Application of QFD Methodology as a Planning Tool for Quality
Management on a Clinical Engineering sector at HUOL / UFRN
Jurandir Barreto Galdino Junior
Master student in Production Engineering from UFRN
Specialist in Clinical Engineering from RTG. Biomedical Engineer from UFRN Bachelor of Science and Technology from UFRN
E-mail: jurandirbarreto@ufrn.edu.br Hélio Roberto Hékis
Post Doctorate by UnB. PhD in Production Engineering at UFSC
Master in Business Administration from UDESC. Specialization in Health Informatics by UFRN Specialization in Auditing by UFSC. Degree in Accounting from UFSC
E-mail: hekis1963@gmail.com Davidson Rogério de Medeiros Florentino
Master in Production Engineering from UFRN. Specialization in Public Management from FAEL Specialization in University Hospital Management at SUS by SIRIO-LIBANÊS
Graduated in Electrical Engineering UFRN E-mail: davidsonflorentino@gmail.com
Danylo de Araujo Viana
Master student in Production Engineering at UFRN Graduated in Production Engineering from UFRN
E-mail: danyloviana@gmail.com Tiago de Oliveira Barreto
Master student in Production Engineering from UFRN
Biomedical Engineer from UFRN. Bachelor of Science and Technology from UFRN E-mail: barretotiago21@gmail.com
Ícaro Fernando Fonsêca Braga
Master student in Production Engineering from UFRN
Biomedical Engineer from UFRN, Bachelor of Science and Technology from UFRN E-mail: icaro187@gmail.com
Gyuliano Rufino Aniceto Biomedical Engineer from UFRN
E-mail: gyuliano@gmail.com Wilkson Ricardo Silva Castro
Master student in Production Engineering at UFRN Graduated in Production Engineering from UFRN
Eric Lucas Dos Santos Cabral
PhD student at the Post-Graduate Program in Petroleum Science and Engineering at UFRN Master in Production Engineering from UFRN. Production Engineer at UFRN
E-mail: ericlucascabral94@gmail.com Abstract
In a complex hospital environment, where in many cases the demands for a quality in Clinical Engineering are high and resources are low, it is important to apply tools that can assist at improving services provided by clinical engineering’s professionals. Thus, this paper aims to apply the QFD methodology as an aid tool in planning the quality of service provided by the clinical engineering team of Onofre Lopes University Hospital, with the intention of proposing improvements to be included in future planning. Initially, this research aims to discover the main needs of healthcare professionals that use services provided by the clinical engineering team, by reviewing articles on quality at hospitals environments. The target sectors of this research were chosen using as criteria the highest number of work orders (OS) generated and criticality of equipment. It is also object of study to analyze the level of satisfaction and importance that the employees of the studied sectors attribute to the clinical engineering sector. This study was conducted through semi-structured interviews, which were granted by the heads and coordinators of each sector. After completing the previous step, the quality house was built starting with translating users' needs into design requirements, and then correlating existing design requirements with finding out which design requirement is of highest relevance to meet customer needs. In the end, it will be possible to generate data that can be interpreted efficiently by the clinical engineering team, thus identify which points are working as expected and which need to be analyzed more closely in future strategic planning.
Keywords: Clinical engineering; Quality management; QFD.
1. Introduction
Nowadays, it is common to find hospitals with various kinds of difficulties related to the absence of reliable data on quality, efficiency and their care costs, creating difficulties for the hospital to improve the user satisfaction in respect to their services (GUERRA, 2011).
However, many of these problems can be reduced with an efficient management, once according to a study, developed Brito et al. (2017), hospitals that have a good adoption rate of management practices have good results regarding the occupancy rate of beds, hospitalization per hospital bed and accreditation certificates.
Moreover, with the increasing demand for qualified health services, it is essential that the hospital, along with the team of Clinical Engineering (CE) professionals, can not only offer a good quality service but also be able to plan the quality for future projects and processes to be implemented. This way, you will know which problem intervene, which process is working correctly and, thus, improve the quality of services provided (GOMIDE, PINTO, FIGUEIREDO, 2012; GIORDANI et al, 2018.).
