Article

Using the functional resonance analysis method on the drug administration process to assess performance variability

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  • Istanbul Medeniyet University, Istanbul
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Abstract

The complex and dynamic features of neonatal intensive care units (NICUs) have made it necessary to think beyond traditional safety management approaches. The Functional Resonance Analysis Method (FRAM) was thus developed to explore how functional variability affects the overall system. This study performs the FRAM on the drug administration process in a NICU to understand performance variability as conditions change, as well as to understand how variability in functions influences the system in terms of both success and failure. A mixed methods approach was used, including observations, interviews and workshops. From the data obtained, we identified 21 foreground and 16 background functions and developed 58 scenarios in relation to the effects of potential variability on the system. This study shows that the FRAM can be used to determine how to respond to changing conditions, to anticipate how variability might lead to system success or failure, to understand how to monitor it and to learn from all these.

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... 31,40 There was one (3.2%) each from Canada, 36 Italy, 28 Norway, 7 Scotland, 25 and Sweden. 45 22,23,30,36 and one (3.2%) each of secondary analysis of qualitative data 2 and grounded theory. 18 Most of the research studies took place in a hospital, including three (9.7%) each in intensive care 21,27,41 and in the emergency department, 33,38,42 two (6.5%) in neonatal intensive care, 22,23 and one (3.2%) each in an operating room, 45 geriatric evaluation and management, 19 cardiosurgical department, 20 neurosurgery, 28 and a spine center. ...
... Concepts that provide a background understanding of the principles from which the FRAM was developed were explained in many of the papers (n ¼ 14; 45.2%). The two most-discussed concepts were ''Work as Imagined and Work as Done'' (n ¼ 14; 45.2%) 2,10,18,19,23,25,31,33,36,37,40,41,43,45 and Safety II (n ¼ 12; 38.7%). 2,10,[19][20][21][22][23]28,35,37,40,43 Resiliency in health care was another concept discussed in eight (25.8%) of the included papers. ...
... The two most-discussed concepts were ''Work as Imagined and Work as Done'' (n ¼ 14; 45.2%) 2,10,18,19,23,25,31,33,36,37,40,41,43,45 and Safety II (n ¼ 12; 38.7%). 2,10,[19][20][21][22][23]28,35,37,40,43 Resiliency in health care was another concept discussed in eight (25.8%) of the included papers. 10,18,21,23,28,30,43,45 The majority of papers in this review provide a definition or description of the FRAM by explaining activities or functions in a process and the steps necessary to operationalize the FRAM (n ¼ 25; 80.6%). ...
Article
Objective: The objective of this review was to examine and map the literature on the use of the Functional Resonance Analysis Method (FRAM) in health care research. Introduction: The FRAM is a resilient health care tool that offers an approach to deconstruct complex systems by mapping health care processes to identify essential activities, how they are interrelated, and the variability that emerges, which can strengthen or compromise outcomes. Insight into how the FRAM has been operationalized in health care can help researchers and policy-makers understand how this method can be used to strengthen health care systems. Inclusion criteria: This scoping review included research and narrative reports on the application of the FRAM in any health care setting. The focus was to identify the key concepts and definitions used to describe the FRAM, the research questions, aims, and objectives used to study the FRAM, the methods used to operationalize the FRAM, the health care processes examined, and the key findings. Methods: A three-step search strategy was used to find published and unpublished research and narrative reports conducted in any country. Only papers published in English were considered. No limits were placed on the year of publication. CINAHL, MEDLINE, Embase, PsycINFO, Inspec Engineering Village, ProQuest Nursing & Allied Health were searched originally in June 2020 and again in March 2021. A search of the gray literature was also completed in March 2021. Data were extracted from papers by two independent reviewers using a data extraction tool developed by the reviewers. Search results are summarized in a flow diagram, and the extracted data are presented in tabular format. Results: Thirty-one papers were included in the final review, and most (n = 25; 80.6%) provided a description or definition of the FRAM. Only two (n = 2; 6.5%) identified a specific research question. The remaining papers each identified an overall aim or objective in applying the FRAM, the most common being to understand a health care process (n = 20; 64.5%). Eleven different methods of data collection were identified, with interviews being the most common (n = 21; 67.7%). Ten different health care processes were explored, with safety and risk identification (n = 8; 25.8%) being the most examined process. Key findings identified the FRAM as a mapping tool that can identify essential activities or functions of a process (n = 20; 64.5%), how functions are interdependent or coupled (n = 18 58.1%), the variability that can emerge within a process (n = 20; 64.5%), discrepancies between work as done and work as imagined (n = 20; 64.5%), the resiliency that exists within a process (n = 12; 38.7%), and the points of risk within a process (n = 10, 32.3%). Most papers (n = 27; 87.1%) developed models representing the complexity of a process. Conclusions: The FRAM aims to use a systems approach to examine complex processes and as evidenced by this review, is suited for use within the health care domain. Interest in the FRAM is growing, with most of the included literature being published since 2017 (n = 24; 77.4%). The FRAM has the potential to provide comprehensive insight into how health care work is done and how that work can become more efficient, safer, and better supported.
