Structured Abstract
Purpose
There is a growing awareness on the use of systems approaches to improve patient safety and quality. While earlier studies evaluated the validity of such approaches to identify and mitigate patient safety risks, so far only little attention has been given to their inputs, such as structured brainstorming and use of system mapping approaches (SMAs), to understand their impact in the risk identification process. To address this gap, this study evaluates the inputs of well-known systems approach, Failure Modes and Effects Analysis (FMEA), in identifying patient safety risks in a real healthcare setting.
Design
This study was conducted in a newly established Adult Attention Deficit Hyperactivity Disorder (ADHD) service at Cambridge and Peterborough Foundation Trust in the UK. Three stakeholders of the chosen service together with the facilitators conducted an FMEA exercise along with a particular system diagram that was initially found as the most useful SMA by eight stakeholders of the service.
Findings
In this study, it was found that the formal structure of FMEA adds value to the risk identification process through comprehensive system coverage with the help of the system diagram. However, results also indicates that the structured brainstorming refrains FMEA participants from identifying and imagining new risks since they follow the process predefined in the system diagram given.
Conclusions
While this study shows the potential contribution of FMEA inputs, it also suggests that healthcare organisations should not depend solely on FMEA results when identifying patient safety risks; and therefore prioritising their safety concerns.
Keywords: Patient safety, risk identification, FMEA, system mapping approaches, brainstorming
Introduction
The problem of the high rate of medical errors and their serious consequences on patient safety and quality have been discussed in various studies since the pioneer report of the Institute of Medicine (IOM), To Err Is Human: Building a Safer Health System (IOM, 2000). In response to this problem, one of the recommendations was made on risk management to provide substantial and sustainable improvements in patient safety and quality (Card et al., 2014).
Over the last few decades, risk management has gradually become a valuable tool to assist organisations in improving the effectiveness of care delivery (NPSA, 2006). As Vincent (2001) emphasized, risk management has matured in crucial ways, and has begun to have a positive impact on patient safety and quality of care, rather than simply addressing potential losses as a result of litigation. While retrospective methods, such as incident reporting and investigation, have been embedded in various healthcare contexts in the last two decades (Kurutkan et al., 2015; Simsekler, Card, Ruggeri, et al., 2015), proactive methods are still underused to identify patient safety risks (Simsekler, Card, Ward, et al., 2015; Simsekler et al., 2018a).
Proactive risk management methods are in general systems approaches broadly and successfully utilised in other safety-critical industries, including chemical and aerospace industries (Ward et al., 2010). As suggested by earlier studies, healthcare can potentially be improved by learning from the experiences and methods used in other safety-critical industries to identify a comprehensive list of risks proactively. Since the nature of health systems is dynamic and complex, such systems approaches embedded in proactive methods seem crucial to accelerate improvement in patient safety and quality of care delivered (Carayon et al., 2014).
While more than a hundred systems approaches are used in a range of safety-critical industries; most of the methods have not been applied in the healthcare field (Simsekler, Card, Ward, et al., 2015). From such methods, FMEA has got greater recognition in healthcare since 1990s, and, in turn, it is one of the most widely known and practiced proactive risk assessment tool (Ward et al., 2010).
Due to its popularity, FMEA has been extended and similar methods were developed on it. These methods are called FMECA (Failure Mode Effects and Criticality Analysis) and HFMEA (Healthcare Failure Mode and Effect Analysis). For instance, HFMEA was developed to make the structure of FMEA more appropriate to healthcare settings (Habraken et al., 2009). Providing the system details are available, HFMEA aims to help analyse system factors to identify hazards at a functional level (DeRosier et al., 2002).
As a prospective hazard analysis approach, FMEA is used to identify the ways components, systems, or processes could fail to fulfil the intention of their design (ISO 31010, 2009). This approach is a well-documented process, requiring in-depth knowledge of the system studied (NASA, 1998); it therefore needs a strong multidisciplinary team, including a leader and members from different professional backgrounds with wide collective experience (Alamry et al., 2017).
Despite the benefit FMEA has brought to healthcare because of its prospective nature, many limitations were also noted in the literature. These limitations were mainly about time and cost constraints, and the difficulty of gathering a team for the analysis (Lago et al., 2012). As Potts et al. (2014) emphasised, such issues may limit the effective use of FMEA in healthcare. For instance, van Tilburg et al. (2006) reported that the entire HFMEA process required more than seven meetings, a total of 140 man-hours, something generally difficult to arrange in healthcare settings where time and resources are limited.
