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30 days SACT UK
Alfredo Addeo
Lung NSSG 15th November 2016
Background
• Cancer chemotherapy has been provided in the NHS for decades
• Accurate, timely and complete data collection is now seen as a
priority and this can be assisted by e-prescribing systems
• The introduction of the Systemic Anti-Cancer Therapy (SACT)
Information Standard (ISB 1533)
• Collection and submission of SACT data is specifically
incorporated in the England NHS Standard Contract
SACT dataset applies to:
All organisations providing cancer chemotherapy services in
or funded by the NHS in England and includes:
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all cancer patients,
adult AND paediatric
acute inpatient, daycase outpatient settings and
delivery in the community;
Includes oral chemotherapy
Covers chemotherapy treatment for:
• all solid tumours
• haematological malignancies
• and includes those in clinical trials
SACT dataset
• Consists of 6 sections across 42 data items:
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Demographics & Consultant
Clinical Status
Programme & Regimen
Cycle
Drug Details
Outcome
Who?
Public Health
England CKO
Chief Knowledge
Officer
Disease Registration
National Director for
Disease Registration
NCIN (PHE)
Directors
Dr Ken
NCIN
Lloyd
and Sue
Clinical
Forsey
Information
Principal
Specialists
developers of
the SACT
CCIG
Chemotherapy
Clinical Information
Group
Pharmacist
Support
SACT
Programme Board
CIU Core Team
SACT
Programme Manager
SACT
Snr. PH Analyst
SACT
Trainer/Liaison
SACT
Senior Public Health
Data Clerk
SACT
Project Manager
SACT
Senior Public Health
Data Clerk
SACT
Systems Developer
Allows additional scrutiny of clinical
decisions
Ineffective drug?
or insufficient dose
of effective drug?
SACT Dataset
young : old
stage : performance status : co-morbidity
Clinica
l status
age
benefit
- curative treatment
- disease control
- symptom control
Optimal choice of
clinical management
for desired outcome
toxicity
Regimen
&
delivery
recording regimen and detail correctly is critical
- stopped early
- dose modified
- treatment delayed
also:
• To describe the level and variation of 30 day
mortality following SACT on a national levelidentified as quality measurement tool
• To highlight the potential to use SACT data to
monitor and improve cancer patient care and
outcomes and enhance the data quality and
reporting by trusts to that end
National SACT data
• Published in the Lancet Oncology Sept 2016
• Data collected for patients treated between January –
December 2014
• 28,400 women with breast cancer
• 15,000 patients with lung cancer
• NHS began submitting data in April 2012, and it became
mandatory in April 2014
• This paper + companion report- 1st major output from this
data source
National SACT data
SACT DATA 2014
• Palliative intent:
• Breast – death within 30 days: 7.5%
• Lung – 10%
• Curative intent:
• Breast – 0.3%
• Lung – 2.9%
National SACT data
England’s 30-day chemotherapy mortality: a
measure of quality of care?
1. despite this initiative to collate national data for cancer
chemotherapy, there were significant gaps and deficiencies in
the national dataset.
2. it remains a tragedy that we still cannot get complete national
(anonymised) datasets to inform clinicians and patients and to
drive real improvements in patient care.
3. This study sets a standard for what health-care systems should
achieve: to routinely record, collate, and report at a national
level the negative consequences of medical interventions to
improve the quality of health care.
Brest Cancer curative
Figure 2
Funnel plot of variation in risk-adjusted 30-day mortality in patients with breast cancer given systemic anticancer therapy with curative
intent, by hospital trust
Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8% confidence interval
boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality rate.
NSCLC curative
Figure 4
Funnel plot showing variation in risk-adjusted 30-day mortality in patients with non-small cell lung cancer given systemic
anticancer therapy with curative intent, by hospital trust
Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and 99·8%
confidence interval boundaries that are represented as grey lines. Red line shows national risk-adjusted 30-day mortality
rate.
NSCLC palliative
Figure 5
Funnel plot showing variation in risk-adjusted 30-day mortality in patients with non-small cell lung cancer
given systemic anticancer therapy with palliative intent, by hospital trust
Each circle represents a separate hospital trust; blue and red circles represent outliers beyond the 95% and
99·8% confidence interval boundaries that are represented as grey lines. Red line shows national riskadjusted 30-day mortality rate.
Summary of 30-day mortality rates in patients with
breast or lung cancer by treatment intent
Data are n (%) of total patients by cancer type and treatment intent; and n (%) of deaths
occurring within 30 days of systemic anticancer therapy for each of those groups.
30-day mortality rates in patients with lung cancer by morphology
and treatment intent
Data are n (%) of total patients by lung cancer type and treatment intent; and n (%)
of deaths occurring within 30 days of systemic anticancer therapy for each of those
groups. NSCLC=non-small cell lung cancer. SCLC=small cell lung cancer.
• 1st important insights into 30-day mortality in
a large, representative population of patients
with breast or lung cancer receiving systemic
anticancer therapy in England.
• Some trusts having significantly higher rates
for early mortality, the reasons require further
investigation
Conclusion
Media Reaction
1) NEW STUDY FINDS CHEMO KILLS 50% OF
PATIENTS IN FIRST 30 DAYS
2) LANDMARK STUDY SHOWS HALF OF CANCER
PATIENTS ARE KILLED BY CHEMO — NOT CANCER
LIMITATIONS
1) Submission data mandatory only form
april 2014.
2) Possible wrong coding.
3) SACT number for 2014 much lower than
real?
National SACT
• Data being sent to PHE not a reflection of
true 30 day mortality
• Disparity in number of patients treated
compared to national SACT data
• Possible improvement with increased
clinical engagement.
Conclusions