... For instance, the FRAM has been applied to analyse safety in railway traffic supervision (Belmonte et al., 2011), to investigate the key resilience characteristics of the air traffic management system (De Carvalho, 2011) and to model performance variability in oil spill accidents (Cabrera Aguilera et al., 2016). In health care, it has been used for various purposes, including to understand the performance variability in blood sampling (Pickup et al., 2017) and drug administration (Kaya, Ovali and Ozturk, 2019), to align the work-as-imagined with work-as-done in clinical guidelines (Clay-Williams, Hounsgaard and Hollnagel, 2015) and to serve as a basis for risk assessment as a complementary method to the Failure Mode and Effect Analysis method (Sujan and Felici, 2012). All these studies have applied the FRAM qualitatively, which is the original way of its application (Hollnagel, 2012). ...
... In the data collection-I stage, data were gathered to describe the functions and to quantify the variability. The initial data to describe the functions were obtained from a previous study conducted by Kaya, Ovali and Ozturk (2019). In the previous study, researchers conducted several meetings, constituting over 41 man-hours, to identify the drug administration process in the same NICU setting. ...
... FRAM models can be highly complex due to the interactions of several functions; thus, generating scenarios by visually using the FRAM models can be challenging (Patriarca, Bergström and Di Gravio, 2017;Hulme et al., 2019;Kaya, Ovali and Ozturk, 2019). The semi-quantitative application allows its users to build FRAM models by focusing on the couplings having high variability. ...
Article
In complex systems, as in health care, traditional safety management methods have limited capability to understand the system as a whole. The Functional Resonance Analysis Method (FRAM) has been introduced to overcome this challenge. This study applied a semi-quantitative approach to the FRAM on the basis of Monte Carlo simulation to gain an in-depth understanding of the drug administration process and, in turn, to manage performance variability and to support safety management. The contributions of this paper are twofold. Firstly, this study revealed that the semi-quantitative approach to the FRAM facilitates a clear understanding of the critical interactions in the FRAM model. Secondly, the use of the simulation generated a large number of different real-life scenarios to be examined, which is likely to contribute to situational awareness.
... Over the years, identification of human or system failures has resulted in adjustments in standard procedures. However, if existing processes are not taken into account, this could result in complex and unworkable procedures [20][21][22]. Protocols describe how care processes should be executed and often such processes are seen as linear. In practice, these processes are subjected to day to day variability of providing care. ...
... Different processes often occur simultaneously or are intertwined. This leads to more dynamic and complex care processes than imagined in a protocol [20][21][22][23][24]. Achieving absolute compliance with guidelines and protocols may be too ambitious, as daily practice requires adaptations to changing work conditions and constraints upon resources [20]. ...
... For that reason, the interest in the 'Safety-II' perspective is increasing, as it seeks to understand daily practice better and focusses on why things often go right [20,25]. Within this perspective, practice variation is not perceived as a 'negative' factor which must be restrained by standardisation, but as a logical consequence of the need to adapt in order to succeed despite changing circumstances [20,22,25]. Healthcare professionals need to adjust their work to varying conditions (i.e. ...
Article
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Background Healthcare professionals are sometimes forced to adjust their work to varying conditions leading to discrepancies between hospital protocols and daily practice. We will examine the discrepancies between protocols, ‘Work As Imagined’ (WAI), and daily practice ‘Work As Done’ (WAD) to determine whether these adjustments are deliberate or accidental. The discrepancies between WAI and WAD can be visualised using the Functional Resonance Analysis Method (FRAM). FRAM will be applied to three patient safety themes: risk screening of the frail older patients; the administration of high-risk medication; and performing medication reconciliation at discharge. Methods A stepped wedge design will be used to collect data over 16 months. The FRAM intervention consists of constructing WAI and WAD models by analysing hospital protocols and interviewing healthcare professionals, and a meeting with healthcare professionals in each ward to discuss the discrepancies between WAI and WAD. Safety indicators will be collected to monitor compliance rates. Additionally, the potential differences in resilience levels among nurses before and after the FRAM intervention will be measured using the Employee Resilience Scale (EmpRes) questionnaire. Lastly, we will monitor whether gaining insight into differences between WAI and WAD has led to behavioural and organisational change. Discussion This article will assess whether using FRAM to reveal possible discrepancies between hospital protocols (WAI) and daily practice (WAD) will improve compliance with safety indicators and employee resilience, and whether these insights will lead to behavioural and organisational change. Trial registration Netherlands Trial Register NL8778; https://www.trialregister.nl/trial/8778. Registered 16 July 2020. Retrospectively registered.
