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Showcase: Reducing Variations in lung cancer pathway
Donna Chung
Head of Centre for Cancer Outcomes, North Central and East London Cancer Alliance
27 January 2020
CRUK Strategic Intelligence Forum
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Outline
Use data to change practice and track implementations
Setting the scene
Work in partnership to deliver Cancer Long Term Plan
• Gather collective wisdom across alliance to reduce variations in care
• Use of Pathway Tool to select and measure of outcomes
• Support organisational development, influence practice through data dashboards encompassing operational performance, treatment, outcomes and patient experience data
• Variations in 5 year survival in North Central and East London
• How data on variations in care has improved outcomes in lung cancer
• Current challenges
• Addressing quality of COSD data locally
Part 1
Part 2
Part 3
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Variations in 5 year survival 5 year survivals for NCEL patients, followed up to 2016 by tumour groups
Source: ONS
(*) Age-standardisation cannot be based on the complete five age groups but four instead. The age range that fails one of the robustness criteria is combined with a neighbouring age range before the age standardised figure is calculated. (:) Where it was not possible to age-standardise, the unstandardised estimate has been presented instead.
Opportunities to improve 5 year survival by: - increasing proportion of early stage diagnoses
- identifying and addressing variations in (radical) treatment rates - ensuring universal and timely access to molecular testing, enabling optimal use of innovative treatments
Five year survivals Patients in
NCEL NS (%)
95% CI Patients in Eng
NS (%) 95% CI
Opportunities to reduce variations Lower Upper Lower Upper
Bladder 1,490 48.7 : 44.4 52.9 42,861 56.4 55.6 57.2 Significantly below England
Colorectum 5,845 58.1 56.2 60.1 164,980 60.5 60.1 60.9 Borderline below England
Kidney 1,730 65.5 * 61.6 69.6 46,918 60.8 60.0 61.5 Significantly above England
Lung 7,101 16.7 * 15.3 18.1 179,060 15.2 14.9 15.5 Borderline above England
Myeloma 1,156 53.9 * 48.9 59.5 22,249 51.4 50.3 52.6 Similar to England
Non-Hodgkin's lymphoma 2,289 67.0 : 64.0 70.0 54,391 66.9 66.2 67.6 Similar to England
Oesophagus 1,173 16.0 : 13.0 18.9 36,075 16.6 16.0 17.3 Similar to England
Stomach 1,182 25.4 : 22.0 28.9 27,496 21.3 20.6 22.1 Borderline above England
Breast 8,688 84.2 82.4 86.1 203,983 86.0 85.7 86.4 Similar to England
Cervix 568 77.8 : 73.7 81.9 12,716 61.3 59.6 63.0 Significantly above England
Prostate 7,564 89.6 * 87.8 91.4 193,518 88.3 87.9 88.7 Similar to England
Uterus 1,682 76.1 : 72.9 79.2 36,632 76.7 75.9 77.5 Similar to England
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How data on variations in care has improved outcomes Trends in one- & five- year net survival & surgical resections
Sources: S Walters et al . Br J Cancer: 2015;113(5):848-60 (updated) & D West, Society of Cardiothoracic Surgeons
Hybrid-based prediction
First audit report
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Proportion (%) of stage I & II NSCLC patients receiving surgery; England and Wales 2016
%
Source: National Lung Cancer Audit 2017
Trust first seen
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Age-standardised rate of emergency route to diagnosis for lung cancer by CCG in England, 2006-2015
Source: National Cancer Registration and Analysis Service: www.ncin.org.uk
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Reducing variations requires collective wisdom across a cancer alliance
Data is integral to help us change practice…
Avoid blind spots & lop-sided solutions
Think beyond ‘top down’ vs ‘bottom up’ change
Don’t pilot and push out when seeking to spread
Bring together all the skills & perspective needed
Improvement needs action at all levels
Nurture peer networks to enable iterative learning
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Events from referral to treatments before death in lung cancer patients (single trust)
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Events from diagnosis in deceased lung cancer patients (single trust)
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A&E attendances pre- and post- diagnosis for deceased lung cancer patients: single trust view
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Lung cancer patients with surgery as first treatment (2015-17) – volume of activities and median days
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Lung cancer patients with surgery as first treatment (2015-17)
– volume of activities and median days
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Lung cancer patients with surgery as first treatment (2015-17) – volume of activities and median days
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Data completeness - patients characteristics
Trust level COSD dashboard – can filter by tumour groups, first seen trusts and date of diagnosis
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R Dashboard feeding COSD Level 2 data back to NCEL MDTs
Evaluate data as close to real time as possible
Data completeness over time
COSD L2 metric
Alliance Trust
Tumour Gp
Boxplot comparison with England and alliance
Export data tables
SPC for variation in data completeness over time
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Data is integral to help us change practice
Bring together all the skills & perspective needed
Improvement needs action at all levels
Nurture peer networks to enable iterative learning
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Data is integral to help us change practice
This work uses data provided by patients and collected by the NHS as part of their care and support.
makes the rich cancer registry data more accessible,
potentially to the whole Cancer community.
Gives ‘infinitely’ flexible insights into variations in care. Potentially a way to produce
audits in the future.
Peer networks plays an important role in quality
improvement
The pathway tool
Requires analytical support and addressing data lag