Further discussions have also addressed the validity of FMEA in the healthcare context (Franklin et al., 2012; Shebl et al., 2012). Several studies have shown that different professional teams identified different risks for the same healthcare setting, and some discrepancies were found in the grading of the same risks (Ashley and Armitage, 2010; Shebl et al., 2009). Potts and colleagues (2014) also stated that it is not surprising that different outcomes can be reached by different teams in applying the same risk assessment tool because of the subjective nature of the analysis. Due to such issues, Shebl et al. (2012) proposed that healthcare organisations should not depend solely on the results of FMEA in prioritising patient safety issues. Apart from such issues, it was addressed that the tabular structure of an FMEA does not allow assessors to visualise the system and then identify some other potential risks in the system (Battles et al., 2006; Ward et al., 2010). As a result, the FMEA could not list all necessary risks and lead to unreliable risk identification unless it is supported by the use of system mapping approaches (SMAs, also known as process maps, process models and diagrams). In order to overcome such issues and improve the reliability of FMEA, use of SMAs are recommended along with FMEA exercises so as to visualise and capture potential failure points in a given system (Battles et al., 2006; Ward et al., 2010). In turn, a more comprehensive overview of risks could be identified and more reliable results could be achieved by the analysis.
As the primary research on SMAs in healthcare risk assessment, Jun et al. (2009) evaluated the applicability of various mapping approaches in patient safety context. Following this research, Clarkson and his colleagues identified and shortlisted six SMAs, as below, in the Prospective Hazard Analysis (PHA) toolkit to provide fundamental visual representations in the application of prospective hazard analysis approaches (Clarkson et al., 2010).
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1-
Task diagrams describe a hierarchy of operations and plans
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2-
Information diagrams describe a hierarchy of information and/or material
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3-
Organisational diagrams describe a hierarchy of people and/or roles within organisation(s)
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4-
System diagrams represent how data are transferred through activities
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5-
Flow diagrams represent activities occurring in sequence or in parallel
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6-
Communication diagrams represent information and material flows between people and process
A recent study also provided guideline to understand the capability of these six SMAS in identifying different risk sources, such as equipment-related risks, task-related risks, patient-related risks, environmental risks, staff-related risks, communication risks, and organisational risks (Simsekler et al., 2018b). While all these studies evaluated the usability of SMAs in different healthcare settings (Clarkson et al., 2010; Jun et al., 2010; Simsekler et al., 2018), still only limited research results are available to validate the successful embedment of SMAs within the use of prospective hazard analysis tools, such as FMEA, and how helpful they are in risk identification within the scope of risk assessment.
One another important outcome was a result discovered during the HFMEA exercise conducted by Potts and his colleagues (2014). The team raised a central patient safety issue, patient understanding, during the discussion in the HFMEA. However, this issue was not included in the final results of the HFMEA, as it did not readily fit the nature of the structured brainstorming process in FMEA. Many other issues, related to health and safety, hygiene, and sharps, were also discussed; these were also largely absent in the HFMEA results. This may be an important result, demonstrating that structured brainstorming as an input in HFMEA may hinder the imagination of new risks, or may cause safety issues to be disregarded that need to be included in the final results of the chosen method.
Such issues lead us to address the question on the usability and utility of inputs - structured brainstorming and systems mapping approaches - in prospective risk management tools in the healthcare context, particularly in the identification of patient safety risks. Therefore, in this study, we aim to understand how the use and selection of systems mapping approaches and the nature of brainstorming play a role in FMEA exercise. It is also vital to understand how such inputs are treated in the context of patient safety in the healthcare field. Therefore, this study integrates systems mapping approaches into a real FMEA exercise along with its brainstorming component to clarify how systems mapping approaches along with the structured brainstorming contribute to the FMEA in identifying risks in a real healthcare setting.
Methods
Study Setting and Participants
This study was carried out in a newly established service, called the Adult ADHD (Attention Deficit Hyperactivity Disorder) Service, based at the Cambridge Peterborough Foundation Trust (CPFT) in the UK. This service provides services to people experiencing ADHD after the age of seventeen. Having a multidisciplinary team of professionals, led by a consulting psychiatrist, the service provides specialist diagnostic services and delivers a range of pharmacological and psychosocial interventions for those with adult ADHD.
Table I shows the characteristics of each participant including job title, the years of experience in the British National Health Service (NHS), experience on the use of SMAs and experience on risk assessment.
Table I. Participants Information.