... In addition to the cases we reflect on in this paper, FRAM has been used in healthcare across different settings and for the analysis of different activities, including several studies set in emergency care (Sujan andFelici, 2012, MacKinnon et al., 2021) and intensive care (Clay-Williams et al., 2015), analysis of intravenous infusion and medication administration (Furniss et al., 2020;Kaya et al., 2019;Schutijser et al., 2019;Sujan, 2021), modelling of the transition of care of older adults discharged from hospital (O'Hara et al., 2020), and for exploring the recognition and management of sepsis (Raben et al., 2018, McNab et al., 2018. ...
... All the examples described in this paper investigated issues that had been studied previously but which had proved to be stubborn problems, e.g., the management of the deteriorating patient, blood sampling, and anticoagulation management. This is consistent with other studies using FRAM, which aimed to provide a different perspective on such problems, e.g., transfer of patients from intensive care to a hospital ward (Clay-Williams et al., 2015), handover in emergency care (Sujan and Felici, 2012), or drug administration in neonatal intensive care (Kaya et al., 2019). This aim links back to the underlying thinking in Resilience Engineering and Safety-II, which frames safety as the ability to succeed under varying conditions , and which thereby brings a different perspective. ...
Article
Resilience Engineering principles are becoming increasingly popular in healthcare to improve patient safety. FRAM is the best-known Resilience Engineering method with several examples of its application in healthcare available. However, the guidance on how to apply FRAM leaves gaps, and this can be a potential barrier to its adoption and potentially lead to misuse and disappointing results. The article provides a self-reflective analysis of FRAM use cases to provide further methodological guidance for successful application of FRAM to improve patient safety. Five FRAM use cases in a range of healthcare settings are described in a structured way including critical reflection by the original authors of those studies. Individual reflections are synthesised through group discussion to identify lessons for the operationalisation of FRAM in healthcare. Four themes are developed: (1) core characteristics of a FRAM study, (2) flexibility regarding the underlying epistemological paradigm, (3) diversity with respect to the development of interventions, and (4) model complexity. FRAM is a systems analysis method that offers considerable flexibility to accommodate different epistemological positions, ranging from realism to phenomenology. We refer to these as computational FRAM and reflexive FRAM, respectively. Practitioners need to be clear about their analysis aims and their analysis position. Further guidance is needed to support practitioners to tell a convincing and meaningful “system story” through the lens of FRAM.
... A recent special issue on Resilient Health Care in the journal Safety Science (Hollnagel et al., 2019) included several papers that demonstrated how FRAM might be used to describe and to understand performance variability in healthcare settings. For example, FRAM has already been applied to show some of the complexity of drug administration on a neonatal intensive care unit in Turkey, which gives examples of error occurrence and recovery (Kaya et al., 2019). FRAM has been applied to understand the variability in the double-checking procedures for injectable medicines in the Netherlands, which described barriers and facilitators as to why these checks are not performed correctly (Schutijser et al., 2019). ...
... This paper helps develop the picture of performance variability around intravenous infusion medication administration. Kaya et al. (2019) present a FRAM network with similar functions to those presented in this paper. However, they focus more on the preparation stage whereas our unit had many pre-made drugs so this was less variable. ...
Article
Full-text available
Systems contradictions present challenges that need to be effectively managed, e.g. due to conflicting rules and advice, goal conflicts, and mismatches between demand and capacity. We apply FRAM (Functional Resonance Analysis Method) to intravenous infusion practices in an intensive care unit (ICU) to explore how tensions and contradictions are managed by people. A multi-disciplinary team including individuals from nursing, medical, pharmacy, safety, IT and human factors backgrounds contributed to this analysis. A FRAM model investigation resulting in seven functional areas are described. A tabular analysis highlights significant areas of performance variability, e.g. administering medication before a prescription, prioritising drugs, different degrees of double checking and using sites showing early signs of infection for intravenous access. Our FRAM analysis has been non-normative: performance variability is not necessarily wanted or unwanted, it is merely necessary where system contradictions cannot be easily resolved and so adaptive capacity is required to cope.
... One justification is the capability of FRAM for describing and analyzing interdependencies among system elements or functions. Unlike most conventional safety management methods that do not consider human and organizational factors (Hollnagel, 2016;Woods & Cook, 2002), FRAM considers technological, human, and organizational functions together (Hollnagel, 2012b -technical systems' processes (De Carvalho, 2011;de Vries, 2017;Kaya et al., 2019). FRAM plays a vital role in understanding complex systems. ...
... It is more a social system than an engineered system. In healthcare, frontline personnel must adapt to work conditions where preconditions are not ideal and resources are limited (Hounsgaard, 2016 Kaya et al. (2019) and . ...
