Transcript ACUTE ONCOLOGY SERVICE MODELS Overview

ACUTE ONCOLOGY SERVICE MODELS
Dr Judith Carser
Consultant in medical oncology
Southern Health & Social Care Trust
Overview

AO workload projections

AO models in England

Merseyside & Cheshire experience and workload analysis

Clinical case examples
Projected AO workload

2006/07 - 273,000 unplanned cancer admissions = 750 admissions
per day in England1

Equates to 5 cancer admissions per trust per day on average

2008/09 average LoS varied for cancer related admissions between
5.1-10.1 days - potential saving of 566,000 bed days if every region
had the same LoS as average in the best performing regions 2

One day snapshot at combined cancer centre/acute hospital trust
reported 19% of all in patients had a cancer diagnosis3

Average Los for those admitted to oncology was shorter than for those
admitted to general medicine3
1NCEPOD
report 2008
Office.DoH:Delivering the Cancer Reform Strategy 2010
3Acute Oncology Service: assessing the need and its implications. Clin Oncol 2011 Mansour D et al
2National Audit
AO models in UK

Core principles of AO promote education, awareness and early access
to specialist oncology advice

Number and type of AO admissions variable and will reflect local
service configuration

AO models should be configured to best meet local needs and
integrate with existing services whilst identifying areas for development

Acute district general hospital vs. integrated cancer centre vs. stand
alone tertiary oncology service
Model I – comprehensive cancer centre


Yorkshire Cancer Network – 2.6 million, 8000 new patient episodes/yr.
Non-surgical oncology –St James Institute of oncology – local services
for Leeds and tertiary referral centre for region. Acute services on site

Six additional hospital trusts providing cancer unit services with mix of
resident and visiting oncologists

AOS developed independently in each cancer unit by the resident
oncology team

In Cancer centre – assessment unit staffed by ANPs and junior
doctors. Model requires 20PAs of consultant time to provide a 5 day
service – equivalent to 2 FTEs
Model II – An acute cancer unit model,
Whittington Health

Stand alone consultant medical oncologist, specialty doctor in
oncology, haematology consultant and 2 oncology CNS, admin support

Dedicated medical ward for oncology-related admissions with medical
oncologist responsible for inpatient care – admission guidelines

Daily AOT review offered of appropriate patients in outlying medical
wards / MAU


Electronic referral pathways – inbuilt audit trail and data gathering
capacity.
Electronic alerts for chemotherapy patients / fast track MUO clinics /
weekly CUP MDT / radiology flags
Model III – stand alone cancer centre


Merseyside and Cheshire Cancer network – population 2.3 million,
10,000 new patient episodes/yr.
Tertiary stand alone Cancer Centre – no acute services on site. Local
cancer services for Wirral

Nine satellite chemotherapy clinics, one satellite radiotherapy unit

AOS developed in all 7 acute trusts in 2010 (excluding IoM) to
complement existing service in St Helens and Knowsley NHS Trust

ANP-led Acute oncology assessment ward, CCC established 2013
Location of AOS within acute
trusts Merseyside & Cheshire
SORM
UHA
WTH
Key:
s
s
s
SHK
W&H
RLUH
CCC
COC
CCC – The Clatterbridge Cancer
Centre NHS FT
WTH – Wirral University Hospitals
NHS FT
UHA – University Hospital Aintree
NHS FT
SORM – Southport & Ormskirk NHS
Trust
RLUH – Royal Liverpool & Broadgreen
NHS Trust
W&H – Warrington & Halton NHS
Trust
SHK – St Helen’s and Knowsley NHS
FT
COC – Countess of Chester NHS
Trust
Model III – acute oncology services

Local AOS with visiting oncologists (at least 2 per unit), 5PAs of
consultant support provided per week. The AOS oncologists provide at
least one site specialised service at the same trust

At least 1 WTE acute oncology CNS, 0.6-1.0 WTE admin support

No inpatient oncology beds, no acute trust employed oncology nurses

AO service available mon-fri 9am – 5pm to review patients as necessary
and within one working day of referral

Local AO and CUP MDTs
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Central 24hour chemotherapy triage at Cancer Centre
Comparison of projected (2005-6 data) vs. actual workload of AOS
throughout network (2010-11)
- NatCanSAT commissioned to provide analysis of potential annual AO
workload – HES, chemotherapy, radiotherapy data, Cancer Registry
Projected potential workload = 3,924 patients, overall average LoS 12.8 days
Type of admission
Average LOS days (range)
1.new cancers (17%)
11 (7.5-16.1)
2.complications of cancer treatments (40%)
9.1 (5.7-14.1)
3.complications of cancer (43%)
17.3 (10.2-23.5)
Network AO workload 2010-11