An important point, that justifies the need for good management, is the current financial situation that most of the Brazil’s public hospitals are in, thus good management has a very important role in improving the quality of service provided by the hospital (SALDIVA; VERAS, 2017).
A possible solution for improving the CE service is the implementation of the Quality function deployment methodology (Quality Function Deployment - QFD), which was originated in Japan,
around the 60’s final and was created by Japanese’s Yoji Akao and Shigeru Mizuno, in order to analyze the quality required by its users and incorporate it in their projects. Thus, the work aims to apply the QFD methodology as a tool in the planning of the services provided by the CE sector at Onofre Lopes University Hospital (HUOL) (Akao; MAZUR, 2003).
2. Methodology
Population and SampleThe survey was conducted at the Onofre Lopes University Hospital (HUOL), consisting primarily of the choice of sectors in which the research will be applied, since it is not possible to conduct the study in all sectors of HUOL due to the enormous volume of data to be collected, processed and analyzed. Therefore, to define the sectors the criteria used was the number of work orders (WO) and criticality of them, because through these criteria you can determine which sectors have a higher demand and importance for the CE team of HUOL.
Data Collection Instrument
To carry out the survey of data on WO, spreadsheets provided by HUOL’s EC team were used, those containing all WO that occurred from March 2017 to February 2018. As the data provided were not organized by sector, but by order call, it was necessary to carry out the survey of each sector to collect the number of WO that have occurred in each month. After the survey data, the three sectors with the highest number of WO have been identified: Diagnostic Imaging Center (DIC), with 315 WO, Central Building of Hospitalization (CBH), with 233 WO and Intensive Care Unit (ICU) with 142 WO.
In the criticality survey, we used four frames provided by the CE team of HUOL, which were based in the collegiate board resolution 185, which has different criteria for each frame in which each criterion has a different score, and higher the score is the more important the criteria. Thus, the selected sections were analyzed for each frame and received a certain score, whose resultant sum of Tables 1, 2 and 3 resulted in the final score analyzed within Table 4.
Table 1 provides the principal function of the sector, as Table 2 sets out the main type of risk represented.
Table 1: Determine the main function of the sector
Function Points Support Life 10 Therapy 8 Diagnosis 6 Analyze 4 Support 2 Source: HUOL (2018).
Table 2: Determines the main type of risk inherent in the sector
Scratchs Points
Death 7
Injury 5
Therapy or diagnosis flawed 3
Without risk 1
Table 3 determines the level of importance of the full operation of the sector, and this level is determined by adding the scores of the sector in Tables 1 and 2. Thus, it is stipulated that the groups shown in Table 3 (A, B and C) correspond to the values obtained in this sum, as follows: group C (between 2 and 7 points), group B (between 8 and 13 points) and group A (15 to 17 points).
Table 3: Determine the importance of a fully functioning industry
Importance Points
A 10
B 5
C 0
Source: HUOL (2018).
Finally, the fourth frame serves to indicate what level of criticality the sector fits after being held the sum of the scores obtained in Tables 1, 2 and 3.
Table 4: Indicates at what level of criticality the sector fits
Criticality Points
Low 04-11
Median 12 to 18
Maxim 19 to 27
Source: HUOL (2018)
It was analyzed only the three sectors with the highest number of WO, added to the operating room. HUOL’S CE team indicated the operating room, because it is a sector with personalized service, with a fixed biomedical technician, so the real value of WO will not appear at the spreadsheet used in the survey of WO in the other sectors.
After the sectors have been chosen, a semi-structured interview was elaborated to evaluate the services provided by the CE team. This interview was made up with questions taken from articles involving quality management in hospitals or healthcare facilities. Through these articles, it was possible to form a database of possible requirements involving health institutions, which in turn was analyzed by the CE team of HUOL occurring to the selection of the most important needs, and the own CE team proposed some suggestions that were not contained in the database obtained by reviewing the articles.
