Barts Health NHS Trust is the largest NHS trust in the UK, serving over 1.5 million people across five hospitals. It is working to improve its performance against cancer waiting time standards, which have been challenging to meet consistently. A Cancer Performance Management Team was established to develop a Recovery Action Plan, with a focus on improved demand modeling, standardized pathways and processes, competency training for coordinators, and deep dive reviews of challenged tumor types together with clinical commissioning groups. The goal is to sustainably achieve all cancer waiting time targets through strengthened leadership, data quality, and collaborative working across the care system.

1. Improving Delivery against Cancer
Waiting Time Standards
Barts Health NHS Trust
20th April 2016
Dr Angela Wong
Clinical Director for Cancer
Performance & Improvement
Stephen Hall
Director for Cancer
Performance & Improvement
Karina Malhotra
Operational Turnaround Director – Elective Care
Programme Management Office (PMO) for
1

2. 2
Overview of the Trust
2
Barts Health NHS Trust is the largest NHS Trust in the country, employing
16,000 staff, with a turnover of £1.25 billion. The Trust comprises five
hospitals, in addition to running a community health service for the London
Borough of Tower Hamlets. The Trust serves a population of 1.5 million
people.
Royal London
Hospital
Mile End Hospital
St Bartholomew’s
Hospital
Whipps Cross
University
Hospital
Newham
University
Hospital

3. 3
Cancer Services at Barts Health
3
We offer patients the very latest treatments and technology, as well as the
opportunity to participate in clinical trials, and we are always trying to improve
the treatment that we are able to offer.
Internationally
Reputed
Common and rare
cancers
Experimental
Cancer Medicine
Centre
Cancer Research
UK Centre (at St
Bartholomew's
Hospital)
High quality,
specialist cancer
care

4. 4
Improving Delivery and Performance
against the Cancer Waiting Time Standards

5. 5
Two Week Wait Demand
5
Barts Heath NHS Trust sees approximately c2,200 two week wait
referrals each month and the number of referrals has been increasing
year on year

6. 6
Impact on Cancer Standards
6
Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15
Seen 1809 1949 1591 1754 1861 1734 1782 1655 1827 1947 1802 1912 1987 2213 1870 1945 1982 2157 2127
Breach 274 200 129 145 106 78 119 109 74 79 167 163 85 90 79 123 83 87 62
(%) 84.9% 89.7% 91.9% 91.7% 94.3% 95.5% 93.3% 93.4% 95.9% 95.9% 90.7% 91.5% 95.7% 95.9% 95.8% 93.7% 95.8% 96.0% 97.1%
Seen 179 185 154 212 240 252 267 252 265 236 164 201 286 356 244 287 261 319 337
Breach 21 12 6 4 5 7 10 5 4 8 2 10 9 7 9 8 11 7 7
(%) 88.3% 93.5% 96.1% 98.1% 97.9% 97.2% 96.3% 98.0% 98.5% 96.6% 98.8% 95.0% 96.9% 98.0% 96.3% 97.2% 95.8% 97.8% 97.9%
Seen 244 264 235 252 304 232 239 250 210 244 229 238 240 286 230 279 304 260 240
Breach 10 14 12 15 16 8 8 12 9 7 8 11 7 11 9 11 10 5 4
(%) 95.9% 94.7% 94.9% 94.0% 94.7% 96.6% 96.7% 95.2% 95.7% 97.1% 96.5% 95.4% 97.1% 96.2% 96.1% 96.1% 96.7% 98.1% 98.3%
Seen 112 97.5 119 119 136.5 107.5 108.5 108 96.5 120 111 102 109 137 103 117 143 105 109.5
Breach 29.5 22 26.5 35.5 37.5 23 32 29 24.5 23.5 26.5 25.5 32.5 36 22.5 30 20.5 16.5 15
(%) 73.7% 77.4% 77.7% 70.2% 72.5% 78.6% 70.5% 73.1% 74.6% 80.4% 76.1% 75.0% 70.2% 73.7% 78.2% 74.4% 85.7% 84.3% 86.3%
Seen 15.5 29 13 10.5 25.5 11.5 16 20 8 15.5 23 21.5 23 22.5 15.5 22 21.5 18.5 22
Breach 2 6.5 3.5 1.5 4.5 2.5 1 4 1 2 3 4 4 2 0 1.5 2 0 2
(%) 87.1% 77.6% 73.1% 85.7% 82.4% 78.3% 93.8% 80.0% 87.5% 87.1% 87.0% 81.4% 82.6% 91.1% 100.0% 93.2% 90.7% 100.0% 90.9%
Seen 18.5 17.5 11.5 17.5 29.5 21.5 26 18 13.5 18 13.5 23.5 19 19.5 24 19.5 22 28 29
Breach 5.5 3 2.5 3 7 2.5 5 5.5 3 2.5 2.5 7 4 2 3.5 2 1.5 2 3
(%) 70.3% 82.9% 78.3% 82.9% 76.3% 88.4% 80.8% 69.4% 77.8% 86.1% 81.5% 70.2% 78.9% 89.7% 85.4% 89.7% 93.2% 92.9% 89.7%
Seen 45 33 38 34 40 30 24 23 14 11 8 87 111 170 125 151 129 99 60
Breach 3 0 1 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
(%) 93.3% 100.0% 97.4% 88.2% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 99.1% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Seen 34 22 29 35 34 41 31 60 24 25 25 17 25 43 45 42 49 43 38
Breach 5 4 0 3 2 6 5 5 1 1 1 1 1 1 0 1 1 1 0
(%) 85.3% 81.8% 100.0% 91.4% 94.1% 85.4% 83.9% 91.7% 95.8% 96.0% 96.0% 94.1% 96.0% 97.7% 100.0% 97.6% 98.0% 97.7% 100.0%
Seen 126 144 112 129 132 120 100 100 100 111 115 112 125 112 103 109 123 119 91
Breach 7 8 4 6 3 2 0 6 2 1 4 4 3 1 6 4 0 2 0
(%) 94.4% 94.4% 96.4% 95.3% 97.7% 98.3% 100.0% 94.0% 98.0% 99.1% 96.5% 96.4% 97.6% 99.1% 94.2% 96.3% 100.0% 98.3% 100.0%
31 Day Standard 96%
85%
90%
62 Day Standard
62 Day Screening
Patients
31 Day
Subsequent:
Radiotherapy
94%
62 Day
Consultant
Upgrade
85%
31 Day
Subsequent:
Drug
98%
31 Day
Subsequent:
Surgery
94%
All
All cancer Two
Week wait
93%
Symptomatic
Breast Two
Week wait
93%