No | Job title | Experience in the NHS | Familiarity with SMAs | SMA Evaluation | FMEA Evaluation | Experience in Risk Assessment |
---|---|---|---|---|---|---|
1 | Service Manager | 28 years | Medium | ✓ | ||
2 | Consultant Psychiatrist | 24 years | Very familiar | ✓ | ✓ | Medium |
3 | Specialist Psychiatrist | 10 years | Medium | ✓ | ||
4 | Admin Support | 3.5 years | Not familiar at all | ✓ | ||
5 | Clinical Psychologist | 13 years | Not familiar at all | ✓ | ✓ | A little |
6 | Clinical Psychologist | 5 years | Not familiar at all | ✓ | ✓ | A little |
7 | Specialty Registrar | 12 years | Medium | ✓ | ||
8 | Nurse Specialist | 24 years | Medium | ✓ |
As the primary step in this study, eight participants from the chosen healthcare setting were involved in individual workshops to evaluate the usability of the SMAs in their healthcare setting with the help of two facilitators, as shown in Table I. We first shortlisted six of the SMAs in accordance with the Prospective Hazard Analysis (PHA) toolkit (Clarkson et al., 2010) to determine their potential contribution to general risk identification and to assess their ability to identify different types of risk sources. For the purpose of this study, the aim in the SMA evaluation was to help the stakeholders of the chosen service to select the best matching SMA to use throughout the FMEA exercise.
As exclusively detailed in our recent study (Simsekler et al., 2018), the results showed that the system diagram was the most useful SMA to identify patient safety risks in the chosen healthcare setting since it includes a comprehensive view on system components, such as stakeholders, tasks, and data transfers throughout the process, in one picture (see Appendix). As the secondary step in this study, we conducted the FMEA exercise along with the most useful SMA – system diagram – identified in the primary step. For the FMEA exercise three participants and two facilitators were involved.
Procedure
At the beginning of the FMEA exercise, the facilitators, the research background, and the aim of the study were first introduced to the participants. The tabular structure of the FMEA process, as shown in Table II, was then introduced to the participants in greater detail as follows:
Describing the system; identifying system components and system functions in order, by following the chosen SMA; system diagram
Identifying the failure modes
Determining the potential cause of each failure mode
Determining the immediate effect of each failure mode
Determining the system consequences
Determining the current controls
Ranking the likelihood of failure mode effects
Ranking the severity of failure mode effects
Grading the risk (severity x likelihood; hence identifying low, medium, and high risks)
Table II. Example FMEA worksheet.
ID | Component | Function | Failure mode | Potential cause | Immediate effect | System consequence | Current control | Likelihood | Severity | Risk |
---|---|---|---|---|---|---|---|---|---|---|
1 | ||||||||||
2 |
The first two column headings in the FMEA table (component and function headings, as shown in Table II) were filled out by the facilitators by following the chosen system diagram. This served as the main component of the bridge to be constructed between the system diagram and FMEA. Following the activity stages in the system diagram, each system component and function were identified for each possible risk. A range of failure modes associated with the functions were then listed by the facilitators.
As shown in Table II, FMEA has no explicit risk identification process for identifying the risk components, such as hazard, cause, and effect. However, failure mode, potential cause, and immediate effect serve as equivalents that can be associated with risk identification. After identifying the failure modes, participants were asked to identify the potential cause, immediate effect, system consequence, and current control for each failure mode. After these, severity and likelihood dimensions were assessed for each component identified. These were then multiplied to arrive at the risk priority number, based on the grading matrix used by the Trust. Although Table II provides the whole process of the FMEA, in this study we focused solely on the first five steps, since they are the only ones relevant to risk identification within the scope of the risk assessment process.
After completing the FMEA exercise, the participants were also asked to provide further comments on the use of system diagram and structured brainstorming process during the FMEA. Due to the limited number of participants and possibility to obtain limited quantitative results via statistical analysis, we verbally asked the following statements to the participants to gather their opinions for the purpose of the evaluation in the study.
Statement 1. I found FMEA is helpful in risk identification
Statement 2. Listing all potential failure modes in FMEA is helpful in risk identification
Statement 3. I found the use of system diagrams is helpful in risk identification
Statement 4. Brainstorming through FMEA is helpful in risk identification
Statement 5. The same risks can be identified without using FMEA
Statement 6. FMEA helped me become more aware of system-wide safety risks
Results and Discussion
In general, the FMEA session was constructive and interactive, with valuable insights contributed by all participants. Team participation in risk identification, and then grading the risks, was high. The identified risks can be seen in Table III.
