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Received August 19, 2018, accepted September 17, 2018, date of publication October 13, 2018

Applying Human Factors Methods in a Clinical 
Engineering Setting to Reduce Medical Device 
Risks

By A Easty 

University of Toronto 

ABSTRACT

This paper describes the ways in which human factors methods can help to enhance the work of established clinical 
engineering teams by placing a new emphasis on error reduction and patient safety. This approach in many ways rep-
resents a natural evolution for departments that are looking to enhance their usefulness and relevance to healthcare. 
Several examples are given of points at which the introduction of human factors methods can reveal issues related 
to the safe use of medical devices that are not easily accessible by other means. Adoption and implementation of 
these methods offers the potential for clinical engineering departments to enhance their role in ensuring optimal 
patient safety.

Keywords – Human factors, medical devices, error investigation, patient safety.

INTRODUCTION
For clinical engineering teams, managing risks associ-

ated with medical devices is at the core of their work. Great 
attention is rightly paid to the effective maintenance of 
medical devices, to ensure that they are operating within 
specification and are inspected as required to support 
continued good performance. An ideal approach to this 
considers all phases of the medical device lifecycle, from 
acquisition planning to eventual decommissioning. The 
objective is that properly selected and maintained devices 
will help to ensure good patient outcomes during treatment.

In 1999, the Institute of Medicine (IOM) in the United 
States issued a landmark report titled: To Err is Human: 
Building a Safer Healthcare System,1 which provided a 
harsh wakeup call to the healthcare community with 
an extrapolated estimate that at least 44,000 to 98,000 
deaths were occurring each year in the US healthcare 

system as a result of generally preventable medical er-
rors. This explosive statistic caused much debate and 
analysis within the healthcare community, both in the US 
and in other countries, and subsequent studies in other 
jurisdictions revealed remarkably similar rates of error 
when normalized for population size.2 One of the results 
of this information was to place new emphasis on patient 
safety, and organizations began to search for methods that 
would allow them to study their current levels of safety, 
capture errors, and make improvements that would have 
a lasting effect on patient safety outcomes.

In the search for methods and approaches that might 
prove beneficial in healthcare, attention turned to the 
aviation and nuclear power industries, both of which had 
experienced significant catastrophic events that led to a 
clear demand for action. The discipline of human factors 

http://www.globalce.org
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Easty: Applying Human Factors Methods in a Clinical Engineering Setting to Reduce Medical Device Risks

5 J Global Clinical Engineering Issue 1:4-8; 2018

combines principles and methods from psychology and 
engineering to understand how humans interact with 
the world around them, examining issues of cognition 
and the interaction between people and the environment 
that surrounds them. Leaders in the field, such as James 
Reason and Jens Rasmussen, have developed models that 
help to determine whether a system is well designed for 
safe human use by posing questions such as; Is it clear 
and logical to operate? Does it behave in a manner that 
is similar to other systems that the operator encounters? 
Does it reveal its operating state in a clear and concise 
manner? 

These methods have proved remarkably effective 
at increasing the safety both in aviation and at nuclear 
power plants. Commercial aviation has become far safer 
in the past 40 years as a result of the standardization of 
various procedures and the use of tools such as checklists 
and safety interlocks.3 These methods offer great poten-
tial for improving the safety of healthcare as well, but to 
date, the results have been mixed4 and it is useful at this 
point to consider why it is proving so difficult to achieve 
truly significant reductions in error rates in healthcare. 
Healthcare providers spend many years of training to 
deliver the best possible care to their patients and are 
understandably distressed when errors occur during 
diagnosis or treatment. 

Effective improvements in aviation and nuclear power 
safety have come about because of the standardization 
and codification of safe practices, and at first glance it 
appears that it might be possible to have a similar effect 
in healthcare, but there are some important differences 
that come into play which are making it much more dif-
ficult to have an impact on error rates.

(1) Healthcare processes are far more varied than 
the processes followed in an airplane cockpit prior to 
take off, for example (J Ruiter-Ligeti, MD, personal com-
munication). They cannot necessarily be standardized 
to the same extent, and many healthcare providers have 
become expert at improvising in complex situations. The 
term “workaround” is one that is commonly heard in 
patient care environments as front-line care providers 
modify well-intentioned but restrictive protocols to try 
to provide optimal care for each patient.