Once sectors and 15 relevant needs for the improvement of the CE Service were chosen to be studied, a semi-structured interview based on these needs was applied. Respondents are people who know in depth the activities of each sector and, in this context, the managers and coordinators were appointed due to their property to talk about their relationship with the CE service, since they put effort in the correction of the sector's problems, and this activity develops knowledge and maintains a relationship with support services.
For each item of the interview, two types of scales were made available, and the scale 1 serves to indicate the participant's level of satisfaction with the performance of the CE team in its own sector. The scale 2 serves to indicate the level of importance that the participant industry attaches to the item in question. The scale 1 is defined as follows: very bad (1) bad (2), reasonable (3), good (4) and great (5). Since the scale 2 is defined as follows: very poor (1) poor (2), reasonable (3), high (4) and very high (5). As shown above, each evaluation is represented by a number that is used to obtain an arithmetic average of the results of all participants. This average should be an integer and represents the overall assessment of each item present in the interview.
Data Analysis
After collecting the data, it was initiated the processing step and analysis of such information. The step in question was made using the QFD method, mentioned in the introduction. However, it is necessary to mention the process to determine the direction of improvement and the existing type of importance in every relationship of arrays that comprise the house quality.
For the existing relationships, within the matrix of relationship and correlation, to be reliable with reality, it was chosen professionals who know the background of all processes involving the CE service present on the sectors studied, so that they can fill with property all relations present within the house of quality. These chosen professionals hold the following positions at HUOL: head of the infrastructure division and hospital Logistics, clinical engineer and nurse.
However, due to the limited time to conduct research and mainly due to the time availability of professional participants, it was unable to hold meetings in order to discuss what kind of relationship each relation has. Thus, each participant completed the house’s quality individually and then it was made the arithmetic mean of the results evaluated.
The frames 5, 6 and 7 show the criteria used to determine the existing level of relationship in all arrays that form the home of quality as well as the type of direction of improvement present in every technical requirement. In all these tables it shows the type of relationship, the result and the symbol to be assigned in the house of quality, depending on the arithmetic mean obtained from the evaluation of three professional participants in this research phase. The scale used to evaluate the professionals is formed by the values 0, 1, 3 and 9 in the relationship matrix, 0, 1 and 3 in the correlation matrix and 1, 3 and 9 in the direction of improvement.
Figure 5: Criteria used to determine the average value of each relationship in the relationship matrix
Condition Relationship Result to be assigned Symbol
0 ≤ arithmetic average ≤ 0.49 Nonexistent 0 In blank ≤ 0.5 1.99 ≤ arithmetic mean Weak 1
2 ≤ 5.99 ≤ arithmetic mean Medium 3 6 ≤ ≤ arithmetic mean 9 Strong 9 Source: Adapted from Slack, Chambers and Johnston (2009)
Table 6: Criteria used to determine the average value of each relationship in the correlation matrix
Condition Relationship Result to be assigned Symbol
0 ≤ arithmetic average ≤ 0.49 Nonexistent 0 In blank
≤ 0.5 1.99 ≤ arithmetic mean Positive 1 +
2 ≤ 3 ≤ arithmetic mean strongly positive 3 ++
Source: Adapted from Slack, Chambers and Johnston (2009)
Table 7: Criteria used to determine the type of each direction of improvement in existing technical requirements
Condition Result to be assigned Symbol description
≤ 1 ≤ 1.99 arithmetic mean 1 The smaller the better
2 ≤ 5.99 ≤ arithmetic mean 3 specific value
6 ≤ ≤ arithmetic mean 9 9 The bigger the better Source: Adapted from Schmid et al, (2015).
3. Results and Discussions
The first and most important criterion used to choose the sectors to be studied was the number of WO issued by sectors within one year. The figure 1 shows the three sectors with the highest number of WO.