7. 7
Two Week Wait Recovery
7
y have 16 more slot(s) than might be needed to sustain the service at a comfortable level
0
5
10
15
20
25
30
35
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51
Patients
Week
Demand
75th Percentile 85th Percentile 2 Deviations Below
2 Deviations Above Referrals Mean
NHS IMAS IST Capacity and Demand modelling

8. 8
Delivering 31 Day Standard
8
Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15
Seen 244 264 235 252 304 232 239 250 210 244 229 238 240 286 230 279 304 260 240
Breach 10 14 12 15 16 8 8 12 9 7 8 11 7 11 9 11 10 5 4
(%) 95.9% 94.7% 94.9% 94.0% 94.7% 96.6% 96.7% 95.2% 95.7% 97.1% 96.5% 95.4% 97.1% 96.2% 96.1% 96.1% 96.7% 98.1% 98.3%
Seen 45 33 38 34 40 30 24 23 14 11 8 87 111 170 125 151 129 99 60
Breach 3 0 1 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
(%) 93.3% 100.0% 97.4% 88.2% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 99.1% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Seen 34 22 29 35 34 41 31 60 24 25 25 17 25 43 45 42 49 43 38
Breach 5 4 0 3 2 6 5 5 1 1 1 1 1 1 0 1 1 1 0
(%) 85.3% 81.8% 100.0% 91.4% 94.1% 85.4% 83.9% 91.7% 95.8% 96.0% 96.0% 94.1% 96.0% 97.7% 100.0% 97.6% 98.0% 97.7% 100.0%
Seen 126 144 112 129 132 120 100 100 100 111 115 112 125 112 103 109 123 119 91
Breach 7 8 4 6 3 2 0 6 2 1 4 4 3 1 6 4 0 2 0
(%) 94.4% 94.4% 96.4% 95.3% 97.7% 98.3% 100.0% 94.0% 98.0% 99.1% 96.5% 96.4% 97.6% 99.1% 94.2% 96.3% 100.0% 98.3% 100.0%
31 Day Standard 96%
31 Day
Subsequent:
Radiotherapy
94%
31 Day
Subsequent:
Drug
98%
31 Day
Subsequent:
Surgery
94%
All

