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\begin{document}

\title{Rapid implementation of an evidence-based remote triaging system for
assessment of suspected head and neck cancer referrals and patients on
follow up after treatment during the COVID-19 pandemic: A model for
international collaboration}



\author[1]{Vinidh Paleri MS FRCS}%
\affil[1]{The Royal Marsden Hospital,}%


\vspace{-1em}



  
  \date{June 14, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Background

Outpatient telemedicine consultations are being adopted to triage
patients for head and neck cancer. However, there is currently no
established structure to frame this consultation.

Methods

For suspected cancer referrals, we adapted the Head and Neck Cancer Risk
Calculator (HaNC-RC)-V.2, generated from 10,244 referrals with the
following diagnostic efficacy metrics: 85\% sensitivity, 98.6\% negative
predictive value and area under the curve of 0.89. For follow up
patients, a symptom inventory generated from 5,123 follow-up
consultations was used. A customised Excel Data Tool was created,
trialled across professional groups and made freely available for
download at
\href{http://www.entintegrate.co.uk/entuk2wwtt}{www.entintegrate.co.uk/entuk2wwtt},
alongside a user guide, protocol and registration link for the project.
Stakeholder support was obtained from national bodies.

Results

No remote consultations were refused by patients. Preliminary data from
511 triaging episodes at 13 centres show that 77.1\% of patients were
discharged directly or have had their appointments deferred.

Discussion

Significant reduction in footfall can be achieved using a structured
triaging system. Further refinement of HaNC-RC V.2 is feasible and the
authors welcome international collaboration.%
\end{abstract}%



\sloppy


Vinidh Paleri MS FRCS \textsuperscript{1 2 3 4}

John Hardman MRCS, MSc \textsuperscript{1 2}

Theofano Tikka \textsuperscript{5 6}

Paula Bradley \textsuperscript{7}

Paul Pracy FRCS \textsuperscript{8 9}

Cyrus Kerawala FDSRCS, FRCS \textsuperscript{1 10}

\textsuperscript{1} Head and Neck Unit, The Royal Marsden NHS Foundation
Trust, London, UK

\textsuperscript{2} Institute of Cancer Research, London, UK

\textsuperscript{3} Council member, ENTUK Head and Neck Society

\textsuperscript{4} Research Committee Director, British Association of
Head and Neck Oncologists

\textsuperscript{5} Otolaryngology - Head and Neck Surgery, Queen
Elizabeth University Hospital Glasgow, Glasgow, UK

\textsuperscript{6} School of Psychological Sciences and Health,
University of Strathclyde, Glasgow, UK

\textsuperscript{7} GP Trainee \& PhD Candidate, Northumbria GP Rotation
\& University of Sunderland

\textsuperscript{8} Otolaryngology, Head-Neck Surgery, Queen Elizabeth
Hospital, University Hospitals Birmingham NHS Foundation Trust,
Birmingham, UK

\textsuperscript{9} Chair, ENTUK Head and Neck Society

\textsuperscript{10} President, British Association of Head and Neck
Oncologists

Correspondence

Vinidh Paleri, Head and Neck Unit, The Royal Marsden Hospital, London
SW3 6JJ, UK. Email: vinidh.paleri@rmh.nhs.uk

\textbf{Abstract}

\textbf{Background}

Outpatient telemedicine consultations are being adopted to triage
patients for head and neck cancer. However, there is currently no
established structure to frame this consultation.

\textbf{Methods}

For suspected cancer referrals, we adapted the Head and Neck Cancer Risk
Calculator (HaNC-RC)-V.2, generated from 10,244 referrals with the
following diagnostic efficacy metrics: 85\% sensitivity, 98.6\% negative
predictive value and area under the curve of 0.89. For follow up
patients, a symptom inventory generated from 5,123 follow-up
consultations was used. A customised Excel Data Tool was created,
trialled across professional groups and made freely available for
download at www.entintegrate.co.uk/entuk2wwtt, alongside a user guide,
protocol and registration link for the project. Stakeholder support was
obtained from national bodies.

\textbf{Results}

No remote consultations were refused by patients. Preliminary data from
511 triaging episodes at 13 centres show that 77.1\% of patients were
discharged directly or have had their appointments deferred.