Figure 1: Percentage OSs considering the three main sectors
Source: Authors (2018).
On the study of criticality, it was concluded that although the DIC and EBI did not show a great level of criticality, it is essential that these sectors participate in the survey due to their high demand to the CE service. Instead, the ICU showed a high level of criticality, being classified with maximum level, making it entering on the group of the target sectors of this study, due to additional the high criticality, it also has a great demand. The following table summarizes the results.
Table 1: Results of the evaluation of the criticality of the sectors studied
ICU SURGERY CENTER DIC EBI
Function Support Life Function Support Life Function Diagnosis Function Support
Points 10 Points 10 Points 6 Points 2
Scratchs Death Scratchs Death Scratchs Therapy or diagnosis
flawed Scratchs Without risk
Points 7 Points 7 Points 3 Points 1
Importance A group Importance A group Importance group B Importance group C
Points 10 Points 10 Points 5 Points 0
Total of
points 27 Total of points 27 Total of points 14 Total of points 3
criticality maxim criticality maxim criticality median criticality Low
Source: Authors (2018).
Mesurement of Satisfaction Level and Importance
After the review of literature and meeting with the CE team of HUOL, customer needs to be studied were determined and it was concluded the first stage of implementation of the QFD methodology, ie, it was discovered the “customer’s voice".
Right after, it was needed to conduct a semi-structured interview with leaders and coordinators of each studied sector, in order to find out the level of satisfaction and importance of the service provided by the HUOL’s CE team regarding each studied needed. From interview results, each item represents a necessity. 46% 34% 20% DIC EBI ICU
Figure 2 shows the results obtained by averaging the grades assigned from each sector to the level of importance and satisfaction of the CE Service, additionally figure 3 shows the standard deviation and the average of evaluations considering all the sectors studied.
We must inform that each item represents the following needs:
Item 1: What is level of clarity of information passed by the clinical engineering team during their service?
Item 2: The overall time of clinical engineering team services occurring in your sector is satisfactory?
Item 3: The team of clinical engineering explains the reason for waiting time for the requested services?
Item 4: Decisions taken by the clinical engineering team during the service to your sector are fast? Item 5: A team of clinical engineering respond immediately to inquiries made by your sector? Item 6: The team of clinical engineering fulfills the hospital's standards for compliance to your sector or in any other situation?
Item 7: What is the level of presentation and friendliness performed by the clinical engineering staff, during the service to your industry, or in any other situation?
Item 8: The clinical engineering team has a good repair time with respect to the equipment in your sector?
Item 9: How the team of clinical engineering behaves with respect to maintenance of the organization in its sector during and after treatment?
Item 10: The clinical engineering team search new investments in facilities and new equipment? Item 11: The clinical engineering team is managing to prevent a recurrence of defects of equipment in your industry?
Item 12: The maintenance of equipment in your industry is kept up to date?
Item 13: They are investments in capacity building and training of employees in your industry? Item 14: The clinical engineering team develops Preventive Maintenance (PM) schedules for equipment in your industry?
Item 15: Is there a provision of manuals in Portuguese for the equipments in your industry?
Figure 2: Average level of satisfaction and importance of each studied sector
Figure 3: High level assessment of importance, satisfaction and population standard deviation for each item
studied
Source: Authors (2018).
Besides the statistical data collected during the application of the semi-structured interviews, there were also caught opinions about the quality of service provided by the CE team, in which the main complaints concerned the need for continued training in the use of complex equipment, preventive maintenance plan, need of employees to stay longer in the sectors and a permanent technical DIC.
It is noteworthy that the high level of importance regarding customer needs proves the right choice of the greatest shortcomings needs of users from the CE service, since the work aims to study the customer's voice, i.e., their most important desires.