Article
Full-text available
This is a review paper of studies that have employed the functional resonance analysis method (FRAM). FRAM is a relatively new systemic method for modeling and analyzing complex socio-technical systems. This review aims to address the following research questions: (a) Why is FRAM used? (b) To what domains has FRAM been applied? (c) What are the appropriate data collection approaches in practice? (d) What are the deficiencies of FRAM? A review of 52 FRAM-related studies published between 2010 and 2020 revealed that FRAM-based models can be used as a basis for improving safety management, accident/incident investigation, hazard identification/risk management, and complexity management in complex socio-technical systems. The outcomes also showed that healthcare was the most common domain that employed FRAM (31% of the investigated studies). The results of exploring data collection methods indicated a mixed method (interview, focus group, observation) was employed in 52% of the analyzed studies, and the accident investigation report was the most popular approach in aviation-related studies. An investigation of the deficiencies of the FRAM showed that it should be upgraded by exploiting supplementary methods to enhance its analytical and computational capacity to help risk analysts and safety managers in complex socio-technical systems.
... In fact, FRAM was not fully applied in the referenced study, but was used to model the system. When applying FRAM, systems are modelled by actions without focusing on their hierarchical structure (Kaya et al., 2019c). STPA, on the other hand, was fully applicable to analyse risks and modelling the system seemed to require less effort. ...
... Despite the science behind FRAM -from its terminology to application -being criticised by Leveson (2020) and Cooper (2020), both methods have their own strengths and weaknesses (Adesina et al., 2017;Bjerga et al., 2016;Kaya et al., 2019c;Rejzek and Hilbes, 2017). STPA and FRAM have been built on different philosophies; one considers the glass to be half-empty and other regards the glass as half-full. ...
Article
In healthcare, most accidents occur as a result of inadequate interactions between system components rather than component failures. In such cases traditional risk analysis methods are of limited use for analysing system safety, so methods such as Systems Theoretic Process Analysis (STPA) and the Functional Resonance Analysis Method (FRAM) have been developed. This study uses STPA to assess risks in the sepsis treatment process, discusses the potential value STPA adds and compares the results of STPA with the results of another study that used FRAM. The findings indicate that STPA and FRAM have different strengths which reflect the different scientific approaches behind these two methods. FRAM facilitates an in-depth understanding of a system, while STPA allows for more comprehensive risk analysis by identifying more risks, scenarios and safety recommendations. Nevertheless, it is reasonable to say that not only does STPA provide more comprehensive risk analysis; its terminology and philosophy are also closer to the current safety management applications employed in complex systems.
... Sağlık sektörünün çeşitli alanlarında da FRAM kullanılmıştır. Örneğin, yeni doğan yoğun bakım ünitelerinde ilaç uygulama süreci, hemşire, doktor, diğer hastane personeli, yeni doğan, elektronik ilaç sipariş sistemi, eczaneler, protokol, yönergeler ve personel davranışlarının birlikte incelenmesine olanak sağlamıştır (Kaya, Ovalı ve Özturk, 2019). 2017 yılında sağlık sektöründe yapılan diğer bir çalışmada ise çocuklara uygulanan diş tedavisi oluşan sırasında diş çürüklerini önlemek için florür vernik uygulaması analizinde FRAM kullanılmıştır (Ross, Sherriff, Kidd, Gnich, Anderson, Deas ve Macpherson, 2018). ...
... Hollnagel, 2012 yılında model üzerinde yeniden çalışma yaparak geliştirmiştir. FRAM, fonksiyonel değişkenlikleri kullanarak sistemi anlamak için model olarak geliştirilmiş, sonrasında kaza incelemeleri ve risk analizlerinde kullanılmıştır(Kaya, Ovalı ve Özturk, 2019;Özay, Ateş, ve Uçan, 2020). etkin olabileceği sosyo-teknik sistem olarak adlandırılabilen karmaşık yapının bir arada incelenmesine fırsat verir. ...
... Sağlık sektörünün çeşitli alanlarında da FRAM kullanılmıştır. Örneğin, yeni doğan yoğun bakım ünitelerinde ilaç uygulama süreci, hemşire, doktor, diğer hastane personeli, yeni doğan, elektronik ilaç sipariş sistemi, eczaneler, protokol, yönergeler ve personel davranışlarının birlikte incelenmesine olanak sağlamıştır (Kaya, Ovalı ve Özturk, 2019). 2017 yılında sağlık sektöründe yapılan diğer bir çalışmada ise çocuklara uygulanan diş tedavisi oluşan sırasında diş çürüklerini önlemek için florür vernik uygulaması analizinde FRAM kullanılmıştır (Ross, Sherriff, Kidd, Gnich, Anderson, Deas ve Macpherson, 2018). ...
... Hollnagel, 2012 yılında model üzerinde yeniden çalışma yaparak geliştirmiştir. FRAM, fonksiyonel değişkenlikleri kullanarak sistemi anlamak için model olarak geliştirilmiş, sonrasında kaza incelemeleri ve risk analizlerinde kullanılmıştır(Kaya, Ovalı ve Özturk, 2019;Özay, Ateş, ve Uçan, 2020). etkin olabileceği sosyo-teknik sistem olarak adlandırılabilen karmaşık yapının bir arada incelenmesine fırsat verir. ...
