EHF2017 EK FinalPaper
EHF2017 EK FinalPaper
EHF2017 EK FinalPaper
Abstract. This paper describes how a suite of research techniques were used to inform the
development of a vision for the future of radiotherapy. The aim of the vision was to
conceptualise a next-generation radiotherapy system that creates a step-change in system
performance. The impact of the vision on patient and HCP experience, safety, and efficiency
were all explicitly considered and measured. The vision was used to inform the design of
Elekta’s release of Atlantic – a high-field MRI-guided radiation therapy system.
1. Introduction
Radiotherapy is a safety critical and highly demanding treatment. From a patient perspective, it
represents part of an incredibly emotional journey, as it is typically associated with life changing
conditions. Health care professionals (HCPs) working in radiotherapy have a challenging,
multifaceted role. The emotional and physical needs of patients need to be carefully balanced
alongside the requirements of efficiency placed upon them by healthcare systems which are
often under pressure.
Current radiotherapy systems have evolved and been optimised over many years. Successive
innovations have improved the accuracy of the treatment and reduced the likelihood and
severity of complications. This iterative journey of improvement has been punctuated by a series
of step-change innovations, most notably in imaging, that have impacted the type of treatments
that are possible and the way that these are delivered.
When a new product is based on a paradigm shift in technology the observation of legacy
equipment only provides a partial picture. New technologies provide new capabilities which, in
turn, permit new ways of working (see Task-Artefact Cycle; Carroll et al, 1991). The design of
the equipment, its human machine interfaces (HMIs), and its surrounding environment can each
shape these possibilities and constraints. As with almost all design projects, exploring and
understanding these relationships and constraints early in the design process allows the design to
be evaluated and optimised before the cost of change, in terms of both time and money,
escalates, potentially to prohibitive levels.
With this is mind, DCA supported Elekta in designing and developing a next generation suite of
radiotherapy equipment at an early stage of the design process. While conceptual, these ‘visions
for the future’ were grounded through collaborative technical review and based on an extensive
body of evidence collected from visits to seven treatment sites worldwide (including sites in
Belgium, Brazil, Canada, USA; see Figure 1 and Figure 2), over 90 hours of observations
(approximately 360 treatment sessions), and over 50 in-depth interviews with health care
professionals, thought-leaders and system stakeholders.
The first stages of the design process involved working with identified stakeholders (including
key members of the Elekta Team, clinical specialists, health care providers and purchasers) to
define key measures of system performance that are bespoke to the project. These were defined
as system efficacy, efficiency, safety (staff and patient), user experience (staff and patient) and
resilience (see Figure 3). Understandably, different stakeholders placed different priorities on
each of these values; however, each was considered an important factor in decision making.
Once the values were agreed upon, a framework of tools and techniques was constructed to
allow objective measures of each of the performance values to be identified. These metrics of
system performance were considered critical in driving an evidence-based approach to design.
The overarching philosophy was to first measure the performance of existing radiography
systems. This assessment would be used in two ways. Firstly to identify opportunities for
improvement, and secondly to form a baseline to measure design concepts against.
The resultant framework of tools, used to populate these metrics, (see Figure 4) can be broadly
divided into two types of methods, descriptive and formative. Descriptive tools, such as task
analysis (Annett et al, 1971) and link analysis, were used to describe current activity within
existing radiotherapy units. These models were also used to assess the impact of evolutionary
changes (adjusting size, shape, speed and performance of existing system component types) and
estimating their impact. More formative tools, such as those from the Cognitive Work Analysis
framework (Rasmussen et al, 1994), were better placed to describe the impact of radically new
technologies and approaches.
3. Result
The final vision addressed the design of equipment, accessories, digital displays and their
interaction, as well as the surrounding room, control room and overall patient experience. From
a patient perspective, the vision sought to minimise the physical discomfort and the emotional
strain of the procedure. The ambiance of the room was designed to strike a delicate balance
between a welcoming and relaxing environment and one that instils confidence by
communicating clinical excellence – offering customisation of lighting and projection and of
ambient music. The patient treatment couch was designed for comfort and support during
loading, unloading and treatment while considering technical requirements such as alignment,
accuracy and compatibility with MRI technology.
From a health care professional (HCP) perspective, detailed assessment of information
requirements resulted in a design that provides the right information, at the right time, in the
right place, to the right people, in the right format. This involved presenting information that is
relevant to the treatment based on the specific step in the treatment process. This information is
distributed so that it remains as close to the point of use as possible, whether that is in the
control room, on the equipment, on the couch or accessories or a combination of all of the
above. By allowing the system to differentiate between user types (HCPs, physicists, etc) non-
relevant information can be hidden and relevant information can be presented in meaningful
ways. The type of information and the way it is displayed is customised, providing clear
advantages for usability, efficiency and safety.
