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Received January 16, 2021, accepted May 21, 2021, date of publication May 27, 2021

A risk assessment method based on the failure analysis of 
medical devices in the adult Intensive Care Unit

By Fabiola M. Martinez-Licona, Sergio E. Perez-Ramos    

Electrical Engineering Department, Universidad Autonoma Metropolitana, Mexico City

ABSTRACT

Backgrounds and Objective: The Intensive Care Unit (ICU) receives patients whose situation demands high complexity tasks. 
Their recovery depends on medical care, their response to medications and clinical procedures, and the optimal functioning 
of the medical devices devoted to them. Adverse events in the ICU due to failures in the facilities, particularly medical devices, 
impact the patients, operators, and all involved in their care. The origins of the technological failures seem to be more oriented 
to the interaction between the equipment and the operator. Once the medical equipment is functioning, we must guarantee 
its correct execution to meet both the clinical service’s objectives and the expectations of those involved in care, including the 
patients themselves. We present an approach to quality management based on failure analysis as the source of risk for medical 
devices’ functioning and operation in the ICU. We decided to address it through a systematic approach by using elements from 
the Failure Mode and Effects Analysis (FMEA) method and the Ishikawa diagrams’ support to obtain the causes graphically.
Material and Methods: We used the risk analysis framework as a basis of the methodology. By obtaining the causes and sub 
causes of technological failures in the ICU for adult patients, we adapted some of the FMEA method and applied the Ishikawa 
diagrams to analyze the relationship between cause and failure. The ICU devices came from the Official Mexican Standard and 
the World Health Organization (WHO) information related to the ICU operation and facilities. The data from the causes of failure 
came from specialized consultation and discussion forums on medical devices where these topics were addressed; we searched 
for over five years in Spanish forums. We proposed a calculation of the Risk Priority Number based on the information subtracted 
from the forums. Then, we defined an indicator showing the priority level used to address the issue.
Results: In general, the results showed that most of the medical equipment failure causes have medium and high-risk priority 
levels and, in some cases, the cause presented as the most prevalent did not match with the reported in official documents such 
as technical or operation manuals. The most frequent causes found are related to electrical system issues and operation skills. 
We presented three study cases: defibrillator, vital sign monitor, and volumetric ventilator, to show the risk level designation. The 
conclusions inferred from these cases are oriented to training strategies and the development of support material in Spanish.
Conclusion: The development of risk management methodologies to monitor and solve potential hazard situations in critical 
areas is valuable to the health technology management program. The FMEA method showed a solid basis for the risk assessment 
processes, and its application to the ICU medical technology allowed the creation of the evidence supporting the decision-making 
process concerning strategic solutions to guarantee patient safety.

Keywords – Risk Assessment, Failure analysis, FMEA, ICU medical equipment, Health Technology Management.

Copyright © 2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY): Creative Commons - Attribu-
tion 4.0 International - CC BY 4.0. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) 
are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is 
permitted which does not comply with these terms.

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J Global Clinical Engineering Vol.4 Issue 2: 2021  16

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

INTRODUCTION

The patients in the Intensive Care Unit (ICU) are un-
der unique circumstances. This situation is due to the 
requirement of specialized multi-organ support actions 
needed to restore their health, including medical devices.1 
Furthermore, the ICU patients’ complexity makes them 
depend on medical care, their response to medications 
and clinical procedures, and the optimal functioning of 
the medical devices devoted to them. Studies carried out 
in this regard have shown the impact of failures related to 
technology and its applications in the analysis of adverse 
events at ICU,2 and the importance of safety improvement 
in using medical devices in this area to have greater con-
trol of incidents.3

Technological failure is defined in the hospital envi-
ronment as an event in which medical equipment has 
stopped working correctly, which is associated with a 
probability of harming the patient or the operator.4 The 
origin of technological failures can be approached from 
different perspectives; some of the most relevant has to 
do with the negative effect on the patient or the context 
of medical devices’ operation. Some sources of failure 
that have been identified in this regard are5:

• The wrong dynamic range of measurement
• A lack of training in the operation of the equipment
• A lack of quality control in measurements
• A lack of quality control in pre-installations
• The wrong design
The origins of the technological failures mentioned are 

more oriented to the interaction between the equipment 
and the operator. Once the equipment is in operation, we 
must guarantee its correct execution to meet both the 
clinical service’s objectives and the expectations of those 
involved in care, including the patients themselves. In this 
sense, technological failure becomes a reference point 
for developing plans and strategies that help improve 
quality. Within this frame of reference, aspects related to 
the medical device’s operation will be taken as a quality 
feature so that the failure analysis approaches from a 
strictly technological perspective. Furthermore, it implies 
that the factors associated with its operation and function-
ing, including infrastructure, device design, and human 
resources, will be analyzed around the medical device and 

not as independent causes. Thus, we can design strategies 
for the containment and eventual elimination of the fault.