\textbf{Discussion}

Significant reduction in footfall can be achieved using a structured
triaging system. Further refinement of HaNC-RC V.2 is feasible and the
authors welcome international collaboration.

\textbf{Introduction}

Travel has been identified as the single most important contributor to
the spread of the coronavirus disease 2019 (COVID-19) pandemic.
Reduction in the transmission of the severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2) has a direct link with the introduction of
travel control measures \textsuperscript{1}. The Wuhan shutdown delayed
the occurrence of the first case of SARS-CoV-2 in other cities by 2.91
days (95\%CI: 2.54- 3.29 days), an intervention that benefited
\textgreater{}130 cities in mainland China, covering more than half its
geographic area (Tian et al). Social distancing measures are also a key
component of the control strategies during pandemics and form one of the
most effective techniques in reducing the number of infections. It is
also vital that social distancing and travel restrictions are not lifted
prematurely while there is a pool of susceptible hosts in the
population, as this will lead to an increase in the number of
infections\textsuperscript{2}. When applied to the healthcare sector
these measures should aim to reduce hospital attendance by triaging out
low risk patients both to protect clinicians and hospitalised patients,
while still allowing timely investigations on those deemed to be at
higher risk.

Interventions, such as outpatient telemedicine consultations, can reduce
footfall in hospitals, thereby promoting adherence to social distancing
policies \textsuperscript{3}. These measures are especially relevant in
the cohort of patients with head and neck diseases as the nose and
nasopharynx have been shown to be reservoirs for high concentrations of
the SARS-CoV-2 \textsuperscript{4}. Reduction of upper aerodigestive
tract interventions, including outpatient examinations, is important as
many are considered to be aerosol generating
procedures\textsuperscript{5}. Additionally, SARS-CoV-2 remains viable
in aerosols with a median half-life of 1.1 hours \textsuperscript{6},
potentially making the examination room a source of infection.

The NHS guidance for managing cancer referrals during the COVID-19
pandemic recommends a telephone triage to minimise interactions and
appointments with health services and stream patients for investigations
where appropriate \textsuperscript{7}. Additionally, a telephone
appointment with a specialist clinician is accepted as a first
appointment for the purposes of recording cancer waiting times for new
referrals. As telephone triage is a relatively novel intervention for
suspected head and neck cancer, there is currently no established
structure to frame this consultation.

The aim of this paper is to demonstrate a rapid implementation of an
evidence-based, structured, remote triaging system for assessment of
suspected cancer referrals and patients who are on regular follow up
after treatment for HNC in the United Kingdom (UK).

\textbf{Rationale:}

\emph{New referrals}

A substantial part of outpatient care in head and neck surgical oncology
work involves assessment of patients referred in with symptoms
suspicious of HNC. Apart from a few malignancies (basal cell carcinomas,
low-grade salivary gland tumours and well-differentiated thyroid cancer
in young patients), most HNCs progress within a matter of months, and a
delay in management can have an adverse effect on the prognosis. In
2000, the Department of Health in the UK developed national guidelines
for referral of suspected HNC from primary care, updated by the National
Institute for Health and Care Excellence (NICE) in 2005 and 2015.
Systematic reviews have shown that the pooled detection rate of cancer
in this population is between 8.8\% \textsuperscript{8} and
11.1\%\textsuperscript{9}. Thus, the vast majority of referrals may be
safely triaged to a deferred assessment.

In 2016, our group used information from a cohort of 4715 patients
referred in for suspected HNC to generate a 13-symptom inventory which,
when combined with age, could generate a personalised risk of cancer
with a high diagnostic efficacy (area under the curve (AUC)
0.77)\textsuperscript{10}. Sensitivity analysis identified the 8\% risk
probability cut off to offer optimal performance for the calculator.
This risk calculator was subsequently validated in an external cohort of
1998 patients, where it performed well compared to the inception cohort,
with an AUC of 0.81 \textsuperscript{11}.