... While traditional techniques focus on the reliability of each system component, FRAM focuses on system resilience (Hollnagel, 2012). FRAM has been used in various industries to investigate accidents, to assess risks, to measure performance variability, to understand system complexity and, thus, to enhance system resilience Adriaensen et al., 2019;Kaya, Ovali and Ozturk, 2019) This study applies FRAM to assess risks in a Turkish coffee-making process, and it discusses the applicability of FRAM in complex systems. ...
... Several studies have shown the potential value of FRAM to ensure safety in complex systems (De Carvalho, 2011;Cabrera Aguilera et al., 2016;Furniss, Curzon and Blandford, 2016;Tian et al., 2016;Kaya, Ovali and Ozturk, 2019). FRAM supports a better understanding of a system and provides a more in-depth analysis by revealing risks emerging from system interactions. ...
Chapter
Risk management has been applied in a wide range of industries to ensure safety by using risk management tools and techniques. Many of those techniques were developed long ago to analyze individual system components. In complex systems, however, accidents emerge from system interactions. Hence, traditional risk management tools and techniques have become inadequate to analyze risks in complex systems. The Functional Resonance Analysis Method (FRAM) was recently developed to address the limitations of traditional risk management methods. This study provides an example of the use of FRAM to demonstrate its use and to highlight its potential value in safety risk management.
... Furthermore, they are often designed to break up the system into parts and evaluate each one separately (Hollnagel, 2012) to linearize even the workers' behaviour (Rosa et al., 2015). On the other hand, the whole system cannot be comprehensively understood by simply knowing its components or parts (Kaya et al., 2019). ...
... Some contributions from the literature have been addressed to improve the visualization of functions. For instance, when modelling the drug administration process in neonatal intensive care units (NICUs), Kaya et al. (2019) began to explore the idea of extracting information from the integral FRAM to improve the visualization of a subset of functions. In the same way, Saldanha et al. (2020) also used this strategy when representing a set of functions from the integral model in secondary graphics. ...
Article
Maintenance of heating, ventilation, and air-conditioning (HVAC) systems has become one of the most relevant maintenance operations in public buildings. The intense interaction among human agents and equipment, aligned with information's distributed nature, exposes the maintenance workers to significant and complex risks during their routines. Prescribed procedures frequently differ from reality, which becomes essential the examination of the work-as-done. The functional resonance analysis method (FRAM) offers a promising perspective on analysing work-as-done in daily activities. However, the FRAM brings a limitation due to its complexity of representation. This study presents a layered FRAM as an alternate way of analysing the work-as-done in the maintenance of HVAC systems. This approach consists of cutting the couplings among functions in those presenting variability to clarify how the functions affect each other. The results show that the layered FRAM offers a better view of functions, decreasing the complexity and the analyst's cognitive workload. This contribution is a user-friendly and straightforward technique to facilitate the model analysis and explore a new perspective to popularize and spread the FRAM to treat complex issues.
... In addition, the software tool FRAM Model Interpreter (FMI) has recently become available, which is a stepwise automatic interpretation of the syntactical and logical correctness of an FRAM model to formally check and adjust its consistency and completeness. With regard to validation, subjective evaluation through interviews with experts, workshops, and discussions was mainly used to improve the face validity of developed FRAM models, as pointed out by Bridges et al. (2018), Kaya et al. (2019), and Ross et al. (2018). The reason may be associated with an experts' deep knowledge of the work system and daily operations, which can help to enrich developed FRAM models and to provide more reliable models (Salehi et al. 2021). ...
... Thus, construct validity can be generally assumed for an FRAM model as long as the method and its principles were correctly and comprehensively used, once again emphasising the strong dependency between an FRAM model's output quality and the experience and training of the user and modeller as mentioned above. Content validity can mainly be proved by face validity using subjective evaluation through interviews, workshops, and discussions with experts who have a deep knowledge of normal work systems and daily operations, as already applied by Bridges et al. (2018), Kaya et al. (2019), and Ross et al. (2018). In addition, a theory-based validation could be used to further increase the content validity by comparing the FRAM model's outputs with both other models or indicators in literature or incident and accident reports (including contributory factors and reasons) regarding the same application context. ...