As for the ICU, analyzing the causes of medical devices’ 
failures will make it possible to develop plans for risk 
management and control of related incidents. This kind 
of management process is particularly relevant, given 
the vulnerable condition of the patients treated in ICU 
demands actions that guarantee their safety and those 
who interact with them. We must address two consider-
ations: a failure may be due to more than one factor, and 
in ICU, the potential factors involved increase the difficulty 
of the analysis. We decided to address the issue through 
a systematic approach, so we chose to take the Failure 
Mode and Effects Analysis (FMEA) method.

FMEA method is a systematic process that identifies 
the potential product or process design failures before 
they occur to eliminate them or minimize the associ-
ated risk.6 Although this method has been used more 
frequently in the automotive industry; it can detect and 
contain potential failures in various natures’ products 
and processes. Therefore, its application to the medical 
field has been growing.7 It includes improving patient 
safety,8 the analysis of risk points in the implementation 
of smart devices,9 its application in radiotherapy,10 or 
quality management in the clinical laboratory.11 FMEA 
method integrates two stages for its implementation: 
identifying the failure and its evaluation.12

The identification stage includes the following: the 
process’ phases list to be analyzed, the potential failure 
modes, the identification of the effects, if the failure mode 
occurred, the causes that could have originated them, 
and the discovery of the controls that the process has to 
prevent failures from happening, that is, prevention and 
detection. The evaluation stage evaluates the severity, 
occurrence, and detection of the failure and identifies the 
points to apply corrective and improvement actions. Finally, 
the stage is complemented by assigning risk through an 
indicator and prioritizing failure modes to take action.

Tools such as Pareto diagrams or cause-effect diagrams 
are common to identify the causes of failures. In this case, 
we selected the Ishikawa diagram because it facilitates 
analyzing problems and solutions in aspects such as quality 
of processes, products, and services. The Ishikawa dia-
grams rely on a logical order to structure the information 



17 J Global Clinical Engineering Vol.4 Issue 2: 2021

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

and take the form of a fishbone; the multiple cause and 
effect relationships of the variables that intervene in the 
processes are presented.13

We present an approach to quality management that 
starts from analyzing failures as sources of risk for medical 
devices’ functioning and operation in the ICU. From the 
FMEA, we used the first stage, identification of the failure. 
Then, with the Ishikawa diagrams’ support, we obtained 
graphic displays of its causes and origins where created, 
which, together with a numerical indicator, allowed de-
termining the prioritization of corrective actions.

METHODS

The methodology we used was founded on the risk 
analysis framework. By considering the technological 
failures that occur in the ICU for adult patients, we iden-
tified their causes and sub-causes. We adapted some 
elements from the FMEA method with the support of 
Ishikawa diagrams to analyze the relationship between 
cause and failure.

We obtained the ICU medical devices’ identification 
to be analyzed from the Official Mexican Standard NOM-
025-SSA3-2013 for the organization and operation of 
intensive care units14 and the central medical equipment 
section of the World Health Organization (WHO).15 Then, 
for each piece of medical equipment, the causes of failure 
were classified into the following five categories13 and 
incorporated into an Ishikawa diagram:

• Human resources that are involved in the operation
• Environment or conditions under which medical 

equipment operates
• Materials used for its operation
• Methods for the development of functions for its 

operation
• Machines or any equipment or tools required to 

perform the work
We obtained the information to identify the possible 

causes of failures associated with using the equipment 
from the search in specialized consultation and discus-
sion forums on medical devices where these topics were 
addressed; we searched for over five years in Spanish 
forums. Among the platforms consulted are yoreparo.
com, ayudabiomedica.com, forumsdeelectronica.com, sefh.

es, and elhospital.com. The information was completed 
by consulting the equipment’s technical and operation 
manuals. We identified the possible causes of a failure 
for each medical equipment and, based on the number 
of mentions found in the forums consulted, their priority 
level. We determined to evaluate the quality of operation of 
each piece of equipment by defining the following metric 
based on the Risk Priority Number (RPN) that, according 
to the FMEA evaluation stage, is defined by 

RPN= Severity*Occurrence*Detection (1)

Each of the terms included in (1) were adapted to the 
forum information context, so: 

• Severity is computed by taking the number of found 
mentions per specific cause divided by the highest 
value of mentions per any cause in the medical device.

