: Filter by specialty where relevant.
  • Admission Status: View admitted, non-admitted, or all patients.
  • Area Type: Filter by ED area (for example, Main or other configured areas).
  • Triage: Analyse specific triage categories (1–5).

Explore breach trends

Use the toggle buttons within charts to switch between:

  • Date of Breach: When the KPI was exceeded
  • Arrival Date: When the patient presented to ED

This allows comparison between when demand entered the system and when breaches occurred.

Explore breach trends and performance

Tile / Chart Name What it shows
Total PET Breach by Date of Breach Daily count of patients in ED who exceeded the selected KPI, grouped by the date the breach occurred. Includes breakdown by triage category.
% Achieved by Date of Breach Percentage of patients who met the KPI on each day, based on breach date. Calculated as the proportion of patients within the KPI.
Total PET Breach by Arrival Date Daily count of patients who breached the KPI, grouped by their ED arrival date. Helps link breaches back to demand patterns.
% Achieved by Arrival Date Percentage of patients meeting the KPI, grouped by arrival date. Useful for understanding performance relative to incoming demand.
Total Number of Breached Patients in the Department by Date Total number of patients present in ED on each date who exceeded the KPI, regardless of when they arrived.
% Achieved Patients in the Department by Date Percentage of all patients in ED on a given date who met the KPI. Reflects overall department performance on that day.
Total PET – Average Time Waiting by Arrival Date Average total ED length of stay (LoS) for patients, grouped by arrival date and triage category. Highlights variation in patient experience over time.
Total PET Patient Journey ED Pathway Duration Patient-level table showing timestamps across the ED journey (arrival, triage, first seen, bed request, etc.), along with wait times and triage category.

How it works

This component uses historical ED presentation and patient journey data to analyse performance against a selected time-based KPI.

  • A breach occurs when a patient’s time in ED exceeds the selected KPI threshold (for example, 6-hour PET).
  • The KPI filter determines the threshold applied across all charts.
  • Breach Type defines which part of the ED journey is being measured against the KPI (for example, total ED length of stay or specific wait stages).
  • Data can be grouped by either:
    • Arrival Date (when the patient presented), or
    • Date of Breach (when the KPI threshold was exceeded).

Data is refreshed regularly from source systems and reflects recorded ED events and timestamps.

How it helps you

  • Identify recurring pressure periods: Understand which days or periods consistently show higher breach volumes.
  • Link demand to performance: Compare arrival-based and breach-based views to identify delayed effects of demand.
  • Understand cohort impact: Analyse which triage categories or patient groups are most affected by delays.
  • Support performance reporting: Use % achieved metrics to track access target compliance over time.
  • Investigate individual journeys: Drill into patient-level data to understand where delays occur.

Best practices

How often should I use it?

What to do How often Who typically does this Why it helps
Review breach trends over recent weeks Weekly ED Operations Manager / Flow Coordinator Identifies emerging patterns and recurring pressure points
Compare arrival vs breach date views Weekly ED Leadership / Performance Analysts Helps distinguish demand-driven vs process-driven delays
Analyse triage category performance Fortnightly ED Clinical Leads Highlights which patient groups are most impacted
Investigate specific high-breach days As needed ED Analysts / Operations צוות Supports root cause analysis and review

Pair with these components

Tips for success

  • Use Arrival Date and Date of Breach together to understand how demand translates into downstream pressure.
  • Start with Total PET, then refine to specific wait stages to isolate where delays occur.
  • Review both counts and percentages to balance volume and performance perspectives.
  • Use the patient-level table to validate trends and investigate outliers.
  • Be aware that filters significantly affect interpretation, particularly KPI and Breach Type.