9. 9
Cancer Treatments against the 62 Day Standard
9
• The Trust treats circa 110 patients a month diagnosed with cancer on
a 62 day cancer waiting time pathway
• Like most large tertiary centres, the key challenge is achieving the 62
day cancer waiting time standard

10. 1010
Challenges Facing the Trust (62 days)
• Increased volume of TWW referrals
• Lack of robust demand and capacity modelling
• Inadequate performance forecasting tools
• Loss of knowledge and skilled MDT staff
• Insufficient Trust supporting policies
• Lack of agreed timed pathways
• No formal coordinated action plans
• Lack of focus on cancer standards due to competing priorities

11. 1111
Approach to Improving Performance
• Clinical leadership and Senior Executive support in recovery
• Cancer Performance Management Team established

12. 1212
Director of Cancer
Performance and
Improvement
Operational
Turnaround PMO
Support
General Manager for Cancer
Performance
Cancer Clinical Director
Performance and
Improvement
Cancer Service Manager
Service Manager for Cancer
Data Quality
Service Manager for Service
Improvement and Pathway
Pathway
Manager
St
Bartholomew’s
Pathway
Manager
The Royal
London
Pathway
Manager
Newham
Pathway
Manager
Whipps Cross
Technical Data
Quality
Analysts
Technical Data
Quality
Analysts
MDT Co-
ordinators x 6
St
Bartholomew’s
MDT Co-
ordinators x 5
The Royal
London
MDT Co-
ordinators x 5
Newham
MDT Co-
ordinators x 7
Whipps Cross
Apprentice
Pathway
Trackers x 2
St
Bartholomew’s
Pathway
Trackers x 2
The Royal
London
Pathway
Trackers x 1
Newham
Pathway
Trackers x 2
Whipps Cross

13. 1313
Approach to Improving Performance
• Clinical leadership and Senior Executive support in recovery
• Cancer Performance Management Team established
• Developed a Recovery Action Plan
• Developed and implemented an MDT Co-ordinator competencies and training
package
• Worked collaboratively with CCGs to undertake ‘Deep Dives’ on challenged
tumour types

14. 1414
• Focus on Trust Performance and Trajectory
• Meet with challenged tumour groups every 6-8
weeks
• Attendees:
 Chaired by Director of Performance & Quality
from CCG
 Clinical Director for Cancer Performance (BH)
 Commissioning Support Unit
 General Manager
 Clinical Lead Service
• Break down on 2WW, 31 day, 62 day
performance and review any patients waiting
more than 104 days.
• Breaches broken down to -Avoidable vs.
Unavoidable
• Update on Cancer Recovery Action Plan
• REPEAT!

15. 15
Sample Data from Deep Dive pack
• The chart below shows a capacity challenge experienced in Colorectal
and how it was identified with reporting improvements

16. 1616
Approach to Improving Performance
• Clinical leadership and Senior Executive support in recovery
• Cancer Performance Management Team established
• Developed a Recovery Action Plan
• Developed and implemented an MDT Co-ordinator competencies and training
package
• Worked collaboratively with CCGs to undertake ‘Deep Dives’ on challenged
tumour types
• IST supported Cancer Care review + Demand and Capacity modelling

17. 17
Demand and Capacity Modeling
• Work was separated into 2 Phases:
 Phase 1 – Endoscopy
 Phase 2 – Two week wait clinic capacity refresh
• Process:
 The IST demand and capacity models were used
 The IST demonstrated the models to the operational teams locally
 Operational Teams were asked to populate the model
 Support was available via e-mail or telephone calls
 Meetings were arranged for IST to review populated models
• Benefits:
 The operational teams were able to assess the shortfalls in capacity in a scientific
way
 The model used was externally validated
 The model allows for scenario planning
 Robust data for business planning
 Shows variations in demand over the year
 For endoscopy the data can be modelled by type of test or total number of tests
17

18. 18
Example of an Endoscopy Demand & Capacity Graph
Table
Indicator Week
Approximate Sustainable Range 329 to 357
Mean Active Requests 327
Weekly ROTT 19
Mean DNAs Rebooked 1
65th Percentile (minus ROTT) 329
85th Percentile (minus ROTT) 357
You currently have 151 fewer point(s) available than requests per week plus DNAs minus ROTT
You currently have 171 fewer point(s) than required to sustain the service at a minimum level (65th percentile)
You currently have 199 fewer point(s) than required to sustain the service at a comfortable level (85th percentile)