• Occurrence is calculated by taking the number of 
mentions per specific cause divided by the total 
number of mentions in the medical device. 

• For Detection we proposed to assign three levels of 
impact of the failure, 1 to low, 2 to medium, and 3 to 
high, according to the information reported in the 
equipment’s medical manuals. We carried out the as-
signment by searching the troubleshooting sections 
for the frequency of reported failures and solutions, 
assigning a higher level to the most frequent.

Then, we defined an indicator that shows a level of 
priority that can be used to address the issue. First, we 
normalized the RPN for each failure cause in the equipment 
(RPNn); then, we classified it into low, medium, and high 
categories based on the proportion of the RPNn failure 
cause within the related equipment. In general, high class 
was assigned to RPNn > 0.5, low priority to RPNn < 0.1, 
and medium priority to RPNn between these two values. 
Following, we proposed a priority level percentage indica-
tor that shows the general situation of the equipment as: 

%_Priority_Level = (Number of mentions per RPN class/
number of total mentions per equipment)*100 

We determined each medical equipment’s risk level 
based on the percentage of failures with high and medium 
priority levels obtained from the priority indicator. These 

http://yoreparo.com
http://yoreparo.com
http://ayudabiomedica.com
http://forumsdeelectronica.com
http://sefh.es
http://sefh.es
http://elhospital.com


J Global Clinical Engineering Vol.4 Issue 2: 2021  18

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

results enabled us to focus on specific issues to develop 
action plans to address them. 

RESULTS

The ICU medical equipment included in the analysis 
were:

• Apnea monitor
• Central monitoring

• Defibrillator
• Hospitalization bed
• Infusion pump
• Portable X-ray system
• Vital sign monitor
• Volumetric ventilator
The numbers of causes found, total mentions identi-

fied, and percentages of priority levels for each one are 
shown in Table 1. 

TABLE 1. Causes, Mentions, Priority Levels (PL) Percentage Found in ICU Medical Devices

Medical Device Causes Total Mentions % High PL. % Medium PL. % Low PL.

Apnea Monitor 11 24 50 33.33 16.67
Central Monitoring 10 24 62.50 25 12.50

Defibrillator 14 39 53.85 33.33 12.82
Hospitalization Bed 13 34 26.47 44.12 29.41

Infusion Pump 14 55 49.09 21.82 29.09
Portable X-ray 17 69 39.13 23.19 37.68

Vital Signs Monitor 15 39 46.15 38.46 15.38
Volumetric Ventilator 13 38 28.95 44.74 26.32

We present below the Defibrillator, Vital Signs Monitor, 
and Volumetric Ventilator cases to illustrate the results.

Case 1: Defibrillator.

Table 2 shows the causes found, the number of men-
tions, the values of severity, occurrence, and detection 
obtained, and the computed normalized RPN. The cause 
with the highest number of mentions was the suspension 
of the electrical system with 5. In contrast, the causes 
with the lowest number of mentions were related to the 
equipment’s documentation. The prioritization was car-
ried out as follows:

- Low priority: 0.01≤RPNn≤0.1
- Medium priority: 0.16≤RPNn≤0.24
- High priority: 0.43≤RPNn≤1
The last column’s color corresponds to the priority 

class assigned, green to low, yellow to medium, and red 
to high priority level.

To illustrate obtaining the Severity, Occurrence, De-
tection and RPNn values, we will take the failure cause 
“Insufficient battery charge” (ibc).

Then, we get the RPNn :



19 J Global Clinical Engineering Vol.4 Issue 2: 2021

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

FIGURE 1. Ishikawa diagram for the defibrillator failure analysis.