Intelligent feedback mechanisms allow the system to detect the stage in the treatment process
and can detect non-conformance to predefined setup plans. Likewise, the layout of the room and
the location of equipment have been considered based on the HCP workflow, reducing the need
for manual handling and excessive footfall. This focus also translates to the control room with
workstations designed to support a vigilant task as well as meeting the requirements of operators
moving between the control and treatment rooms.
Human factors remained a key factor in the development of the Atlantic product. Further
ethnography activities were conducted in additional markets (including China) focusing on
exploring the workflow, time and motion studies, and stakeholder perceptions. These were used
to expand the existing evidence-base used to inform the vision.
In order to gain greater confidence in the largely desk-based anthropometric studies used to
inform the vision, physical medium-fidelity rigs (wooden spatial representations) were
developed. The rigs were used to explore patient-equipment interactions, HCP-equipment
interactions, and Patient-HCP interactions in greater detail. Initially paper-based representations
of screens and controls were used within the re-configurable rigs to optimise the location of
controls and feedback displays. Theoretical assumptions around text heights and locations were
also explored in context. As the design of the digital human machine interface (HMI) was
developed dynamic interfaced on tablets were used to enhance the fidelity of the prototype.
These full-sized physical spaces were used to role-play different treatment scenarios exploring
how the design supports different workflows.
Stakeholder workshops were also used to refine information requirements model and
differentiate between essential and non essential information and control interactions.
Gradually increasing the fidelity of the prototypes throughout the process allowed fast iteration
in the early stages of the design towards a convergence on a preferred embodiment.
The case study discussed represents a relatively rare example of how an extensive suite of
human factors tools can be applied to a design problem at a conceptual level. Each of the
different tools brought new insights that shaped the design.
Ethnography and interviews dominated the data collection activities and formed the foundation
for the majority of the analyses, as well as being a rich source of inspiration in their own right.
The more analytical approaches also provided a critical part of the process. Despite over 90
hours of clinical observations, there remained a sizable number of predicted situations and
‘hazardous events’ that were not observed. These were validated during in depth interviews with
HCPs and the majority were rated as credible. Thus, their consideration in the design was of
paramount importance.
Quantification of performance, particularly error, remains a contentious issue within the human
factors community. However, in this case, it proved to be a rich source of valuable insights. The
value of the quantification was not the absolute probability or error per se, rather the relative
probabilities that allowed prioritisation to take place. Perhaps, most critically, from a design
perspective the explicit consideration of performance shaping factors served as an excellent cue
for design. More contemporary tools, such as CREAM and FRAM, were used to balance the
known weakness of probabilistic risk assessment. The ‘common performance conditions’ from
CREAM was particularly valuable for exploring the differences between installations in
different geographical and regulatory contexts. FRAM provided a useful description of the
interdependencies of actions, activities and interventions.
References
Annett, J., Duncan, K.D., Stammers, R.B., & Gray, M. (1971). Task Analysis. London: HMSO.
Carroll, John M., Kellogg, Wendy A., Rosson, Mary Beth (1991): The Task-Artefact Cycle. In:
Carroll, John M. (eds). "Designing Interaction: Psychology at the Human-Computer Interface"
Cambridge University Press .
Elekta Annual Report 2014/15
Hignett, S. and McAtamney, L. (2000) Rapid Entire Body Assessment: REBA, Applied
Ergonomics, 31, 201-5.Hollnagel, E. (1998). Cognitive Reliability and Error Analysis Method –
CREAM. Oxford: Elsevier Science.
Hollnagel, E. (1998). Cognitive Reliability and Error Analysis Method – CREAM. Oxford:
Elsevier Science.
Hollnagel, E. (2004). Barriers and accident prevention. Aldershot, UK: Ashgate
HSE (2004) Manual handling. Manual Handling Operations Regulations 1992 (as
amended).Guidance on Regulations L23 (Third edition) HSE Books
Rasmussen, J., Pejtersen, A., & Goodstein, L. P. (1994). Cognitive systems engineering. New
York: Wiley.
Shorrock, S. T. and Kirwan, B (2002). Development and application of a human error
identification tool for air traffic control, Applied Ergonomics. 33(4):319-36.
Swain, A.D. & Guttmann, H.E., (1983) Handbook of Human Reliability Analysis with
Emphasis on Nuclear Power Plant Applications. NUREG/CR-1278, USNRC.
Williams, J. C. (1986). HEART – a proposed method for assessing and reducing human error.
In 9th Advances in Reliability Technology Symposium, University of Bradford.