(2) In an effort to improve safety, system planners in 
healthcare often seek to impose a level of standardization 
which restricts the ability of front-line staff to provide 
optimal care, leading to frustration and a sense that one 
must “go it alone” to provide optimal care. This often 
comes about when systems are imposed on users without 
a thorough understanding of the specifics of the work be-
ing done at the bedside. As an example, it is easier for an 
administrator to write a policy in response to an earlier 
error forbidding a particular practice, than to spend time 
in the care environment understanding why that practice 
is being used. Everyone wants to do what is best for the 
patient, but understanding what that looks like requires a 
very detailed knowledge of the actual environment of care.

(3) Healthcare is not a static entity. Indeed, big changes 
have occurred in the past 19 years since the IOM report, 
including the widespread adoption of computerization and 
the introduction of new types of medical devices. Both of 
these useful forces add complexity to an already complex 
environment, making safety an increasing challenge. 
Further, these systems and devices are often introduced 
in ways that fail to take into account the environment 
of care and the skills, abilities, and training levels of the 
users, leading to new possibilities for error.

Human factors methods can be brought to bear on all of 
these issues, and there are some early encouraging signs 
that these are taking hold. Interestingly, the application 
of human factors methods is not new in healthcare. A 
remarkable early example is the work of Dr. Jeff Cooper 
and colleagues in Boston with regard to anesthesia safety.5 

This work was way ahead of its time compared with other 
areas of healthcare and it had a profoundly positive impact 
on patient safety during anesthesia. Sadly, this approach 
did not gain a significant foothold in many other areas of 
care, and so we are now presented with the challenge of 
how to accomplish widespread adoption in the complex 
health environment of today, where devices are often 
networked together and information is aggregated in 
complex IT systems.

Clinical engineers and technologists are well-placed 
to champion the application of human factors methods 
in healthcare, at least regarding the role that medical 
devices play in errors. Jim Keller of ECRI Institute has 



Easty: Applying Human Factors Methods in a Clinical Engineering Setting to Reduce Medical Device Risks

J Global Clinical Engineering Issue 1:4-8; 2018  6

stated that their data reveal that 75% of errors that oc-
cur with medical devices are not due to device failure per 
se but are as a result of use error.6 In the next section, a 
series of ways in which the clinical engineering team can 
participate in the application of human factors methods in 
the healthcare process are explained, and it is hoped that 
we as a profession will seize the opportunities that these 
tools provide to do our bit to try to ensure that medical 
devices are used as safely and effectively as possible.

HUMAN FACTORS ROLES FOR CLINICAL 
ENGINEERING

While it is unreasonable to assume that clinical engi-
neering can solve all of the systemic error problems in 
healthcare, it is clear that a number of these relate in one 
way or another to the use of medical devices and IT systems. 
Medical device support has been the traditional domain of 
clinical engineering, and in recent years there has been a 
strong emphasis on clinical engineering becoming much 
more involved in the deployment of IT-based systems as 
well, since in many ways the issues posed by these mimic 
the ones posed by medical devices themselves; issues 
such as technical specifications, network connectivity, 
interfaceability, and overall user satisfaction. IT systems 
are often an extension of patient data collection, much 
of it initiated by medical devices at the front end, so this 
extension of activities is logical and sensible.

Clinical engineering is well-placed to bring a systems 
engineering approach to helping to reduce error, and 
this has the advantage of moving the approach away 
from opinion and conjecture and towards measurable 
parameters and outcomes; the classic tools of quality 
improvement. A full review of the various ways in which 
clinical engineering can engage in bringing a human factors 
approach to healthcare is beyond the scope of this paper, 
but a comprehensive treatment of this subject can be found 
online.7 The following is a brief summary of the key areas 
where contributions are possible, and further reading is 
encouraged. There are a small but growing number of 
teams specializing in these methods in healthcare around 
the world, and it is hoped that in time, these methods will 
become widespread and routine, since they offer great 

potential to improve the level of safety associated with 
the use of medical devices and IT systems.