Article
Full-text available
Over the past two decades, systemic-based risk assessment methods have garnered more attention, and their use and popularity are growing. In particular, the functional resonance analysis method (FRAM) is one of the most widely used systemic methods for risk assessment and accident analysis. FRAM has been progressively evolved since its starting point and is considered to be the most recent and promising step in understanding socio-technical systems. However, there is currently a lack of any formal testing of the reliability and validity of FRAM, something which applies to Human Factors and Ergonomics research as a whole, where validation is both a particularly challenging issue and an ongoing concern. Therefore, this paper aims to define a more formal approach to achieving and demonstrating the reliability and validity of an FRAM model, as well as to apply this formal approach partly to an existing FRAM model so as to prove its validity. At the same time, it hopes to evaluate the general applicability of this approach to potentially improve the performance and value of the FRAM method. Thus, a formal approach was derived by transferring both the general understanding and definitions of reliability and validity as well as concrete methods and techniques to the concept of FRAM. Consequently, predictive validity, which is the highest maxim of validation, was assessed for a specific FRAM model in a driving simulator study using the signal detection theory. The results showed that the predictive validity of the FRAM model is limited and a generalisation with changing system conditions is impossible without some adaptations of the model. The applicability of the approach is diminished because of several methodological limitations. Therefore, the reliability and validity framework can be utilised to calibrate rather than validate an FRAM model.
... It is a well-designed method to analyze system behaviour based on performance variability (Kim and Yoon, 2021). It relies on systems theory and aims to identify the interactions between system components in order to analyze the ways safe and unsafe interactions might arise (Kaya et al., 2019). The FRAM emphasizes that there is a relationship between functional variability and system performance. ...
Article
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Although the Functional Resonance Analysis Method (FRAM) is a well-established approach to visualizing complex systems' operations in terms of functions, further improvements are required to examine systems' performance through functionality. This study aims to develop an approach to couple the FRAM to reinforcement learning (RL) to explore complex operations. The developed approach is called the functional RL approach and constitutes a novel way of using a FRAM model to explore functionality using an artificial intelligent (AI) agent who responds to reward values assigned to functional parameters. To exemplify the approach, an agent is employed to perform the role of a patient and explore a functional environment generated by the FRAM. Reward values are considered to motivate the agent in order to explore the environment to achieve its objective. The ability of the developed approach is examined using different scenarios implemented in healthcare operations. The results of using the functional RL approach indicate that the approach is able to specify the functional route taken by the agent and to examine the performance of the system based on accumulated rewards. The outcomes of this study demonstrate that the developed functional RL approach provides a novel means to explore operational environments to identify the routes that have potential to affect the system performance. This method can be used as a powerful way to assess how a system performs under different management structures.
... In this approach, incidents are as a result of a causal chain of events. In the safety management literature, Safety-I approach has been claimed to be limited to manage safety in complex systems, as in healthcare (Sujan et al. 2019;Kaya, Ovali, and Ozturk 2019). To address such limitation, Hollnagel (2014) focusing on "how things go right" in addition to "how things go wrong", and called this approach as Safety-II approach. ...
Article
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In England, hospitals routinely conduct a formal risk assessment practice to ensure the safety of patients and staff. However, although specific criticisms have been made on the practice, few investigated the formal risk assessment practice in the literature. This study investigates the risk assessment policies and procedures of one hundred hospitals in the English National Health Service (NHS) through content analysis. Findings revealed that hospitals provided varied descriptions of the terms risk and risk assessment. The concept of risk was often defined to be an undesired event, and risk assessment was often explained with the involvement of risk control step. Despite the variety in the descriptions of the risk terms, all hospitals recommended following similar steps to undertake risk assessments. Risk matrices and therefore risk scoring-are at the heart of the formal practice, which increases the possibility of wrong risk prioritisation. This study provides several recommendations for the improvement of current guidelines by considering both Safety-I and Safety-II approaches. ARTICLE HISTORY
... FTA and FMEA) by revealing the complex interactions of the socio-technical systems [18,19]. It was claimed that methods like FMEA, FTA and ETA analyses individual system components with a primary focus on human errors [20][21][22]. FRAM and CAST, however, provide more detail and accuracy in modelling and analysing complex processes with the consideration of human, technology and organizational factors [23][24][25]. ...
Article
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Air transport is considered to be the safest means of transport. However, if an accident occurs, it often ends in catastrophe. Thus, significant efforts have been paid to sustain successful operations in aviation. Several studies have been carried out to understand the underlying reasons for accidents. This study used Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA) and Causal Analysis based on Systems Theory (CAST) methods to analyse Tenerife aircraft accident and to compare the findings of different methods. The findings showed that while all three methods provided some overlapping findings, the CAST method led to the identification of all causes that were identified by other methods. Considering the nature of the causal factors, FMEA provided more causal factors that are related to organisation and technology than FTA. This study indicates that CAST has a significant value to identify all causes that can be identified by the use of traditional methods.
... Similarly, this diversity was reflected in the manner in which variability is indexed within FRAM. Several researchers used the "simple solution" (e.g., [7,13,19,33,[51][52][53][54][55]), while others use more detailed indices of variability, such as the 11 CPCs (e.g., [23,[56][57][58][59][60]). ...