After further refinements using additional information to the symptom
inventory in a new cohort (n= 3531), we published the Head and Neck
Cancer Risk Calculator (HaNC-RC)-V.2, which demonstrated increased
diagnostic efficacy with an area under the curve of 0.89, and a
sensitivity of 85\% \textsuperscript{12}. The model performed optimally
at a probability cut off of 7.1\%, where the negative predictive value
(NPV) was 98.6\%. Thus, when the symptom inventory is applied to a
patient who has been referred for suspected cancer and the calculator
indicates a \textless{}7\% risk probability for cancer diagnosis, the
chance of missing cancer if the patient is not seen by a face-to-face
conventional consultation is 1.4\%. In all these instances, a logistic
regression model was used to define personalised probability risk for
each patient. When a variety of machine learning algorithms were used on
a similar cohort of 5082 patients referred for suspected HNC, logistic
regression, the technique used to create the calculator, offered one of
the highest true negative rates, an essential characteristic of a test
to triage patients out during resource constrained
times\textsuperscript{13}.

\emph{Qualitative assessment of triaging from primary care practitioners
and hospital specialists}

Sars-CoV-2 has already changed the face of primary care in England; the
need to reduce face-to-face interactions means clinicians are embracing
new technology that allows remote assessment including SMS images and
video consultations.

Our previous qualitative work (Bradley PT et al; unpublished data) to
gauge the views of hospital specialists and primary care practitioners
has been supportive of a risk calculator. This work used a Normalization
Process Theory (that evaluates implementation and complex interventions)
to explore physicians' attitudes to the introduction and use of a head
and neck clinical cancer decision tool (Version 1 of HaNC-RC) in both
primary care and hospital practice.

The views of eleven head and neck surgeons from the North East of
England were elicited via face-to-face interviews between
6\textsuperscript{th} March 2019 and 9\textsuperscript{th} July 2019.
The interviewees welcomed an evidence-based symptom tool and opined that
a robust tool offered additional confidence to decision-making. Concerns
about triaging in the hospital setting were expressed as adequate
information may not be available in the referral form; however, a
structured triaging system such as the one proposed in this work
directly addresses this concern. Primary care practitioners' views
(twelve general practitioners in the North East were interviewed face to
face between 14\textsuperscript{th} June 2019 and
5\textsuperscript{th}December 2019) discussing the head and neck cancer
risk calculator (version 1) as a means to drive more confidence in the
triage of patients to suspected cancer clinics was met with enthusiasm.
With endorsement from secondary care and careful integration into the
pathway, it was felt that this approach could be an asset to both
primary and secondary care (Bradley PT et al; unpublished data).

\emph{Follow-up patients who have been treated for head and neck cancer}

Change in patient symptoms during follow up is the most frequent
indication of recurrent disease and must be regarded seriously, even if
clinical examination reveals no abnormalities \textsuperscript{14}.

INTEGRATE, the UK Trainee Research Collaborative Network, performed a UK
national audit of patients who underwent 5,123 follow-up consultations
after treatment for HNC in 89 hospitals across the
UK\textsuperscript{15}. Residual or recurrent disease rates were 57\% at
2 years, 32\% between~2-5 years, and~11\% post-5 years Follow-up
appointments expedited by either the patient or the clinician due to
clinical concern correlated significantly with the presence of~residual
or recurrent disease, or a second primary tumour (p=0.0001). The pick-up
rate was 35\% in expedited~appointments compared to 5.2\% in planned
follow-ups. Of the~expedited appointments, 63\%~were initiated by
patients versus~37\% by clinicians (Table 1)

Parallels exist in other cancer sites where remote follow up is
performed based on patent symptomatology and blood markers. Qaderi et
al\textsuperscript{16} optimized an innovative electronic medical record
application for patients with colorectal cancer. Patients can review
their appointments and test results, symptoms are monitored using online
questionnaires; the long term results are awaited. However, in these
resource constrained times, rapid innovation and dissemination of new
care models is needed, which, with careful data collection and robust
governance, can define new standards without causing patient harm.

\textbf{Methodology:}

A focus group of five senior clinicians agreed that structured remote
assessment could be performed, for new referrals, using the latest
iteration of the risk calculator. It was agreed that those who were at
high risk should be triaged for further assessment and the low risk
referrals undergo a deferred assessment until later in the pandemic or
when capacity became available. It was also considered appropriate for
follow up patients to be asked if they had developed any new and
specific symptoms since their previous consultation, allowing data from
the 2018 audit to risk stratify this group to inform decisions regarding
future management.