Use in Assessment and Procurement
The assessment and procurement of medical devices 

has long been recognized as a critical task for clinical 
engineering since decisions that are taken then have an 
impact of many years. A poor choice of technology can 
result in devices that are unreliable or difficult to operate. 
In most jurisdictions, the demand for new technology out-
strips the available funding, so decisions need to be made 
carefully. Once made, the selected devices are long-term 
commitments that ideally should satisfy the needs of the 
healthcare system. Very often, medical device decisions 
do not involve many, or even any, of the end users who 
will ultimately have the task of trying to extract good 
performance from the chosen system. Traditional user 
assessments in clinical areas are often subjective and 
haphazard, and subject to bias. Using the human factors 
methods of work flow analysis and usability testing in a 
controlled simulated or real environment allows a high 
measure of objectivity to be brought to an evaluation of 
competing products from several vendors. 

Representative end users are initially observed inter-
acting with comparable technologies if present, to gain a 
thorough understanding of the ways in which the tech-
nology fits within the environment and associated work 
flows. Users are then recruited into a series of controlled 
interactions with competing technologies using scenarios 
that are scripted to represent typical tasks in the observed 
clinical work flows. The human factors team members 
passively observe the performance of each participant, 
paying special attention to areas where users experience 
confusion interacting with a device, or make errors dur-
ing use. If multiple participants experience problems at a 
particular stage of use, that is a strong indication that some 
aspect of the device being tested is proving problematic 
for the entire user population, and an assessment should 
be made of the potential severity of the problem. Could it 
lead to an incorrect treatment or diagnosis, for example? 
Can it be bypassed or modified in some fashion?

Mounting tests of this kind requires some effort and 
knowledge of the evaluation methods used, but the invest-
ment of time for a major device acquisition is well worth 



Easty: Applying Human Factors Methods in a Clinical Engineering Setting to Reduce Medical Device Risks

7 J Global Clinical Engineering Issue 1:4-8; 2018

this effort. Institutions have to choose which device areas 
to subject to this rigorous evaluation, and as a general 
guide, the following filters can be applied; is the device 
one which has been associated with past incidents and 
errors? Is the device widely distributed in the organization 
and thus used by a variety of different people? Is there a 
major financial investment being made? If the answer to 
one or more of these questions is yes, then the upfront 
cost and effort associated with a human factors-based 
pre-purchase evaluation may well reap dividends over 
the lifetime of the equipment. One other important issue 
to consider is that when end users participate directly in 
this type of evaluation, they come to a better understand-
ing of the capabilities and limitations of the device, and 
are more vested in the selected product, assuming that 
their experiences are used to help inform an optimal 
purchasing decision.

Use in Predicting and Investigating Errors
Even with careful device selections, errors will still 

periodically occur, and so the next area in which the hu-
man factors approach can play an assistive role is in the 
prediction and investigation of adverse events. Tools such 
as Failure Mode and Effects Analysis (FMEA) can be used 
proactively to assess the likelihood of certain events occur-
ring during the use of device or a system. Each potential 
failure mode is identified and the associated effects from 
each are categorized, asking what the probability of oc-
currence is and what the impact will be should it occur. 
Once these are drawn up, a list of mitigating strategies can 
be identified and decisions can be made about which of 
these are realistically implementable. Note that all of this 
work is prospective. It is done ahead of implementing a 
particular device or system, and if the analysis is thorough, 
it offers the potential to significantly reduce the overall 
error rates associated with a particular system. Clinical 
engineering teams are often very well-placed to lead this 
analysis since they are aware of the details of implemen-
tation of a technology and also have a good grasp of the 
potential problem areas associated with its use.

