Tamsin Hill, Macmillan Acute Oncology Service, Southampton General Hospital

1. Development of a traffic light alert system to improve
referral processes within Southampton Macmillan Acute
Oncology Service
Aim:
To develop and pilot a traffic light alert system that is universally
understood, accurately reflects service availability, ensures service
accountability, and has potential to expedite discharge processes.
Introduction:
Macmillan Acute Oncology Service (MAOS) has grown into a 7-bedded
24/7 unit, receiving a high volume of referrals for assessment/admissions
including patient/carer self-referrals and many referrals from health care
professionals (HCP), such as Clinical Nurse Specialists (CNS).
MAOS has identified difficulties in service provision including:
• highly variable workload,
• no clear agreement among HCPs about referral criteria
• how ‘out of scope’ requests are managed
Action was needed so professionals referring to MAOS understand the
current pressures on the service and take appropriate action accordingly.
Traffic light systems are universally understood. This algorithm based application was
designed to reflect service availability and expedite the discharge process.
We are currently trialling the application. Outcomes being measured are:
• ease of use,
• safety,
• accuracy in reflecting current availability to accept referrals,
• improvement in communication and clarity between referrers and MAOS,
• bed manager and consultant engagement in expediting discharges within cancer care.
The survey and focus group confirmed the
problems (given in the introduction), in
particular highlighting the lack of agreement
among HCPs about referral criteria.
Non-availability of information for referrers
about the current capacity of MAOS to accept
referrals and the apparent variability of
responses to referrals was the biggest source
of frustration and misunderstanding for
referrers.
The application developed is a single web
based page for touch screen, taking around 10
seconds to complete/update. It is available for
demonstration at the conference. A screen
shot of the application is shown in Figure 1.
Example outcomes are shown in Figure 2.
Data was collected from MAOS users to
identify and prioritise the difficulties and
successes in the referrals process by
(i) Questionnaire based survey of 3
groups (site specific CNS’, MAOS staff,
and other referring HCPs, and
(ii) a focus group of MAOS staff.
From these results, an algorithm using
parameters with corresponding
numerical values was developed into an
application for piloting within MAOS.
The parameters and values were initially
developed within the focus group and
further defined by the author.
Software development was externally
undertaken at no cost.
Discussion
Background Methods Results
Hill T, Fenton P & Johnson K. Macmillan Acute Oncology Service, University Hospital Southampton NHS Foundation Trust.
email: tamsin.hill@uhs.nhs.uk
Patient Flow:
The ability to deal with new patients is
affected by whether patients can be safely
returned home or moved elsewhere within
the hospital.
This is the biggest source of frustration for
MAOS staff and referrers.
With thanks to Dr P Fenton and Dr E Killick (both UHS) for their support. I gratefully acknowledge the contribution made by Dr Q Hill (Arqiva) and Dr GM Hayes (KCL).
Bed Availability:
Patient flow is dependent on bed availability.
Lack of bed availability is the biggest source
of frustration for MAOS staff and referrers.
Acuity:
MAOS staff felt high acuity level
reflected the inability of staff to deal
with incoming patients. An example
of this is the need to hold a patient
until an ITU bed becomes available.
At this point there are no staff
available to accept further patients
Phone calls:
MAOS manages patients in the community.
Peaks in phone calls mean one nurse
practitioner if fully utilised dealing with
telephone enquiries and screening.
Figure 1: MAOS traffic light alert application screen view
To Come In List:
Managing this list is as important
and takes as much time as dealing
with the patients you have in the
hospital. Telephone triage and risk
assessment is of critical
importance.
Status Action
Green
• Emergency reviews
• Elective and non-urgent cases
• Nurse practitioner-led reviews- full assessment and clerking
• Assist other clinical areas
Amber
• Prioritise urgent reviews
• Nurse practitioner-led reviews focussed on targeted emergency
assessment
• Quick reviews
• Stagger non-urgent jobs
• Referrers to consider CNS-led management
Red
• Emergencies only
• Referrers to consider CNS, clinic reviews
• Manage patients at home/in the community
• Teams to prioritise those in AOS in ward rounds
• Book for next day review
• Bed manager informed
Black
• All emergencies to nearest ED
• Manage other patients at home if possible
• Divert/postpone electives
• Ops to be informed – to review patients and identify those fit for
discharge
Figure 2: Example outcomes – modifiable for individual sites
If the aims of the alert system are met by the pilot:
• The alert system will be embedded within Southampton MAOS
• The hospital site management team will have an accurate reflection of MAOS current
availability to accept and review patients
• The alert system could be used in other acute assessment areas within the trust, such
as Acute Surgical Unit
• Other Acute Oncology Services could use this or a modification to meet their needs.
Future