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The aim of the study was to evaluate the effectiveness of
the new workflow in terms of reducing errors.
Material and Methods
Since April 2016, a paperless workflow has been
introduced for each area of the pathway including;
referral, data capture at CT, planning information and
treatment information up to the last fraction. A focus
group was formed to investigate the options available for
recording the required information at all stages. These
included using an electronic referral and booking form,
dynamic documents for recording treatment setup details,
electronic journals for recording actions and histories
throughout the treatment and toxicity scoring. All checks
required on before, during and after treatments were
assigned as tasks or checklists and these were made into a
standardised automated protocol.All errors at our centre
are recorded electronically on a centralised incidence
reporting system. The numbers of error occurrences that
happened 3 months before and after the introduction of
the process were analysed.
Results
In total, there were 51 and 49 radiotherapy related
incidents recorded before and after the introduction of
the paperless workflow respectively. The number of
incidents related to transcription errors decreased from
29% (15/51) to 16% (8/49) since the paperless change. It’s
noted that there was a small rise in reported incidences in
other areas of the pathway due to a change in work
procedure.
Conclusion
It’s suggested the number of transcription errors was
minimised through the adoption of the paperless
workflow. It’s also proved to be beneficial to have a
centralised electronic incident reporting system to
monitor and review incidents in a radiotherapy
department, in order to streamline and optimise existing
patient pathways.
PO-1023 Reducing waiting room times - A 5 year
review of an in-house KPI tool
A. Wallis
1
, D. Moretti
1
1
Liverpool Hospital, Radiation Oncology, Liverpool,
Australia
Purpose or Objective
Patient waiting times has a significant impact in a
patient’s overall satisfaction of their healthcare
experience (1). The main contributors to patient waiting
times are inadequate appointment duration, staff
experience level, patient late arrival and machine
breakdowns (1). Literature on radiation oncology
productivity is dominated by variation and validation of
the basic treatment equivalent (BTE) model (2). However,
the technological advancements in imaging and treatment
modalities such as intensity modulated radiation therapy
(IMRT), image guided radiotherapy (IGRT), volumetric RT
(VMAT) and Tomotherapy have changed the landscape of
RT and its productivity measures (4).
In 2011, the management team at Liverpool and
Macarthur Cancer Therapy Centres (LMCTC) introduced an
in-house key performance indicator (KPI) tool to measure
the performance of the treatment machines. The catalyst
for the design and implementation of the tool was the
introduction of the New South Wales (NSW) Performance
Measures report of 2010 (3). The main objective of the
tool was to capture each individual patient's appointment
time to ensure adequate and individualised patient
appointment scheduling. It was hypothesised that the
introduction of this tool would reduce the waiting room
time for patients.
Material and Methods
In 2010, Mosaiq 2.0X was installed in LMCTC. This version
allowed the extraction of time stamps in a reporting tool
(Crystal reports version 11). Standardisation of the
treatment processes improved the robustness of patient
data and allowed accurate extraction of time stamps in
Mosaiq. This data were then imported into Microsoft Excel
on a weekly basis for visual display of the KPIs. The tool
was launched in October of 2010 for a trial period of two
months and has been in use in the department since its
introduction.
Results
During the period of October to December 2010, the
department recorded that 56% of patients were treated on
time. Since the tool was introduced and actioned in 2011,
the department has recorded an average of 71.2% (range
69-76%) of patients treated on time. These results are
encouraging considering the number of attendances to the
department has increased over the 5 year period (Fig 1).
The percentage of patients arriving late to their
appointment is 8% (range 7.0-9.1) (Table 1). The average
waiting room time for a patient is 3.5 minutes (range 2.3
– 4.5 minutes).
Conclusion
The development of an in-house KPI tool has reduced
waiting time for patients at LMCTC. Since the introduction
of the tool we have increased the number of patients
treated on time from 56% to 71.2% over the past 5 years.
This is despite the increasing patient attendances and
changes in technology and complexity. Interestingly,
despite improvements from hospital management to
improve parking and access to the departments, 8% of
patients do not arrive on time for their appointment.
PO-1024 Effectiveness of couch coordinate constraints
to reduce error rates in radiation therapy delivery
O. Nairz
1
, N. Breitkreutz
1
1
MVZ InnMed, Strahlentherapie, Oberaudorf, Germany
Purpose or Objective
“Movement from reference marks” is one of the most
error-prone steps in the radiation therapy process. The use
of indexed immobilization devices and constrained
absolute, patient specific couch coordinates is generally
considered to be an efficient tool to reduce the risk of
radiation therapy errors (RTE) during treatment delivery.
In the light of implementing a quantitative risk assessment
we analyzed table coordinates of patients treated in our
department. We investigated the effectiveness of
tolerance values to lower the incidence of both wrong
movements from reference marks and irradiation of the
wrong patient or isocenter.
Material and Methods
Actual table values of patients in treatment position
during a period of 18 months were extracted from the
records of the verification system. Patient setups were