COVID-19: Managing reduced capacity

 

Our system used CREST type modelling to set up some key Community Services, enabling the system to manage waiting times to ensure that service standards are met – by planning for sufficient appointments.

 

We now face a sudden reduction in resources of 10%, due to sudden sickness absence of staff across services.

How can CREST help us to understand the impact of this reduction in capacity?

Can CREST help us prioritise our Crisis and Urgent services?


Services at full capacity:

Services
Referrals per year
average Points of Contact in completed pathway
Service Wait-time Standard
Weekly Appointments required
Average Wait-time when required appointments are available (days)
Average number of Breaches of Service Wait-time Standard per month
% Breaching
Crisis
216
3
98% seen same day
21
0.0
0.3
1.9
Urgent
260
6.4
95% seen within 7 days
40
0.7
0.7
3.5
Routine
1040
4.8
95% seen within 4 days
100
4.9
1.7
2.1

Table 1 shows the key services at healthy capacity, with sufficient weekly appointments to manage a variable flow of referrals whilst meeting service wait standards.

Services at 90% capacity:

Services
Referrals per year
average Points of Contact in completed pathway
Service Wait-time Standard
Weekly Appointments required
Average Wait-time when required appointments are available (days)
Average number of Breaches of Service Wait-time Standard per month
% Breaching
Crisis
216
3
98% seen same day
19
0.2
1
6
Urgent
260
3
95% seen within 7 days
36
4.4
4.2
20.8
Routine
1040
4.8
95% seen within 4 weeks
90
unstable
unstable
100

Table 2 shows the immediate impact of a 10% reduction in capacity – as calculated by CREST modelling.

For the Crisis Service it can now expect to fail to meet its’ wait-time standard once-a-month, compared to once every 4 months when at healthy capacity – with 6% of referrals resulting in a wait-time breach, against the usually achieved 2% standard.

The Urgent Service can expect one-in-five of its referrals to result in a breach of the 7-day wait-time standard, against a usually achieved 5% standard.

 The Routine Service would become unstable with a 10% reduction in capacity, and can expect a growing waiting list and very few referrals meeting the 28-day wait-time standard.

 Our system takes the view that it must prioritise service delivery in its Crisis and Urgent Services, and maintain wait-time standards. At the same time the system needs to ensure that the Routine service is stabilised so far as possible.


Services at 90% Capacity, with Routine capacity shifted to Urgent and Crisis to maintain service quality, and Routine service stabilised:
Services
Referrals per year
average Points of Contact in completed pathway
Service Wait-time Standard
Weekly Appointments required
Average Wait-time when required appointments are available (days)
Average number of Breaches of Service Wait-time Standard per month
% Breaching
Crisis
216
3
98% seen same day
21
0.0
0.3
1.9
Urgent
260
6.4
95% seen within 7 days
40
0.7
0.7
3.5
Routine
870
4.8
95% seen within 4 weeks
84
5.3
1.8
2.7
Routine scenario 2
1040
4.0
95% seen within 4 weeks
84
4
0.9
1

Table 3 shows the reallocation of sufficient capacity from the Routine Service to restore healthy capacity to the Crisis and Urgent Services. There are now 84 appointments available in the Routine service (100 healthy capacity minus 10 appointments for sickness minus 6 appointments re-allocated to Crisis/Urgent Services = 84 appointments).

 

Routine scenario 1

In order to stabilise the Routine service the service will implement a temporary change to its assessment protocols, thereby reducing the numbers of referrals entering the service. Using the CReST model enables the system to identify how many referrals the service can manage without compromising on its wait-time service standards – in this instance the equivalent of 870 annual referrals.

Routine scenario 2

In order to stabilise the Routine Service, and following consultation with clinicians and practitioners, the system will reduce the average number of therapeutic contacts per completed pathway. Essentially the system has judged the risk of a repeat referral to re-embed therapy is less injurious to the young people than would be a potentially indefinite period on a waiting list.

Please see the screenshots below for the CREST modelling which underpins the tables above.

Crisis Service baseline modelling.

 

Crisis Service Modelling Inputs

Image

Graph of Crisis Service baseline modelling outputs

Image

Table of Crisis Service modelling outputs (healthy capacity and 10% reduction highlighted)

Available Appointments
Average Wait (Days)
Breaches per Month
% Breaches
12
-
-
100
13
32.5
13.9
83.4
14
7.9
9.7
58.2
15
3.3
6.6
39.5
16
1.5
4.3
25.9
17
0.8
2.7
16.5
18
0.4
1.7
10.1
19
0.2
1
6
20
0.1
0.6
3.4
21
0.0
0.3
1.9

Urgent Service baseline modelling

Urgent Service modelling inputs

Image

Graph of Urgent Service modelling outputs

Image

Table of Urgent Service modelling outputs (healthy capacity and 10% reduction highlighted)

Available Appointments
Average Wait (Days)
Breaches per Month
% Breaches
33
36
13.8
68.8
34
14.3
9.4
46.8
35
7.5
6.3
31.4
36
4.4
4.2
20.8
37
2.7
2.7
13.6
38
1.7
1.8
8.8
39
1.1
1.1
5.6
40
0.7
0.7
3.5

Routine Service baseline modelling

Routine Service modelling inputs

Image

Graph of Routine Service modelling outputs

Image

Table of Routine Modelling outputs (healthy capacity highlighted)

Available Appointments
Average Wait (Days)
Breaches per Month
% Breaches
95
-
-
100
95
-
-
100
97
29.6
30.6
38.3
98
13
11.7
14.6
99
7.6
4.4
5.5
100
4.9
1.7
2.1

Routine Services remodelled to stabilise service

Re-model inputs

Image

The re-modelling set a range of appointment values – from 70 per week to 110 per week, then it was a case of incrementally reducing the ‘Average points of contact per accepted referral’ from its original 4.8 value until the pale blue highlight bar indicates a stable flow based on our target of 84 appointments (i.e. healthy capacity = 100 appointments; minus 10% = 90 appointments; minus 6 appointments reallocated to Crisis and Urgent Services = 84 routine appointments)

Graph of remodelled Routine model outputs

Image

Table of remodelled Routine model outputs (target capacity highlighted)

Available Appointments
Average Wait (Days)
Breaches per Month
% Breaches
80
-
-
100
81
24.4
25.6
32
82
10.6
8.2
10.2
83
6.1
2.6
3.2
84
3.9
0.8
1
85
2.7
0.3
0.3
86
1.9
0.1
0.1