Evaluating inputs of failure modes and effects analysis in identifying patient safety risks

Autor: P. John Clarkson, James Ward, Gulsum Kubra Kaya, Mecit Can Emre Simsekler
Přispěvatelé: Simsekler, Mecit Can Emre [0000-0002-1555-5012], Apollo - University of Cambridge Repository
Rok vydání: 2019
Předmět:
Zdroj: International Journal of Health Care Quality Assurance. 32:191-207
ISSN: 0952-6862
DOI: 10.1108/ijhcqa-12-2017-0233
Popis: 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). 1- Task diagrams describe a hierarchy of operations and plans 2- Information diagrams describe a hierarchy of information and/or material 3- Organisational diagrams describe a hierarchy of people and/or roles within organisation(s) 4- System diagrams represent how data are transferred through activities 5- Flow diagrams represent activities occurring in sequence or in parallel 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.
Databáze: OpenAIRE
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