TABLE 2. Causes, Mentions, RPNn Data, and Priority Classes Found in the Defibrillator

Cause found No. Mentions Severity Occurrence Detection RPNn

Emergency electrical system 5 1 0.128 3 1
Suspension of electrical service 4 0.8 0.102 3 0.64

Insufficient battery charge 4 0.8 0.102 3 0.64
Difficulty using the defibrillator 4 0.8 0.102 3 0.64

Broken electrode cables 4 0.8 0.102 2 0.43
Transients caused by other loads with the same supply 3 0.6 0.076 2 0.24

Voltage fluctuations 3 0.6 0.076 2 0.24
Power cord 3 0.6 0.076 1 0.12

Poor electrode cleaning or incorrect application 2 0.4 0.051 3 0.16
Battery life 2 0.4 0.051 2 0.11

Faulty electrodes 2 0.4 0.051 3 0.16
Incorrect electrode placement 1 0.2 0.025 2 0.03
Lack of manuals and/or guides 1 0.2 0.025 1 0.01

Difficulty with the documents’ language 1 0.2 0.025 1 0.01

The Max_RPNdefibrillator was obtained from comput-
ing severity, occurrence, and detection of the failure cause 
with most mentions (Emergency electrical system). Since 
RPNn_ibc > 0.5, the priority for this failure cause is high, so 
it gets the red color.

Next, we elaborated the Ishikawa diagram, shown in 
Figure 1, where the causes of failures were located in the 
established categories based on their failure impact, the 
most significant impact near the fishbone. The colors 
indicate the assigned priority level: red-high, yellow-
medium, and green-low.



J Global Clinical Engineering Vol.4 Issue 2: 2021  20

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

Case 2: Vital Signs Monitor.

Table 3 shows the causes found, the number of mentions, 
the values of severity, occurrence, and detection obtained, 
and the computed normalized RPN. For example, the cause 
with the highest number of mentions was related to the 
emergency electrical system with 6. On the other hand, 
the causes with the lowest number of mentions included 
electrical supply and equipment documentation issues. 
In this case, the prioritization was carried out as follows:

• Low priority: 0.03≤RPNn≤0.06 
• Medium priority: 0.11≤RPNn≤0.25
• High priority: 0.35≤RPNn≤1

TABLE 3. Causes, Mentions, RPN Data and Priority Classes Found in the Vital Signs Monitor

Cause found No. Mentions Severity Occurrence Detection Norm. RPN

Emergency electrical system 6 1 0.153 2 1

Suspension of electrical service 5 0.833 0.128 1 0.35

Power cord 4 0.666 0.102 3 0.67

Difficulty using the monitor 3 0.5 0.076 3 0.38

Insufficient backup batteries 3 0.5 0.076 2 0.25

Communication with the non-invasive pressure module 
sensor 3 0.5 0.076 2 0.25

Battery charge timeout 3 0.5 0.076 1 0.13

Lack of knowledge of the use of the control console for 
calibration and adjustment (software) 2 0.333 0.051 3 0.17

Communication with the heart rate module 2 0.333 0.051 3 0.17

Communication with the pulse oximetry module 2 0.333 0.051 2 0.11

Communication with the temperature module 2 0.333 0.051 1 0.06

Voltage fluctuations 1 0.166 0.025 3 0.04

Lack of manuals and / or guides 1 0.166 0.025 3 0.04

Transients caused by other loads with the same supply 1 0.166 0.025 2 0.03

Difficulty with the documents’ language 1 0.166 0.025 2 0.03

As in the previous case, the last column’s color corre-
sponds to the priority class assigned, green to low, yellow 
to medium, and red to high priority. We elaborated the 
Ishikawa diagram corresponding to this medical equip-
ment, shown in Figure 2, using the same settings for the 
previous case of the failure location and the color assigned 
according to the priority.

We elaborated the Ishikawa diagram corresponding 
to this medical equipment, shown in Figure 2, using the 
same settings for the previous case of the failure location 
and the color assigned according to the priority.

Table 4 shows the causes found, the number of mentions, 
the values of severity, occurrence, and detection obtained, 
and the computed normalized RPN. In this equipment, the 
cause with the highest number of mentions was related 
to the power cord with 6. On the other hand, there were 
only two causes with the lowest number of mentions, 

including electrical transients and pneumatic systems. 
In this case, the prioritization was carried out as follows:

• Low priority: 0.01≤RPNn≤0.17
• Medium priority: 0.22≤RPNn≤0.38
• High priority: 0.69≤RPNn≤1



21 J Global Clinical Engineering Vol.4 Issue 2: 2021

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

The last column shows the priority class assigned: 
green to low, yellow to medium, and red to high priority 
level following the color agreement.

In the same way, we elaborated the Ishikawa diagram 
corresponding to this medical equipment, shown in Fig-
ure 3, using the same priority color assignment of the 
other cases.

