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Introduction
The Group Report visualises the journey of every patient who chooses to call from the moment they enter a queue. This report is essential because it provides proof of patient demand. By monitoring the flow of traffic through specific groups you can gain a high-level view of how your practice handles volume across different service lines
What does this report show?
Total Queue Volume
Answered vs Missed Calls
Patient Waiting Times
Staff Workload Distribution
Peak Busy Periods
Queue Activity
This tab provides a high-level overview of call volumes, comparing answered versus missed calls through daily bar charts and a breakdown of activity that can be filtered to specific groups
What you can Measure
Queue-Specific Performance: Filter by Queue Group (e.g., Reception, Secretary, Admin) to see which departments are handling the highest volume. This helps you identify if one specific team is disproportionately burdened compared to others
Answered vs. Missed Ratio: Monitor the % of Answered and % Missed from the queue. This is a vital health check for your patient access, showing exactly what portion of the queued demand is resulting in a successful interaction
Workload Distribution by Group: The Queue Activity by Group pie chart visualises the share of total calls handled by each team. For instance, if Reception is handling nearly all traffic, it may suggest a need to divert more specific queries to Admin or Secretary lines
Daily Volume: The Volume of Calls that Queued bar chart highlights surges in demand. By tracking the "orange bars" (Missed Calls) against the "blue bars" (Answered Calls), you can see if your missed call rate increases linearly with volume or if it spikes at a specific "breaking point"
Weekday Demand Patterns: Use the Weekday filter to compare performance across different days. This allows you to verify if staffing adjustments made for traditionally busy days (like Mondays) are effectively reducing the missed call rate
Queue Duration and Callbacks
This section focuses on wait times and the performance of the callback system, visualising how long patients stay in the queue and the success rate of returned calls
What you can Measure
Wait-Time Trends: Monitor both Average and Longest Queue Durations to identify the patient experience during peak surges. This helps you spot significant outliers allowing you to investigate specific staffing bottlenecks
Callback Adoption Rate: Track how many patients are offered a callback versus how many accept (Callbacks Requested). A high adoption rate during busy periods indicates that patients trust the system and are willing to use "virtual" queuing to avoid long hold times
Callback Success Rate: Measure if the system is effectively reconnecting staff with patients on the first attempt
Virtual Queue Impact: Calculate the total "on-hold" time saved by using the Total Virtual Duration metric. For example, saving patients over 8.5 hours of hold time in a single period demonstrates a significant improvement in patient satisfaction and reduced telephony costs
Service Capacity: The Average and Longest Queue Durations chart highlights exactly when your practice reached its limit. This visual aid is crucial for identifying if long wait times are a consistent daily issue or isolated incidents related to specific events
Daily Summary Table
This tab offers a granular, date-by-date breakdown of all queue metrics in a list format, allowing for a direct comparison of daily performance and specific missed call data
What you can Measure
Comparative Daily Performance: View side-by-side metrics for Inbound Calls Queued versus Inbound Answered
True Missed Call Rate: Distinguish between total missed calls and Short Disconnects (callers hanging up in under 10 seconds). This allows you to filter out "accidental" dials and focus on patients who actually required an interaction but were unable to wait
Service Level Extremes: Track the Longest Queue Duration for both answered and missed calls each day. Identifying these outliers allows for targeted investigation into specific operational bottlenecks
Hourly Summary Table
This breaks down call volume, answer rates, and wait times into specific time slots throughout the day to help managers identify peak hours and adjust staffing levels accordingly
What you can Measure
Peak Traffic Windows: Identify the exact hours of highest demand, typically the 08:00–10:00 morning rush and the 14:00–16:00 mid-afternoon surge. For example seeing over 150 calls per hour in these slots helps justify additional staffing during these windows
Hourly Response Consistency: Track the % of Queue Answered hour-by-hour. This reveals if your service level drops during specific times, such as lunch breaks (13:00–14:00) or shift changes, allowing you to smooth out coverage
Concentrated Missed Calls: Pinpoint the exact hour when the most patients are hanging up. For example, if the 15:00–16:00 window shows a spike in missed calls, it indicates a specific period where demand has momentarily outpaced your available staff
Operational Outliers: Use the Longest Answered Duration metric to find the single most difficult hour of the day. A long wait occurring in the late afternoon suggests a bottleneck that may require a change in how late-day queries are routed
Patient Callback
This report provides a detailed log of callback interactions, specifically tracking outcomes like successful connections, failed attempts, and total virtual queue time
What you can Measure
Callback Completion Success: Track the ratio of Callbacks Requested to Callbacks Successful. A high success rate (e.g., 92%) confirms that your staff are effectively closing the loop with patients once they enter the virtual queue
Patient Time Savings: Measure the Total Virtual Queue Duration to see the cumulative "on-hold" time saved. For example, saving patients over 8 hours of listening to hold music in a single period significantly improves the overall patient experience
Failed Attempts: Monitor the Attempts Exceeded column to see how often the system tried but failed to reach a patient. A low number here ensures that your callback settings are providing enough opportunity for patients to answer their returned calls
Demand for Virtual Queuing: Identify which days of the week see the highest adoption of this service. Comparing Callbacks Offered to Callbacks Requested on busy Mondays or Tuesdays helps you understand patient usage for automated alternatives during peak surges
Virtual vs. Real Wait Times: Compare Average Virtual Duration against Average Real Duration to see the efficiency gain
Queued Call Talk Duration
This final tab analyses the length of the actual conversations once a call is answered, showing both average and peak talk times to help understand staff workload and call complexity
What you can Measure
Departmental Workload: Compare Average Talk Duration across different groups (e.g., Reception vs. Admin). For instance, while Reception may handle the highest volume, Admin calls often take longer on average, reflecting more complex back-office processing
Staff Handling Consistency: Monitor the Average Overall Talk Duration to establish a baseline for performance. This helps in setting realistic expectations for how many calls a single staff member can handle per hour
Complexity Outliers: Use the Longest Overall Talk Duration to identify individual calls that significantly exceeded the average. A high-complexity interaction that may indicate a difficult triage or a patient requiring extra support
Cumulative Resource Impact: The Total Overall Talk Duration quantifies the total staff hours spent on the phone
Volume vs. Duration Trends: The Average and Longest Talk Durations chart visualises whether talk times increase during your busiest days