1. How clinicians use data to make an impact on clinical outcomes
Prof Chris Holcombe, Breast Surgeon
Dr Mick Peake
Clinical Lead, National Cancer Intelligence Network

2. NCIN core objectives
Promoting efficient and effective data collection throughout the cancer journey
Providing a common national repository for cancer datasets
Producing expert analyses, based on robust methodologies, to monitor patterns of cancer care
Exploiting information to drive improvements in standards of cancer care and clinical outcomes
Enabling use of cancer information to support audit and research programmes

3. The History of Cancer Data
There is no data
The data is rubbish
Now
Lots of data
Increasingly good quality
The Challenge is to use it effectively

4. Main elements of clinical engagement
Identification of key clinical issues & priorities
‘Ownership’ of data:
Dataset development & revision
Championing data collection QA
Clinical input into the analytical programme
Advice on ways of reporting data
Communication – colleagues; professional bodies, providers; commissioners
Promoting the use of routine data in research

5. What clinicians use data for
Audit of their practice and that of their MDT
In discussions within their Network (Peer Pressure)
Comparing their activity and outcomes against national ‘benchmarks’
As part of Peer Review
To support local research
For professional revalidation
To change things!

7. Primary lung cancer resections (n=116,148)
6,000
National Lung Cancer Audit
first report
5,000
4,000
Number of procedures
3,000
2,000
1,000
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1992
1993
1994
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
1995
Calendar years
Financial years
Year of surgery
Source: R Page & Doug West, Society of Cardiothoracic Surgeons Audit 2013

8. Primary lung cancer resections (n=122,408)
6360
6,000
National Lung Cancer Audit
first report
5,000
4,000
Number of procedures
3,000
2,000
1,000
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1992
1993
1994
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
1995
Calendar years
Financial years
Year of surgery
Source: R Page & Doug West, Society of Cardiothoracic Surgeons Audit 2013

9. Source: National Lung Cancer Audit 2014

10. Case-mix (risk) adjustment
Age
Fitness &
Co-morbidity
Disease
stage
Social
Deprivation

11. Risk Adjustment (30-day post-operative mortality colo-rectal cancer 2008-2010)
NCIN 2013

12. Resection rate for patients with tissue confirmation of NSCLC (2004-2008:England)
First seen in centre with thoracic surgery?
Number
With a tissue diagnosis
of NSCLC
Number who had surgical resection %
having surgery
Adjusted Odds Ratio for surgery*
P value No
25,248
2,947
12%
1.00
Yes
9,265 (27%)
1,538
17%
1.51 ( )
<0.001
*adjusted for sex, age, PS, stage, deprivation index
and Charlson co-morbidity index
Rich et al; Thorax 2011;66:

13. Hazard ratio of death after surgery by hospital volume
0-30 days
days
>365 days
Hospital volume HR
95% CI
<70
1·00 -
70-99
0·81
0·58-1·13
0·82
0·70-0·96
0·95
0·83-1·09
0·75
0·52-1·08
0·92
0·78-1·09
0·94
0·81-1·08
0·91
0·64-1·31
0·78
0·66-0·93
0·97
0·84-1·13
150+
0·58
0·38-0·89
0·80
0·67-0·95
0·84
0·71-0·99
χ2(1 df)
3·24
5·93
2·67
p-value
0·07
0·01
0·10
Based on shared frailty model adjusted for age, sex, socioeconomic deprivation, Charlson comorbidity score, resection quintile and hospital volume (random effect)
Lüchtenborg et al. J Clin Oncol 2013;31(25):3141-6

14. Resection volume and survival
χ2=8.1; p<0.01
HR: 0.78
( )

15. Consultant Outcomes Programme Thoracic surgical outcomes
NHS England
Consultant Outcomes Programme
Thoracic surgical outcomes
Acknowledgement: Richard Page,
all Thoracic Surgical Units and The HSCIC

16. Numbers of procedures per Unit

17. Numbers of procedures per surgeon
Mean = 34
Median = 30

18. So the question is?

19. What should we do with this data?
What would you do?
By Centre
By Surgeon
Thyroid Cancer in Merseyside and Cheshire

20. Markos 1989, Holden 1992 Pierce 1994, Bolliger 1996 about 40-50%
Garzon 25 ptsover 5 years FEV1< 0.8L or 50% pred, 13 lobe and 12 wedge,no surgical mortality , 1 yr SR 80%
Griffin 31 pts FEV1<2L!!! Treated by wedge 10y SR similar to normal PFTs going for lobectomy!
Kilic operative mortality for surgery is 4.8% for lobectomy in the elderly
Licker, copd pts who go for surgery has a 15% - 18% resp complication rate
Linden 100pts 22 anatomical resections, rest wedges, with preop FEV1< 35% predicted had SPNs removed (57% lung cancer) 1 inhospital / 30 day mortality
Magdeleinat 106 pts with FEV1<50%, periop mortality 8.9%
Shennib 65 pts with FEV1<40%, VATS wedge, conversion in 10 (17%)

21. Colo-rectal cancer - Indicator I 1 year crude survival
Source: E Morris, P Finan et al, Leeds

22. Colo-rectal cancer - Indicator III 30-day postoperative mortality
Source: E Morris, P Finan et al, Leeds

23. Colo-rectal cancer - Indicator IV Odds of an APE
Source: E Morris, P Finan et al, Leeds

24. Conclusions
Ensuring the best outcomes of clinical practice and service configuration is highly dependent on robust data
Clinicians have to take seriously their part in data collection
We need to expand the size of the clinical community engaged with cancer data - feedback and ongoing interaction with clinicians is an essential part of the process
Every MDT should have at least one senior clinician responsible for overseeing data collection and feedback
High quality population-based data can clearly drive clinical behavioural change – and is now impacting on outcomes for patients

25. Changing the Culture
We all are involved with cancer diagnosis, treatment, commissioning or assessment
Next time you see an audit or a data set
Pick one item where you, or your unit or hospital could improve and set about changing it.

26. Using Data for the ruthless pursuit of excellence
Jacob Rees-Mogg
Stiffen your sinews, imitate the actions of a tiger, not like………………..

27. Bagpuss