FIGURE 2. Volumetric Ventilator

TABLE 4. Causes, Mentions, RPNn Data and Priority Classes Found in the Volumetric Ventilator

Cause found No. Mentions Severity Occurrence Detection Norm. RPN

Power cord 6 1 0.157 2 1

Bad filter placement 5 0.833 0.131 2 0.69

Bad connection to nebulizer 4 0.666 0.105 1 0.22

Emergency electrical system 4 0.666 0.105 1 0.22

Bad installation of traps or collectors of excess water 3 0.5 0.078 3 0.38

Gas supply system 3 0.5 0.078 3 0.38

Electronic system 3 0.5 0.078 2 0.25

Bad installation of the humidification system 2 0.333 0.052 3 0.17

Improper battery charging 2 0.333 0.052 3 0.17

Voltage fluctuations 2 0.333 0.052 2 0.11

Difficulty using the ventilator 2 0.333 0.052 2 0.11

Transients caused by other loads with the same power 1 0.166 0.026 3 0.04

Pneumatic system 1 0.166 0.026 1 0.01



J Global Clinical Engineering Vol.4 Issue 2: 2021  22

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

Table 5 shows the failures that occurred most frequently 
in the remaining ICU medical equipment’s consultation 
forums and Table 6 shows the risk level assigned after 
considering the priority levels obtained from the analysis.

The performance of each piece of equipment was 
obtained from considering the high and medium priority 
levels. Accordingly, we established the following Risk Levels:

• High: 75≤PL≤100. The equipment’s operation presents 
failures that must be addressed immediately since 
its impact directly affects the patient’s condition. 
The actions to be taken must be a priority so that the 
failure does not cause a significant problem.

• Medium: 51≤PL≤74. The equipment generally works 
as expected, but some elements indicate that a fail-
ure could compromise the performance and have 
consequences for patient care.

• Low: 0≤PL≤50. The equipment works ideally or 
closely. Care measures should focus on maintaining 
and improving its functioning to have the level of 
risk under control.

FIGURE 3. Ishikawa diagram for the volumetric ventilator failure analysis. Modified from 19

TABLE 5. Most Frequent Failure Causes in the ICU Medical 
Equipment 

Failure Medical Equipment

Suspension of electrical service Apnea Monitor
Emergency electrical system Apnea Monitor

Suspension of electrical service Central Monitoring
Emergency electrical system Central Monitoring

Wear of controls, handles and knobs Hospitalization Bed
Connections box Hospitalization Bed

Difficulty using the hospitalization 
bed Hospitalization Bed

Lack of knowledge in the use of the 
control, calibration and adjustment 

system (software)
Infusion Pump

Emergency electrical system Infusion Pump
Voltage fluctuations Infusion Pump

Hold alarm Infusion Pump
Emergency electrical system Portable X-ray system

Overheating Portable X-ray system
Inactivity Portable X-ray system

Suspension of electrical service Portable X-ray system
Inefficient equipment placement Portable X-ray system



23 J Global Clinical Engineering Vol.4 Issue 2: 2021

Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

DISCUSSION

Risk management is a crucial element for the efficient 
management of medical technology. Unfortunately, its 
principles and applications in this area have not yet 
reached a desired level of consolidation, so work on 
this issue should be promoted. In a critical area, the risk 
management repercussions impact both the patient 
and the operator, even reaching the infrastructure due 
to the complicated relationship these components have 
for functioning. Failure analysis is an approach to risk 
management that allows evaluating quality, in this case, 
reflected in operation, and provides elements that can be 
integrated with those used to manage medical equipment, 
such as schedules and maintenance reports, preventive or 
corrective maintenance documents. These components 
provide relevant information, but it is their systematic 
and well-documented integration that adds value for 
the development of action plans to control these failures.

The FMEA method has proven to be a practical analytical 
element in different settings. At ICU, it has been applied 
to evaluate clinical aspects such as pressure injury due 
to critical illness combined with interventions and thera-
pies.16 When adapting some of the FMEA components to 
the information obtained from the ICU’s equipment, it is 
possible to analyze the interaction between the different 
natures of the causes that generate failures. The Ishikawa 
diagrams complemented the analysis by contrasting the 
practical occurrence of the failures reported in the fo-
rums, with which they report the technical and operation 
manuals, which we would consider as more formal and 
official documentation.