Assessment of Quality Houses
After being held filling the relationship and correlation matrix, in addition to calculating the total and relative importance of each technical requirement and order of operations relating to each engineering requirement, it was revealed that the technical team has a great weight in the proper functioning of the CE service, for training, operational and technical training showed to be the most important indexes to meet the main needs of the user.
It is still valid to make a positive emphasis on the technical requirements involving the use of tools such as management software, analyzers, calibrators, corrective and preventive maintenance equipment, as also have a good level of importance, with good influence on the users’ needs.
In the study done using the correlation table, it is noted that all technical requirements positively influence one another, with highlights to management software, technical staff, preventive maintenance schedule and work processes, as obtained the highest scores. This indicates that they have a high power of influence or are influenced by various requirements, demonstrating that to improve any technical part of other activities will also benefit.
In assessing the direction of improvement almost all technical requirements to favor user when they are enlarged, and management software was the exception because you need specific features that can satisfy the customer.
When using a quality home in each studied sector, it was found that the order of performance of each technical requirement was the same in all sectors, ie, the order of importance of the engineering requirements was the same in all sectors, just by changing the values of relative importance. This result
1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 Item 1 Item 2 Item 3 Item 4 Item 5 Item 6 Item 7 Item 8 Item 9 Item 10 Item 11 Item 12 Item 13 Item 14 Item 15 N ív e l d a a v a li a ç ã o SATISFACTION IMPORTANCE
shows that the adopted engineering characteristics can generate positive impact in different sectors. The quality house of each sector is shown in Figure 4, and Figure 5 shows an overview.
Figure 4: Overview of the house of the quality of services provided by clinical engineering
Source: Authors (2018)
According to the survey, it was found that the QFD can develop quality planning of a product or service, using the analysis of customer satisfaction, and collected information about their main needs and thereby help identifying and analyze the main problems involving quality management, so they can be taken to generate improvements. Thus, QFD can be used in order to improve the service provided by the CE of HUOL, whom once can propose improvements that are able to meet the main needs of users (Akao, 1990; BUTTIGIEG, DEY, CASSAR, 2016).
Since this work was not done in the hospital as a whole, maintaining focus on the most important sectors for the CE was necessary. The DIC is one of those sectors, being composed of radiology services, computed tomography, ultrasound, magnetic resonance imaging and hemodynamic and is considered an important sector to the hospital because of the high technology involved in clinical diagnosis (SALES et al., 2010).
According to the results obtained in the research, another sector that is considered important is the ICU, which is seen as one of the most critical sectors and complex within the hospital services due to difficult clinical exposure that health professionals are subjected. The need to high technology appears constantly as a safe manner, causing the medical staff to be properly trained in the use of such technologies (Massaroli et al., 2015).
The application of research in the operating room is also relevant, since this sector are carried out various types of diagnostic, therapeutic and anesthetic-surgical procedures requiring the use of high-tech equipment due to the complexity of some procedures. In addition, all the work is surrounded
by pressure and stress, making this sector considered a potential high risk scenario (GUTIERRES et al., 2018).
Finally, the EBI, is considered one of the most important sectors for the CE team performance of HUOL due to have been found in this work as the second sector with higher demand, secondly only to the DIC.
In the work of Souza, Miracle, Soares (2012) and Souza (2012), it was found that the EC plays an important role on the researched hospital. Since its implementation, it was possible to realize a reduction of approximately 20% in savings related to maintenance, as well as its stabilization on the following years, which generated savings of R$ 7.6 million on the period from 2001 to 2010. It can be seen that the EC was able to promote the improvement in cost efficiency and technology management, performing an important role within the hospital.
A CE plays an important role in the safety and well being of patients as well as the quality and reduced related costs to medical equipment maintenance, since health expenditures have grown considerably. Therefore, the CE has shown good contributions related to the distribution of resources and improving the quality of care in health as a whole (Coarse, rough, 2015).
According Port and Marques (2016), it was found that with a CE department well structured, it is possible to achieve a better hospital in the socioeconomic, operational and technical directly or indirectly context, generating gains on patient care quality, which corroborates the findings about the importance of the CE work within a hospital.