The project looked to collect data on clinician choice and patient
preference and did not mandate treatment according to set protocols.
Accordingly, the project was deemed to be a service evaluation and did
not constitute research (http://www.hra-decisiontools.org.uk/research/)

The project was developed in collaboration with INTEGRATE. Through
lending its support, and using its network to promote the project, all
UK head and neck cancer centres were approached to consider
participation. Further advertising was delivered through emails from ENT
UK and the Association of Otolaryngologists in Training (AOT;
www.aotent.org).

Designing the project in this way presented a number of challenges that
the data collection strategy that needed to be overcome.

\begin{itemize}
\tightlist
\item
  A need for immediate feedback to the clinician triaging the patient,
  and so the data must be entered directly into a computer interface
\item
  A need for a complete dataset to give valid results, again mandating a
  computer interface for data validation
\item
  A need for follow-up data to be collected at six months to see if
  patients subsequently develop cancer, and so patient identifiable data
  must be used in some capacity
\item
  A need for rapid deployment of the project to ensure the
  newly-implemented service to appropriately evaluated, and so formal
  applications for sponsorship or ethics may be too slow to achieve.
\item
  However, to comply with data governance regulations, patient
  identifiable information should not leave the institution and, if it
  were to, it must be handled with appropriate standards and practices
  to maintain confidentiality. Further, formal consent may be required
  from the patient for their data to be used in this way.
\end{itemize}

The solution developed was a customised Excel Data Tool ((Microsoft.
Excel for Mac. Redmond, Washington, USA: Microsoft Corporation; 2018).
This was made freely available for download at www.entintegrate.co.uk,
alongside a user guide, protocol and registration link for the project.
Dates and hospital numbers may be entered into the Spreadsheet, which is
stored on the hospital computer system, in line with local data
governance regulations for handling patient identifiable data. Data
entry is mostly limited to drop down lists and the decision aid only
provides information if all required fields are completed. Clinician
preference, patient choice and the immediate triage outcome can be
recorded. Subsequently, the patient ID can be used to obtain the cancer
status at six months follow up to complete the dataset.

At this point, the spreadsheet can be anonymised by removing the site,
the date of triage (if recorded) and the patient ID. Anonymous data only
is then submitted to the project management team who then apply
sequential study IDs for further analysis. Using these methods, the data
held by the project management team has high levels of data completeness
but is not traceable back to any individual centre or individual
patient.

Figure 1 summarises the remote triaging process in a flow chart for new
referrals and follow up patients, along with a recommended script to
advise the patient on the outcome of the triaging process.

We intend for the service evaluation to continue for as long as
telephone triage is being utilised in this patient group. It is
anticipated the period of disruption/telephone triage may last for at
least six months. The outcome of presence/absence of cancer diagnosis at
a minimum of six months will be treated as gold standard, and measures
of diagnostic efficacy of the remote triaging system will be analysed,
including a descriptive analysis. This will allow external validation of
the HAN-RC V2 in a pan-UK or even a global suspected head and neck
cancer referral population. Moreover, a detailed assessment of the false
negatives will be carried out to investigate the potential scope for
further refinement of the calculator.

\textbf{Results:}

None of the teleconsultations were refused by patients although some
(\textless{}1\%) expressed some dissatisfaction at the arrangements. The
overwhelming majority understood the reasons for the remote
consultation. Preliminary data were available from 511 triaging
encounters from 13 centres; these show that 77.1\% of patients were
discharged directly or have had their appointments deferred until a
later date; the remaining 22.9\% were triaged to urgent investigations
and/or face- to- face consultations.. At time of submission, the project
page at www.entintegrate.co.uk/entuk2wwtt had been accessed over 700
times.

\textbf{Discussion:}

The UK sees an average of 100 000 suspected HNC referrals per year, with
a cancer pick up rate of less than 10\%. Our preliminary results
indicate that \textgreater{}80\% of referrals can be triaged out through
teleconsultation.