The consultation and discussion forums are a source that 
may not offer high reliability compared to the information 
obtained from more official and formal documentation 
such as technical or operating manuals. However, their 
presence in the community shows a practical reality of 
the failures that appear in the engineers’ and technicians’ 
daily actions and technicians in charge of attending to the 
equipment considered; it also represents a need to share 
and communicate problems and solutions at a higher 
level of specificity. The quality of this source depends on 
the seriousness with which the community presents the 
cases and their responses; we assume this requirement 
is met given these forums’ purpose. 

The results show that in practice, ICU medical equip-
ment requires constant and detailed care. None of the 
equipment was considered obtained at a low-risk level; 
this implies a constant presence of risk that may come 
from different sources. Portable X-ray is the device with 
the lowest risk level; although it is not continuously used, 
its most prevalent causes are related to infrastructure 
and operating conditions. In contrast, the monitoring 
devices are the ones that obtained a higher score in the 
level of risk; problems associated with the quality of the 
electrical system are more prevalent as causes of failure. 
In the case of the vital signs monitor (case 2), it is striking 
that the difficulty in its use has a high priority. The lack 
of knowledge of the control console’s use for calibration 
and adjustment (software) has medium priority, and the 
lack of manuals and documentation has low priority. The 
location of these causes in the Ishikawa diagram indicates 
that they have a high impact on the occurrence of potential 
equipment failure. With this information, a latent training 
need and the development of support material in Spanish 
for staff can be inferred.

The defibrillator is another device that scored high 
risk, and both the level assigned to the high and medium 
priority causes generally match its location on the Ishikawa 
diagram. This situation indicates that it is clear what ac-
tions must be taken to control this equipment’s risk, those 
related to the electrical supply, its use, the battery’s charge, 
and electrodes. In the case of the volumetric ventilator, 
the highest priority causes are related to the operator’s 
handling of equipment components, particularly the filter 
and the power cable. When complementing the Ishikawa 
diagram analysis, a situation similar to the one presented 

TABLE 6. Risk Level Assigned to the ICU Medical Equipment 

Medical Device PL High+ Medium Risk Level

Apnea Monitor 83.33 High
Central Monitoring 87.5 High

Defibrillator 87.18 High
Hospitalization Bed 70.59 Medium

Infusion Pump 70.91 Medium
Portable X-ray 62.32 Medium

Vital Signs Monitor 84.61 High
Volumetric Ventilator 73.69 Medium



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Martinez-Licona, Perez-Ramos : A risk assessment method based on the failure analysis of medical devices in the adult 
Intensive Care Unit 

in the vital signs monitor can be seen, a training and sup-
port material problem is detected.

In general, the found results contrast with those of 
other studies that used the FMEA method in the ICU, 
where the failures with the highest priority related to 
alarms of the ventilation device17 or increased rates of 
internal infection due to the inadequate operation of the 
medical equipment18 are reported. It is important to note 
that the FMEA method’s application in each case depends 
on the quantity and quality of the information collected 
and that the value of the results will be maintained in 
direct relation to its updating.

The limitations of this article are oriented to the data 
and its scope. Information from general and non-formal 
sources was used instead of a specific source such as an ICU 
of a particular hospital or a health system. Consequently, 
the results show generalized trends in the community 
regarding the causes of failures. Therefore, the informa-
tion obtained from the analysis can be a starting point to 
develop action plans that can be improved by providing 
feedback with the particular ICU’s specific data under 
consideration.

The FMEA method is a comprehensive tool for devel-
oping risk management programs; what is proposed is 
to use some of its components to build support elements 
for these programs, focusing on specific aspects, such as 
the operation of the medical device. In a previous ap-
proach, information was considered to assign priorities 
related to functioning.19 Then, using the concepts of se-
verity, occurrence, and detection, an analysis of failures is 
complemented, attending to the causes and giving them 
a complete management approach. In this case, we used 
these concepts as a basis and adapted them by defining 
them in the context of the information presented in the 
forums. More advanced work in this field, incorporating 
information derived from tools such as orders or service 
logs, is in process.

CONCLUSIONS

The development of risk management methodologies 
that aim to monitor and solve potential hazard situations 
in critical areas is valuable to the health technology man-
agement program. The FMEA method showed a solid basis 
for the risk assessment processes, and its application to 

the ICU medical technology allowed the creation of the 
evidence supporting the decision-making process con-
cerning strategic solutions to guarantee patient safety. 

CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.

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