Actual workload = 3,031 new referrals to 7 teams (incomplete 12
months for 3 teams)
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Average Los reduced by 3 days from 12.8 to 9.7 days representing
saving of over 9,000 bed days
Impact of AO intervention
Type of intervention
Major
•
•
% patients
•
•
•
•
Intermediate
•
•
•
Minor
•
•
n=1,403
major vs. intermediate intervention, p<0.05;
major vs. minor intervention p<0.05
Managing new cancers
(including MU0)
Managing complications of
chemo/radiotherapy
Organising diagnostic tests
Cancelling or preventing
unnecessary tests
Symptom management
Preventing admission
Referral to other teams
including cancer centre/other
hospitals
Psychological support
Communication to primary
oncologists/others
Supervising progress of
inpatients
Organising follow up
Wirral experience - AOS
Griffiths R et al Wirral University Hospitals NHS Foundation Trust
New cancer referrals– Royal Liverpool University Hospital AOS
2010-11
Seen by AOS
2010 - 2011
Number
Gender
135
Male
female
71 (53%)
64 (47%)
Median age in yrs (range)
73 (37-92)
Final
diagnosis
Malignancy undefined origin
cCUP
Lung
Breast
Upper/lower GI
Urology
Gynae
Other
32 (24%)
18 (14%)
40 (30%)
6 (4%)
14 (10%)
6 (4%)
7 (5%)
12 (9%)
Median
survival
Admission – death (95% CI)
Discharge – death (95% CI)
61 days (48-74)
37 days (20-54)
Deaths in hospital
27 (20%)
Systemic therapy
Radiotherapy
22 (16%)
12 (9%)
Impact of an AOS upon the management of
patients with MUO – Wirral University Hospital
experience
Non-AO Cohort
Endoscopy
18
AO Cohort
p=0.028
p=0.114
16
14
Radiology
12
p=0.037
10
8
16.9
13.1
6
Tumour
Markers
4
p<0.001
2
0
Non-AO Cohort
0
AO Cohort
2
3
4
5
Number of investigation requests per patient
Mean LoS for patients admitted during the
diagnostic phase
Griffiths RW. et al, abstract NCRI 2012
1
Mean number of investigations during the
diagnostic phase
Wirral University Hospitals NHS Foundation trust
Comparison of historical and AO cohort
at Wirral University Hospital
Definitive Therapy
14%
12%
10%
p=0.098
8%
11.5%
4%
4.3%
2%
27
Decision on Best
Supportive Care
6%
71
29
12
p=0.001
p<0.0001
Non-AO
Cohort
AO Cohort
0%
Non-AO Cohort
AO Cohort
Proportion of patients dying without a clear
decision on management
Griffiths RW et al abstract NCRI 2012
0
20
40
60
Time from Referral (days)
80
Average time from referral until definitive
treatment decision
Wirral University Hospitals NHS Foundation Trust
Local agreements
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Each acute Trust responsible for developing their own AOS which best
meets local needs including geographical location, demographics,
specialist service provisions
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Ongoing engagement between acute trust and tertiary Cancer Centre
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Local AO and CUP MDTs
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Local AO steering groups
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Local teaching and staff education
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Local policies and procedures for referrals and patient alerts
Network agreements
Required to meet National Cancer Peer Review measures for both
carcinoma unknown primary and acute oncology including:
 AO induction packs
 Network treatment and disease related complications protocol book
 AO and CUP clinical network groups
 Specialist regional CUP MDT
 Network agreed pathways for MUO, brain metastases
 AO e-learning module supported by University of Liverpool
 Network audits e.g. MSCC, neutropenic sepsis
 Agreed oncology registrations for all AO patients
 Network agreed minimum data set
Clinical scenarios

Patient 1: 54-year-old woman with breast cancer is undergoing
adjuvant chemotherapy and develops nausea and dizziness. The
patient has a temperature of 38ºC and phones the chemotherapy
helpline for advice

Patient 2: 72-year-old man presents to ED generally unwell with
abdominal pain, nausea and weight loss. CT scan reveals multiple liver
metastases but no obvious primary cancer

Patient 3: 61-year-old woman with metastatic lung cancer presents
with increasing pain. Patient had been due to attend cancer centre for
radiotherapy but admitted acutely to local hospital
Summary
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There is proof that AOS works (and saves money!)
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An evolving service which must adapt to local requirements
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A successful AOS requires ‘buy-in’ and commitment from all
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Should be developed alongside existing visiting oncology services to
provide continuity of care / reduce time travelling for oncologists
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Cancer unit oncologists vs. visiting oncologists with more time in unit
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Team effort – service must be adequately staffed, resourced and
supported if it is to succeed and develop
References

The National Confidential Enquiry into Patient Outcomes and Death. For better, or worse? NCEPOD,
2008

National Chemotherapy Advisory Group. Chemotherapy Services in England: ensuring quality and
safety, 2009

Royal College of Physicians and Royal College of Radiologists. Cancer patients in crisis: responding
to urgent needs, 2012

Towards saving a million bed days: reducing length of stay through an acute oncology model of care
for inpatients diagnosed as having cancer, BMJ Qual Saf 2011: 20:718-724. King J et al.

What is the impact of a new acute oncology service in acute hospitals. Experience from the
Clatterbridge Cancer Centre and Merseyside and Cheshire Cancer Network, Clinical Medicine 2013,
Vol 13, No 6: 1-5. HL Neville-Webbe , JE Carser et al.

Acute oncology service: assessing the need and its implications.Clin Oncol (R Coll Radiol)
2011;23:168-173. Mansour D et al.