Risk calculators are available for several solid malignancies: these
include bladder, brain, breast, colorectal, kidney, lung, oesophagus,
ovary, pancreas, prostate and uterus. Some have been externally
validated. Unlike other cancers where risk calculators need blood tests
and radiology to be performed, the HaNC-RC-V.2 for HNC was generated
solely from patient symptomatology and demographics, rendering it
suitable for the purpose of teleconsultation and remote triaging. The
HaNC-RC-V.2 has a higher AUC than most of the risk calculators published
for other cancers \textsuperscript{17}Usher-Smith et al). As our model
was based on recording of symptoms in the secondary care by specialist,
it is feasible that the detailed recording of the symptoms during the
consultation has helped to achieve higher predictive power than primary
care derived models.

The use of telemedicine directed patient care during public health
emergencies is well described. However, the use of digital technology in
the COVID-19 pandemic across the globe, especially in contact tracing
and testing, has been unprecedented. Concurrently, the use of digital
solutions for healthcare delivery has been accelerating since the
pandemic began. In England, primary care has embraced telemedicine and
deploys a new digital first pathway to manage and stream care, with over
90\% of consultations being remote. Other examples include a central
dashboard to manage bed availability within hospital settings, and use
of personalized online screening. A structured approach to remote
triaging and generation of a personalized risk probability will allow
clinical assessment with a consistency that otherwise cannot be
delivered in this environment.

In the emergency setting, an important strategy for healthcare surge
control during disaster management is forward triage. In the COVID-19
pandemic model, this involves remote assessment of patients before
patients arrive to the emergency care services in the hospital, either
in a location proximate to the hospital or via teleconsultation.
Emergencies that are unrelated to COVID-19 are triaged to the emergency
department~while patients showing signs of the virus are separated to
prevent transmission. The structured remote use of the risk calculator
in the pandemic time is akin to the forward triage, where following
appropriate assessment, to prevent a surge when healthcare is rationed,
patients considered to be high risk are directed to the specialist for
further assessment. Ideally the tool would be used in primary care but
for expediency in the current medical crisis and given the fact it is a
secondary care derived model it was felt best placed there for triage.

Remote consultations will be a prominent part of the outpatient clinical
practice for the near future.

Telehealth services have been promoted actively during the COVID-19
pandemic setting for initial screening of symptomatic patients or those
referred for medical care in other specialties and by more than 50
health systems in the USA \textsuperscript{18}. Structured remote
assessment of sick patients has been described in the pandemic
era\textsuperscript{19}. Research indicates that with appropriate
structure and guidance, a teleconsultation model can be
successful\textsuperscript{20} .

It is very likely that patients will be willing to engage with
teleconsultation when face-to-face access to healthcare is restricted.
Using internet search volume data from Google Trends, Hong et
al\textsuperscript{21} showed that the US population's interest in
telehealth increased as the number of COVID-19 cases increased, with a
strong correlation between population interest and COVID-19 cases
reported (r=0.948, P\textless{}.001).

Medical decision-making is cognitive, especially as experience
accumulates. However, in the early phases of training, when conventional
assessment cannot be performed and where there is less opportunity for
supervision, a structured telemedical approach, backed up by robust
algorithmic approach that has been generated and validated from the
population at risk, will be of significant help in reducing anxiety
among the clinical team and provider organisation. As always, we would
recommend experience and clinical judgement supersede the output on the
screen. To the best of our knowledge, this is the first remote
structured assessment tool that has been robustly generated, validated
and rapidly implemented for use in the HNC setting.

\emph{Stakeholder and international collaboration}

This structured triaging system has been endorsed by
ENTUK\textsuperscript{22}, the official body representing British
Otolaryngologists-Head and Neck Surgeons and BAHNO, the British
Association of Head and Neck Oncologists \textsuperscript{23}. The
authors would welcome international collaboration and prospective
centers are invited to visit the project page at
www.entintegrate.co.uk/entuk2wwtt.

It is anticipated that the COVID-19 pandemic will influence clinical
care for several years to come. The data generated from a real world
triaging such as this, when collected under robust data governance and
oversight, analysed and refined to reduce patient harm even further, can
influence healthcare provision for years to come.

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