19. 19
Example of a Two Week Wait Demand and Capacity Graph
Factors affecting capacity:
Indicator Week
Approximate Sustainable Range 31 to 33
Mean refs received 26
Mean DNAs Reappointed 1
75th
Percentile 31
85th
Percentile 33
0
5
10
15
20
25
30
35
40
1 3 5 7 9 111315171921232527293133353739414345474951
Patients
Week
Demand
75th Percentile 85th Percentile 2 Deviations Below
2 Deviations Above Referrals Mean
Factors which might reduce the amount of
capacity needed to meet demand (i.e. allow
setting capacity nearer to the 75th percentile):
- A good distribution of appointment offers (low
median waiting time)
- Pooling of referrals and the size of the speciality
- The ease with which you can flex capacity, for
example:
- Flex the timing of clinics (annual contract)
- If additional slots/clinics can be provided
quickly and easily
e.g. overbooking or ad hoc clinics
Factors which might increase the amount of
capacity needed to meet demand (i.e. require
setting capacity nearer to the 85th percentile):
- The very short waiting standard itself
- High variation in demand
- High variation in clinic capacity e.g. no absence
cover, bank holidays
- 'Carve-out' e.g. different hospital sites
- High levels of re-bookings and DNAs
- Not offering patient choice

20. 20
Current Position with Demand and Capacity
• Endoscopy work completed and validated beginning of February 2016
• Meetings arranged to validate remaining models
 Early involvement of the cancer data team is essential
 Provide the data for the operational team at the demonstration meeting
 Set timescales and future meeting date on the day of demonstration meeting

21. 2121
Approach to Improving Performance
• Clinical leadership and Senior Executive support in recovery
• Cancer Performance Management Team established
• Developed a Recovery Action Plan
• Developed and implemented an MDT Co-ordinator competencies and training
package
• Worked collaboratively with CCGs to undertake ‘Deep Dives’ on challenged
tumour types
• IST supported Cancer Care review + Demand and Capacity modelling
• Revised Cancer Operational Policy
• Performance forecasting tools with a
focus on backlog reduction

22. 22
Two Week Wait Breach Forecasting
04/04/2016 05/04/2016 06/04/2016 07/04/2016 08/04/2016 12/04/2016 13/04/2016 14/04/2016 15/04/2016
BLT Brain 1
Breast 2 7 11 1
Colorectal 3 1
Gynaecology 2 3 2 2 1 3
Haematology 1 1
Head and Neck 1 6 2
Lung 2 1
Skin 9 6 2
Upper GI 2 3 1 4 5 4
Urology 1 9 1
BLT Total 2 5 5 24 13 35 16
WX Brain 1
Breast 2 5 7
Gynaecology 1 2
Haematology 1
Lung 1 1 1 1
Upper GI 1 1 2 2 3 3
WX Total 1 1 1 1 4 7 9 11
NUH Breast 6
Colorectal 2 3
Gynaecology 2 2 2
Haematology 1
Lung 1
Upper GI 2
Urology 1 2 1
NUH Total 2 1 8 14
Data from 4 April 2016