Table III. Risks identified in the FMEA session.
ID | Component | Function | Failure mode | Potential cause | Immediate effect |
---|---|---|---|---|---|
1 | Admin or Manager | Check documents | Partial failure - fail to check all documents | Overtasking | Clinicians receive incomplete patient information |
2 | Admin or Manager | Check documents | Untimely operate - check documents late | Overtasking | Delay patient admission and assessment |
3 | Nurse prescriber | Review document | Untimely operate - review documents late | Overtasking | Delay patient admission and assessment |
4 | Admin or Manager | Add patient to waiting list | Complete failure - fail to add patient to WL | Inadequate IT facilities | Miss patient admission and assessment |
5 | Admin or Manager | Add patient to waiting list | Incorrectly operate - appointment date/time incorrectly added | Inadequate IT facilities | Delay patient assessment |
6 | Admin or Manager | Send appointment letter & questionnaires | Complete failure - fail to send | Inadequate IT facilities | Miss patient admission and assessment |
7 | Admin or Manager | Send appointment letter & questionnaires | Incorrectly operate - send incorrect appointment date/time | Inadequate IT facilities | Delay patient assessment |
8 | Admin or Manager | Send appointment letter & questionnaires | Incorrectly operate - send to incorrect address | Incorrect information from GP | Delay patient assessment |
9 | Psychiatrist | Conduct psychiatric interview | Incorrectly operate - conduct interview incorrectly | Inexperienced trainee | Incorrect diagnosis |
10 | Psychiatrist | Conduct psychiatric interview | Untimely operate - interview patient late | Overtasking | Delay patient assessment |
11 | Psychiatrist | Review neurodevelopmental history | Untimely operate - review history late | Incomplete neurodevelopmental history | Delay patient assessment |
12 | Psychiatrist | Generate assessment report | Untimely operate - generate report late | Overtasking | Delay patient treatment |
13 | Psychologist | Conduct psychiatric interview | Incorrectly operate - conduct interview incorrectly | Inexperienced trainee | Incorrect diagnosis |
14 | Psychologist | Conduct psychiatric interview | Untimely operate - interview patient late | Overtasking | Delay patient assessment |
15 | Psychologist | Review neurodevelopmental history | Untimely operate - review history late | Incomplete neurodevelopmental history | Delay patient assessment |
16 | Psychologist | Generate assessment report | Untimely operate - generate report late | Overtasking | Delay patient treatment |
17 | Nurse prescriber | Conduct pre-drug assessment | Untimely operate - conduct assessment late | Clinical equipment problem | Delay pre-drug assessment |
18 | Nurse prescriber | Provide dose titration & monitoring service | Partial failure - fail to provide complete monitoring service | Patients don't attend monitoring session | Complete medical treatment failure |
19 | Nurse prescriber | Provide dose titration & monitoring service | Incorrectly operate - titration is incorrect | Patients don't follow instructions | Overdosing |
20 | Psychiatrist | Supervising prescribing | Untimely operate - fail to supervise in time | Overtasking | Delay patient medical treatment |
21 | Admin or Manager | Discharge patient to primary care | Incorrectly operate - discharge patient without proper follow-up | No shared protocol with GP | GP is unable to carry out prescribing & monitoring |
22 | Admin or Manager | Discharge patient to primary care | Untimely operate - unable to send discharge documents in time | Inadequate IT facilities | Delay patient discharge |
In general, FMEA exercise provided a direct link between system components and risk components. We identified 22 risks (see Table III) from the part of the system that we were able to cover in the course of the FMEA exercise. It was helpful to rank the system elements in terms of risks. It was observed that the success of the risk identification process in FMEA was primarily related to the system description provided by the system diagram, which helped define system components, functions, and failure modes, in order. We also found that the FMEA success was related to the motivation of the participants in the brainstorming session. It was noted that participants’ positive motivation could enhance the risk identification process by identifying multiple causes and effects for each failure mode.