Article
Full-text available
The functional resonance analysis method (FRAM) is a system-based method to understand highly complex sociotechnical systems. Besides learning from safety occurrences or undesirable states, FRAM can be used to understand how things go well in a system, by identifying gaps between "work as imagined"(WAI) and "work as done"(WAD). FRAM is increasingly used in many domains and can enhance our understanding of a complex system and proposes strategies to refine the work design. This systematic review identified 108 FRAM research papers from 2006-2019. Most of these papers were conducted by European researchers and employed qualitative methods such as document analysis, interviews, and focus groups with subject matter experts (SMEs) and observations to develop WAI and WAD. Despite being used in healthcare, construction, and maritime sectors among others, aviation was the most commonly explored domain in FRAM studies. The 26 FRAM studies in aviation explored many aspects of the aviation industry, including Air Traffic Control (ATC) systems, cockpit operation, ground handling, maintenance, and a range of past safety incidents, like runway incursions. This paper also characterises the FRAM studies focused on aviation in terms of the common methods and steps used to build FRAM and the available software tools to build FRAM nets. Current FRAM illustrates its advantages in capturing the dynamic and nonlinear nature of complex systems and facilitates our understanding and continual improvement of complex systems. However, there are some critical issues in FRAM use and interpretation, such as the consistency of methods and complexity and reliability of data collection methods, which should be considered by researchers and FRAM users in industry.
... This is not a surprising result since FRAM was developed in the aeronautical field. Other emerging sectors are healthcare (13,99%) and industrial operations (12,44%) as demonstrated by several publications [14][15][16]. Furthermore, some authors pointed out that FRAM does not assess the human behavior and the human performance to analyze the human error [17,18]. ...
Chapter
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Complex industrial plants are characterized by digitalization and innovation. In this context it is strategic to ensure the systematic design, implementation, and continuous improvement of all processes (operations management). One of the most obvious ways to improve operations performance is to reduce the risk of accidents and human errors. In this pilot study the Functional Resonance Analysis Method (FRAM) is proposed to analyze the complexity of safety in industrial plants. This research integrates FRAM with Analytic Hierarchy Process (AHP), a multi criteria technique, to overcome the limits of the FRAM. The result is a proposal of an alternative approach to risk assessment based on principles of resilience engineering. A real case study in a petrochemical company is analyzed.
... The FRAM tries to find causes of unfavourable events because it takes for granted that knowledge of reasons is necessary to prevent things from going wrong in the future. The purpose of the FRAM is to analyze how something has been done, how something is done, or how something could be done to represent it reliably and systematically, using a welldefined format (Hollnagel, Hounsgaard, Colligan, 2014;Kaya, Ovali, Ozturk, 2019). ...
Article
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COVID-19 was identified in Wuhan, China, in December of 2019. Afterwards, it spreads all over the World and causes many difficulties in health management in many countries. Many risk analysis methods have been applied to control and minimize contamination risks.This study aims to understand the COVID-19 management process in health care facilities using the Functional Resonance Analysis Method (FRAM) to facilitate the safety analysis, taking account of the system response to different operating conditions and various risks.The hospital process of COVID-19 patient is examined in three public and one private hospital in Istanbul/Turkey. The information is taken with teleconference meetings over 34 hours with 16 doctors and 12 nurses during a month. The model is applied by "FRAM Model Visualizer" to determine potential couplings between the functions and their potential impact on the hospital process. Fourteen functions are identified to analyze the hospital process of a patient, and multiple scenarios are developed with consideration for the progress conditions of the system. It has been concluded that FRAM does not remain at the conceptual level with application studies, but it is very suitable for many complex systems such as case analyzes such as pandemic and disaster scenarios.
... The results of the customized version of the FRAM showed that successful and unsuccessful transitions are rooted in a same set of functions. Performance variability in the output of the functions was the main reason for the successful and unsuccessful outcomes, as the results of other studies have emphasized (Kaya et al., 2019;Patriarca et al., 2018). ...
Article
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The main purpose of this study was to model and analyze hospital to home transition processes of frail older adults in order to identify the challenges within this process. A multi-phase, multi-sited and mixed methods design was utilized, in which, Phase 1 included collecting semi-structured interviews and focus group data, and Phase 2 consisted of six patient/caregiver dyad prospective case studies. This study was conducted in three hospitals in three cities in a single province in Canada. The Functional Resonance Analysis Method (FRAM) was employed to model daily operations of the transition process. The perspectives of both healthcare providers and patients/caregivers were used to build the FRAM model. The transition model was then tested using a customized version of the FRAM. The six patient/caregiver cases were used in the process of testing the FRAM model. The results of building the FRAM model showed that five categories of functions contributed to the transition model, including admission, assessment, synthesis, decision-making, and readmission. The outcomes of using the customized version of the FRAM revealed challenges affecting the transition process including waitlists for geriatric units, team-based care, lack of a discharge planner, financial concerns, and follow-up plans. The findings of this study could assist managers and other decision makers to improve the transition processes of frail older adults by addressing these challenges. The FRAM method employed in this study can be applied widely to identify work practices that are more or less successful, so that procedures and practices can be adapted to nudge healthcare processes towards paths that will yield better outcomes.