23. 23
Live Two Week Wait Performance Report
Undated
Hospital Tumor Site Seen Breach % Seen Breach % Seen Breach % Seen Breach % Total
Brain 2 0 100% 1 0 100% 0 0 - 1 0 100% 4
Breast 183 0 100% 1 0 100% 149 0 100% 150 0 100% 28
Colorectal 118 2 98% 5 0 100% 46 3 93% 51 3 94% 2
Gynaecology 61 1 98% 0 0 - 36 3 92% 36 3 92% 3
Haematology 16 1 94% 0 0 - 3 0 100% 3 0 100% 0
Head and Neck 135 0 100% 0 0 - 64 2 97% 64 2 97% 22
Lung 47 1 98% 0 0 - 11 1 91% 11 1 91% 1
Paediatric 8 0 100% 0 0 - 1 0 100% 1 0 100% 0
Skin 141 4 97% 1 0 100% 66 1 98% 67 1 99% 22
Symptomatic Breast 162 0 100% 0 0 - - 0 0 - 0
Upper GI 78 6 92% 8 0 100% 31 5 84% 39 5 87% 15
Urology 64 1 98% 0 0 - 38 2 95% 38 2 95% 2
Standard 2WW 853 16 98% 16 0 100% 445 17 96% 461 17 96% 99
Breast 88 2 98% 0 0 - 58 2 97% 58 2 97% 8
Colorectal 99 5 95% 2 0 100% 37 4 89% 39 4 90% 9
Gynaecology 58 4 93% 4 0 100% 26 3 88% 30 3 90% 4
Haematology 8 0 100% 0 0 - 4 0 100% 4 0 100% 0
Lung 22 3 86% 4 0 100% 9 0 100% 13 0 100% 0
Symptomatic Breast 54 0 100% 0 0 - 0 0 - 0 0 - 0
Upper GI 74 2 97% 2 0 100% 18 1 94% 20 1 95% 2
Urology 65 0 100% 0 0 - 24 2 92% 24 2 92% 3
Standard 2WW 414 16 96% 12 0 100% 176 12 93% 188 12 94% 26
Brain 5 0 100% 1 0 100% 1 0 100% 2 0 100% 0
Breast 201 1 100% 24 0 100% 68 0 100% 92 0 100% 17
Colorectal 147 0 100% 0 0 - 55 2 96% 55 2 96% 0
Gynaecology 88 0 100% 5 0 100% 25 0 100% 30 0 100% 8
Haematology 8 0 100% 0 0 - 5 0 100% 5 0 100% 0
Head and Neck 129 1 99% 0 0 - 54 0 100% 54 0 100% 1
Lung 22 1 95% 0 0 - 9 0 100% 9 0 100% 5
Paediatric 1 0 100% 0 0 - 0 0 - 0 0 - 0
Skin 142 2 99% 4 0 100% 85 1 99% 89 1 99% 0
Symptomatic Breast 54 1 98% 6 0 100% - 6 0 100% 0
Upper GI 122 10 92% 3 0 100% 24 3 88% 27 3 89% 13
Urology 99 0 100% 1 0 100% 59 0 100% 60 0 100% 0
Standard 2WW 964 15 98% 38 0 100% 385 6 98% 423 6 99% 44
Overall Standard 2WW 2231 47 98% 66 0 100% 1006 35 97% 1072 35 97% 169
WX
Last Month: March - 16 Month to date: April - 16 Full MonthRemaining: April - 16
BLT
NUH
Data from 4 April 2016

24. 2424
244
54
-
50
100
150
200
250
Patients over 62 days Target Log. (Patients over 62 days)
Number of patients waiting ≥ 62 days on a cancer pathway
July 15 Aug 15 Sep 15 Oct 15 Nov 15 Dec 15 Jan 16 Feb 16 Mar 16
Reducing Backlog

25. 2525
Reducing Long Wait Pathways

26. 2626
Approach to Improving Performance
• Clinical leadership and Senior Executive support in recovery
• Cancer Performance Management Team established
• Developed a Recovery Action Plan
• Developed and implemented an MDT Co-ordinator competencies and training
package
• Worked collaboratively with CCGs to undertake ‘Deep Dives’ on challenged
tumour types
• IST supported Cancer Care review + Demand and Capacity modelling
• Revised Cancer Operational Policy
• Performance forecasting tools with a
focus on backlog reduction
• Whole pathway approach, breach analysis and clinical harm review

27. 27
Barts Health NHS Trust
Draft Suspected Prostate Cancer Timed Pathway
REFERRAL/1ST
APPOINTMENT
Day
0
14
DIAGNOSTICS/OPA/MDT
Day
15
42
TREATMENT
Day
43
62
GP 2WW Referral/Consultant Upgrade
Acute hospital presentation suspected cancer
1st
OPA
By day 7 – 1O and before day 14
Book OPA
(MRI)
(Biopsy)
(MDT)
If no cancer,
discharge or
routine clinic
Cancel
investigations
MRI and report
By day 18
TRUS biopsy
By day 21
MDT
By day 25
2
nd
OPA
Discuss diagnosis, further investigations,
treatments offered, Clinical trials
On or before day 30
Staging investigations:
Bone Scan, CT
On or before day 35
3
rd
OPA
Discuss test results,
treatment options
On or before day
42
Localised disease Advanced
disease
SMDT/Local MDT
On or before day 42
Radical
prostatectomy
(UCH)
By day 62
OPA at UCH
On or before day 42
Pre – op
assessment
Radical
Radiotherapy
(Barts)
By day 62
Oncology OPA
On or before day 42
RT Planning
Low grade disease /
patient choice
Active
surveillance
(All sites)
By day 62
Metastatic
disease
Hormones
Palliative RT
By day 62
Palliative
Care
By day
62
Ref : Draft Prostate Cancer pathway - Barts Health Care
Clinical referral
package to
specialist centre
Draft Prostate
Cancer
Pathway

28. 28
Results and Achievements?