Despite the scarcity of scientific publications related to the use of QFD for quality planning in CE, you can find use for this tool in healthcare. A study developed by Buttigieg, Cassar and Dey (2016), concluded that QFD is effective in improving quality of care on the emergencies of a large hospital trauma sector, due to the importance given to user view.
The results of this study also agree with other studies, where QFD was also useful for the planning of preventive maintenance on medical equipment, demonstrating its usefulness to the CE area, since the management of corrective and preventive maintenance of medical equipment is a routine. In addition, QFD can also be used at the equipment acquisition stage (SALEH et al., 2013; PORTO, MARQUES, 2016).
In a study conducted by Raziei et al. (2018), QFD was applied in concurrence with SERVQUAL, to evaluate the quality of service of a public hospital, where it was found that QFD can be useful for quality management in a health environment, as this tool can plan quality based on the needs of hospital clients and thereby meet their expectations.
QFD can also be used as part of the EC continuous improvement project, improving economic and social outcomes of the hospital. This is possible due to QFD's ability to identify key customer preference and use that to improve the quality of service (LIMA, 2008).
Another important conclusion of this study was the importance of a management software in the management of medical equipment and the help of technical requirements. Since this management tool demonstrates importance in the daily processes of an CE team, for the management of data that can make all the technological hospital park equipment, managing to identify breaking standards and thus enhance the activities undertaken by all members of the CE team and hence improve the quality of service (LUCA, CIORAP 2011; MCCULLOUGH, REED, KAUFMAN-RIVI, 2012).
The use of computerized systems for management of medical equipment and maintaining a qualified technical team can provide an improvement in the quality of services offered to patients, as well as the reduction of costs related to hospital equipment (AMORIM; PINTO JUNIOR; Shimizu, 2015).
The use of management software for medical equipment has demonstrated advantages over conventional management through the use of paper, thus using the software can reduce the time of tasks execution, simplifying the management of information and reducing the likelihood of errors, which makes this useful tool for all processes belonging the CE (ABAYAZEED; HAMZA, 2010).
Despite the positives, QFD has some limitations that must be taken into account, as the way of processing the data, because the subjectivity contained in the data obscures the analysis. Furthermore, it is needed some time to study the QFD before its implementation, which implies an increase of project duration (MOTA, 1996; PRA, MIGUEL, 2013; Fiorenzo, 2017).
In a future work is plausible to consider the use of fuzzy logic applied to the QFD methodology, since this type of logic can result in a major solution for occurring assessments during application of the methodology in question. Since the fuzzy logic can handle recurring variable information during the application of QFD. Moreover, it is also possible to apply the method with Delphi QFD and fuzzy logic, since Delphi can also be used to lend credibility to indicators (YAMAKAWA et al, 2014.;CHEN, LIN, Tseng, 2015; HSU, CHANG, LUO, 2017).
4. Conclusions
Taking into account the aim of this study, ie, use the QFD methodology as an aid tool in planning the quality of service provided by the CE team of HUOL, as well as assess the level of user satisfaction and then translate the main needs of customers design requirements, in order to propose improvements to be included in strategic planning. It is concluded that the QFD methodology was able to achieve results that indicate ways to improve the service provided to the sectors studied, as the strengths, weaknesses of the CE were discovered, in addition to the main needs of its users, and technical requirements capable of satisfy them.
Thus, the application of QFD can be considered successful despite limitations such as lack of time to conduct the study in more sectors, difficulty getting meetings with the medical staff and the CE, apart from the relatively small number of participants in the satisfaction survey.
In future work we can consider the possibility of using the four levels of QFD methodology on the sectors studied, applying this tool in the hospital as a whole, analyzing the standard deviation of the behavior and the reasons for the divergence of views between sectors. Another possibility is to add the fuzzy logic and the Delphi method as a way to complement the use of QFD.
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