Assuming that an incident has now occurred and that 
the institution has initiated an investigation, the Root Cause 
Analysis (RCA) method is a powerful tool grounded in hu-
man factors theory that can be used to try to understand the 

root causes behind the incident. With very rare exceptions, 
healthcare workers are deeply committed to the welfare 
of their patients and are traumatized when adverse events 
occur that compromise their patients’ care. Sometimes 
the initial reaction to an adverse event is to criticize the 
people involved and ascribe it to poor judgment. This 
has the double effect of quickly identifying the “culprits” 
and reassuring the system that this was a one-off event, 
leading to a false sense of security that the underlying is-
sues have been effectively addressed. The human factors 
approach helps us to look behind these assumptions to 
try to understand the root causes involved. Perhaps the 
healthcare provider was interrupted during a very critical 
task. Perhaps the system itself is so complicated that many 
users do not know how to properly operate it. Perhaps 
a user was presented with information that appeared to 
confirm that the system was performing as intended and 
failed to notice that the potential for an adverse event 
was evolving as a result of their actions. An RCA helps to 
uncover these issues, and once they are revealed, helps 
to guide those responsible for the system regarding the 
changes that are required to the system to try to minimize 
the likelihood of a recurrence. Again, clinical engineering 
is well-placed to take a lead role in aspects of this analy-
sis, working with colleagues from other disciplines to 
uncover these root causes. By identifying and mitigating 
these issues, systems truly become safer in the long term.

Looking for No Fault Found Repair Reports
As mentioned at the beginning of this paper, clinical 

engineering departments are rightly charged with the ef-
fective maintenance of the medical devices used in their 
institution. Ask any hands-on service person in clinical 
engineering whether they have ever received a piece of 
equipment from a clinical area with a label on it saying 
“broken” only to find that when they test it on the bench, 
it is performing to specification. These are often referred 
to as “no fault found,” since no fault was detected by the 
service team. A recent study8 pulled data related to no 
fault found service events and then identified a range of 
devices that showed higher incidence levels of no fault 
found reports. When these devices were assessed for us-
ability, a correlation was found between user difficulties 
and the likelihood of a no fault found event occurring. In 



Easty: Applying Human Factors Methods in a Clinical Engineering Setting to Reduce Medical Device Risks

J Global Clinical Engineering Issue 1:4-8; 2018  8

other words, users were experiencing difficulties using 
a device and some of them were giving up in frustration 
on the assumption that something must be wrong with 
the device itself, or simply taking the approach that if I 
can’t get this unit to work, maybe I should get another 
one and send this one in for “repair.” From this it can be 
seen that no fault found reports in clinical engineering 
departments are to some degree a proxy for devices that 
are difficult to operate. Further investigation can reveal 
whether interventions such as further user training can 
be effective at helping to reduce operating problems, or 
are the issues built into the design of the device such 
that the only effective remediation is replacement of the 
device altogether.

CONCLUSION
While not all of the approaches described above can 

be performed solely by the clinical engineering team in 
an institution, the application of these human factors 
methods can easily be developed and championed by it. 
With their technical background, the team is ideally placed 
to adopt and promote these methods, and will often find 
allies among clinical staff, administrators and risk manag-
ers, all of whom have a strong interest in reducing errors 
during care as much as possible. As clinical engineering 
adapts and grows, this area represents a high-impact 
extension to the work that they currently do, and it can 
be argued that promoting human factors methods is a 
challenge not unlike the one faced by clinical engineering 
10 years ago regarding their involvement in information 
technology systems. That debate is largely resolved, and 
it is hoped that the next 10 years will see a similar out-
come regarding the adoption of human factors methods 
by clinical engineering. To gain this knowledge, users 
are encouraged to learn more about this topic through 
reading and through contact with colleagues who have 
already worked in this area. Industrial Engineering and 
Psychology departments of nearby universities may have 
faculty with strong human factors knowledge who are 
interested in collaborating with people who are working 
in a live clinical environment. Also, there are an increas-
ing number of labs whose work is focused specifically on 
the application of human factors methods to healthcare, 

and these represent expert sources of information and, 
potentially, collaboration.

In sum, clinical engineering departments have an ex-
cellent opportunity to play an important role in helping 
to make the provision of healthcare safer through the 
adoption and application of human factors methods in 
their work. Clinical engineering professionals are encour-
aged to seize this opportunity and make a contribution. 
Development of this area of expertise in healthcare will 
help to elevate clinical engineering from a technical sup-
port role to important players in ensuring optimal safety 
for patients.

CONFLICT OF INTEREST
The author declares that there is no conflict of interest 

regarding the publication of this paper.

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