During the FMEA exercise, the participants found the system diagram very helpful. It is a relatively new finding of this study that service users were given freedom to select the most suitable SMA; a valuable insight into the study was gained because the users chose the diagram. Although the use of the system diagram provided a contribution to this research, it was also determined that this helped identify known risks, within the limits of its capability, as found in an earlier study (Colligan et al., 2010). Due to the nature of the system diagram, no external risks were captured — a fact criticised by the participants concerned with critical safety issues in the service. It can therefore be assumed that the validity of FMEA is relevant to the chosen SMA, and its power to represent the system. It should also be noted that with FMEA, the role of facilitators is in general very important. In this case, although the facilitators had had experience with PHA in general, the current study was the first in which they had served as facilitators; this too might have had an impact on the quality of the results. At the end of the FMEA session, we verbally asked six statements to gather the participants’ opinions on the overall study. As mentioned in the first statement, the participants found the FMEA to be an acceptable and positive approach towards identifying risks proactively. Throughout the FMEA exercise, listing all potential failure modes in a spreadsheet was helpful in identifying risks in a useful manner. Further, the participants indicated that the system diagram was helpful in guiding the analysis of risk identification though it was limited to identify environmental risks. They also stated that while they became more aware of system-wide safety risks, they were still not sure whether FMEA was helpful in covering all relevant risks in their healthcare service. Further, participants mentioned that they had expected to be able to address some important concerns they had about the service, but following the structure given in the system diagram prevented them from raising these concerns and even imagining new risks. The participants also pointed out the importance of the facilitators’ role in completely considering all system functions within the time allotted for the FMEA exercise.
As experienced in an earlier study (Potts et al., 2014), a potential limitation of FMEA was found in the identification of external and environmental risks, as they were not addressed in the chosen system diagram. For instance, during the FMEA exercise one participant highlighted an issue regarding the physical environment of the service. However, this issue was not included in the FMEA result, since the failure modes were only identified based on the process steps shown in the system diagram, and no identification of external risks was allowed. Therefore it can be shown that the structured brainstorming through the use of system diagram or any other types of diagrams, such as work flow diagram, in FMEA may refrain participants from identifying some other types of risks that are out of the scope of the chosen diagram. With such limitations, it can be said that the outputs from FMEA should not be relied upon in isolation as highlighted in earlier studies (Shebl et al., 2009). Therefore, they should be treated as a valuable output supporting the overall risk identification in any chosen healthcare settings. Some recent studies also supported the value of FMEA in particular healthcare settings, and indicated that FMEA can be an effective approach for quality improvement (Alamry et al., 2017; Rosen et al., 2015).
As experienced in earlier studies (Ashley and Armitage, 2010; Shebl et al., 2009), it can be said that different results might be obtained with different and/or more participants in another longer study, but it was observed that the limited number of participants allowed for more accurate capture of the perceptions of the participants. As shown in earlier studies (Ashley and Armitage, 2010; Potts et al., 2014), although participants had differing views on potential risks in some cases, they were easily able to reach a consensus during the analysis of each failure mode. Considering how little time for risk assessment is often allotted in healthcare, it is worth remembering that a small group of people can often reach consensus quickly.
It can be concluded that the efficacy of FMEA was directly affected by the chosen SMA (system diagram in this study), time, the experience of facilitators and participants, the number of participants, and their motivation as a multidisciplinary team. Having better options available for these factors may provide better results on the validity of FMEA that was addressed in earlier studies (Potts et al., 2014; Shebl et al., 2012). Further, practical aspect of the FMEA will also be enhanced through a better use of inputs, such as selecting the most helpful system mapping approaches and using the knowledge and experience of facilitator and participants during the brainstorming session.
Conclusions
This study addressed and elaborated the impact of the primary inputs – SMAs and structured brainstorming – utilised throughout the FMEA exercise. Regarding the results of the FMEA exercise, it can be said that FMEA has merit in risk identification, but also had limitations experiences in this study.
It was concluded that FMEA provided a useful opportunity for detailed risk identification using system diagram along with structured brainstorming, but healthcare organisations should not depend solely on the results of the FMEA in identifying patient safety risks. However, the primary inputs of this approach, such as brainstorming and SMAs, would contribute to the improvement of current risk identification practices with a better adaptation to the healthcare context.
Supplementary Material
Acknowledgements
We acknowledge all the hospital staff who voluntarily participated in this study at the Adult ADHD Service at the Cambridge Peterborough Foundation Trust.
The system diagram used throughout the FMEA exercise was generated by using Cambridge Advanced Modeller (CAM) (Wynn et al., 2010). We also thank Dr Jieling Long for his substantial support and collaboration in modelling SMAs.
Funding
This work was partly supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England, at Cambridgeshire and Peterborough NHS Foundation Trust.
Footnotes
Competing Interests
The authors declared no potential conflicts of interests with respect to the authorship and/or publication of this article.
Provenance and Peer Review
Not commissioned; externally peer reviewed.
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