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This charts shows the predicted percentage of patients who will breach, or have to wait beyond the target wait time. It is represented by the green line. We are also able to calculate the modelled utilisation with the blue line. This refers to the percentage of appointments that are expected to be used by appointments. As appointments increase, the chance of patients breaching targets decreases, but in turn the utilisation of appointments will also decrease.
The horizontal line represents the input target performance, the maximum percentage of patients that should be waiting over the target wait time from referral to treatment
At the point where the blue line crosses the horizontal line, we are able to see the required number of appointments in order to achieve the input performance targets
When you change the variables on the left hand side, you will see dashed lines appear on the chart. These represent the adjusted scenarios while the solid lines represent the baseline
- The light green highlighted row indicates the required number of appointments to meet the baseline scenario
- The light blue highlighted row indicates the required number of appointments to meet the adjusted scenario
The figures contained within this data table reflect those shown within the chart above as well as some additional measures. These are presented for each level of weekly available appointments for both the baseline scenario and the adjusted one (if required).
Average wait (days) shows the modelled predicted number of days the average patient would have to wait between referral and treatment
Breaches per month predicted the number of patients who may breach, or wait beyond the target wait time
% Breaches is the percentage of patients referred who may breach, or wait beyond the target wait time
% Utilisation is the percentage of available appointments that would be utilised
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This chart uses the provided monthly referral figures to look at the next 12 months within that service. It allows us to consider seasonality as well as emerging backlogs in the number of appointments
Each blue bar represents the total number of predicted appointments required to meet demand for that month
The horizontal line is the number of appointments that have been input as being available
The blue dots connected by a line represents a potential emerging backlog. This is calculated as the difference between the number of required appointments and the number of available. On months where there are less appointments than the number required, the backlog of appointments grows. On months where there are more, the backlog doesn't grow, or may even recover. These calculations are cumulative.
(Assumption: no backlog as of the first month. This backlog should be considered in addition to any pre-existing backlog).
The figures within this data table are those within the chart above. Please note, they will change depending on the input variables to the left
Predicted referrals is the number of referrals that the model predicts will be recieved for that month
Predicted required appointments is the number of appointments that would be required to meet the demand each month
Cumulative backlog calculates the difference between the number of required appointments and the number of available appointments each month, calculated on a cumulative basis meaning figures could increase or decrease depending on the different between the two figures.
(Assumption: no backlog as of the first month. This backlog should be considered in addition to any pre-existing backlog).
This tab will enable you to select saved scenarios for inclusion in a management report to download and take away. Your baseline scenarios for each service will be modelled by default.
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Generate PDF report Generate Powerpoint report