29. 29
Cancer Waiting Times Standards Performance Scorecard
29
Data taken from Internal Data 07.04.16
Barts Health
Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 Quarter 1 Quarter 2 Quarter 3
Cancer Standards
14 day GP to first seen 90.7%
1,800
91.6%
1,908
95.7%
1,984
95.9%
2,213
95.7%
1,865
93.9%
1,925
95.8%
1,989
96.1%
2,160
97.4%
2,103
92.7%
5692.0
95.2%
6003.0
96.4%
6252.0
168 161 85 91 80 117 83 85 54 414.0 288.0 222.0
14 day GP breast symptoms
to first seen
98.8%
163
95.0%
200
96.7%
276
98.0%
355
96.3%
242
97.6%
286
95.8%
261
97.8%
314
97.9%
337
96.7%
639.0
97.4%
883.0
97.3%
912.0
2 10 9 7 9 7 11 7 7 21.0 23.0 25.0
31 days from decision to
treatment (first treatment)
97.2%
211
95.1%
225
96.7%
214
96.1%
257
95.8%
215
96.2%
261
96.9%
290
97.9%
241
98.2%
222
96.3%
650.0
96.0%
733.0
97.6%
753.0
6 11 7 10 9 10 9 5 4 24.0 29.0 18.0
62 day GP to treatment (inc.
31 day for urgent)
77.6%
105.0
72.5%
103.5
77.2%
96.5
77.9%
122.0
76.8%
99.0
74.9%
109.5
86.2%
141.0
83.9%
99.5
87.1%
105.0
75.7%
305.0
76.6%
330.5
85.8%
345.5
23.5 28.5 22.0 27.0 23.0 27.5 19.5 16.0 13.5 74.0 77.5 49.0
62 day Screening to Treatment 87.0%
23.0
80.0%
20.0
82.2%
22.5
90.9%
22.0
100.0%
15.0
95.5%
22.0
90.5%
21.0
100.0%
17.0
91.3%
23.0
83.2%
65.5
94.9%
59.0
93.4%
61.0
3.0 4.0 4.0 2.0 0.0 1.0 2.0 0.0 2.0 11.0 3.0 4.0
62 days from consultant
upgrade to first treatment.
Target not yet set
78.9%
9.5
65.5%
14.5
76.0%
12.5
90.9%
11.0
87.9%
16.5
85.3%
17.0
85.7%
17.5
90.0%
20.0
87.2%
23.5
72.6%
36.5
87.6%
44.5
87.7%
61.0
2.0 5.0 3.0 1.0 2.0 2.5 2.5 2.0 3.0 10.0 5.5 7.5
31 days from decision to
treatment (subsequent
treatments, drugs)
100.0%
7
100.0%
85
100.0%
109
100.0%
172
100.0%
131
100.0%
156
100.0%
128
100.0%
94
100.0%
57
100.0%
201.0
100.0%
459.0
100.0%
279.0
0 0 0 0 0 0 0 0 0 0.0 0.0 0.0
31 days from decision to
treatment (subsequent
treatments, surgery)
95.2%
21
92.3%
13
96.0%
25
97.6%
42
100.0%
43
96.9%
32
97.9%
47
97.4%
38
100.0%
36
94.9%
59.0
98.3%
117.0
98.3%
121.0
1 1 1 1 0 1 1 1 0 3.0 2.0 2.0
31 days from decision to
treatment (subsequent
treatments, radiotherapy)
96.5%
115
96.4%
112
97.6%
124
99.1%
110
94.3%
105
96.3%
108
100.0%
129
98.2%
112
100.0%
91
96.9%
351.0
96.6%
323.0
99.4%
332.0
4 4 3 1 6 4 0 2 0 11.0 11.0 2.0

30. 3030
• Endoscopy and Histopathology are pinch points: PTL
• 6 monthly review of demand and capacity
• Improve IT systems / have one version of Cancer database
• Commence Local hospital site Clinical Cancer Boards
• Develop Cancer Sustainability Action Plan
• Look at developing eLearning for all relevant Trust staff
• Working with our ITT providers and pathway improvements
Next Steps for Sustainability

31. 31
Continuing Challenges
31
Internal
• Internal HDU and bed availability
• Diagnostic capacity
• Competing pressures, e.g. 18 Weeks, Emergencies
External
• Increased scrutiny and reporting requirements
• Impact of industrial action

32. 32
LEARN
D&C
MODELLING
TRAIN
ANALYSIS
Data
STRUCTURE

33. 3333
Questions?