... The FRAM has been widely applied for different purposes in several domains like aviation (Patriarca, Di Gravio, Cioponea, & Licu, 2019), construction (del Pardo-Ferreira, 2020; Rosa, Haddad, & de Carvalho, 2015), flood-risk (Anvarifar, Voorendt, Zevenbergen, & Thissen, 2017;Steen & Ferreira, 2020), healthcare (Jatobá et al., 2018;Kaya, Ovali, & Ozturk, 2019;Raben, Bogh, Viskum, Mikkelsen, & Hollnagel, 2017), maritime (Patriarca & Bergström, 2017;Vries & Bligård, 2019;Wahl, Kongsvik, & Antonsen, 2020), manufacturing (Zheng, Tian, & Zhao, 2016), oil and gas (França et al., 2019(França et al., , 2020, information technology (de Carvalho, Gomes, Jatobá, da Silva, & de Carvalho, 2020;Souza et al., 2021). Other FRAM applications can be found in extensive mappings, such as in Patriarca et al. (2020) and Salehi, Veitch, and Smith (2020). ...
Article
Work in socio-technical systems (STS) exhibits dynamic and complex behaviors, becoming difficult to model, evaluate and predict. This study develops an integrated soft computing approach for nonlinear risk assessment in STS: the functional resonance analysis method (FRAM) has been integrated with fuzzy sets. While FRAM is helpful to model performance variability in qualitative terms, the assessments are usually subjected to a high degree of uncertainty. This novel approach is meant to overcome the subjectivity associated with the qualitative analyses performed by experts’ judgments required by FRAM. For demonstration purposes, the approach has been applied to model a waste recycling process for construction materials. The results show how the approach allows assessing and ranking critical activities in STS operations.
... It acknowledges the complexity of systems and the need to link social and technical aspects [45]. The concept has been operationalized (including for health services, e.g., in primary care management [46] and drug administration [47]. Although this application to health infrastructures is helpful, it has often been done with a focus on the system without considering it in a wider context. ...
Article
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The current understanding of critical health infrastructure resilience is still dominated by a technical perspective. Reality however is different, as past events including the COVID-19 pandemic have revealed: emergency situations are only rarely exclusively technical in nature. Instead they are a product of prior circumstances, often linked to natural hazards, technical mishaps, and insufficient social and organizational preparedness structures. However, experiences and lessons learned from past events are still largely overlooked and have not sufficiently found their way into conceptual understandings of critical health infrastructure resilience. This paper addresses this gap by challenging the one-sided and technically oriented understanding of resilience in the context of critical health infrastructure. Based on a systematic literature review, it assesses real-world cases of water supply failures in healthcare facilities, a serious threat largely overlooked in research and policy. The results underscore the need for targeted organizational strategies to deal with cascading impacts. The overall findings show that addressing technical aspects alone is not sufficient to increase the overall resilience of healthcare facilities. Broadening the dominant resilience understanding is hence an important foundation for healthcare infrastructures to improve risk management and emergency preparedness strategies to increase their resilience towards future disruptions.
... FRAM is increasingly being used as a prospective analysis method for understanding performance variability in everyday work or work-as-done (WAD). FRAM has seen widespread uptake especially within healthcare, where the complexity of everyday clinical work lends itself particularly well to the study with FRAM (Kaya et al., 2019, Pickup et al., 2017, Raben et al., 2018, Schutijser et al., 2019. ...
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Muddling through can be understood in terms of the trade-offs healthcare workers make in response to tensions and contradictions in their everyday work. This gives rise to the performance variability observed in work-as-done. This chapter describes the application of the Functional Resonance Analysis Method (FRAM) to study performance variability, and thus how trade-offs are made, in the intensive care unit. The case study used is the management of intravenous infusions. Using FRAM, several instances of performance variability were identified and analysed for their impact on other functions. The FRAM analysis can be a useful tool for reflection for those involved in delivering and managing the work, and it can provide guidance for the design of tools and technologies.
... It unveils interactions between the actions, considers aggregated variability effects and, in turn, supports the management of performance variability [19]. FRAM has been used in diverse industries [21,22], including aviation [23], maritime [24], healthcare [25,26], construction [27] and oil and gas [28,29]. All these studies highlighted the potential value of FRAM in modelling complex systems, analysing risks and managing safety. ...
Article
Safety management in tram systems is considered to be effective, but improvement is still necessary. This study applies the Functional Resonance Analysis Method (FRAM) by integrating Monte Carlo simulations and a criticality matrix to explore how the system-based perspective would enrich the quantified risk-oriented analysis in a tram operating system. The study models the tram operating system, estimates performance variability, identifies critical couplings and assesses risks presented by those couplings. The findings showed that a daily tram operating system runs with a degree of variability, in which tram driver- and pedestrian-related actions are the most variable ones. Performance variability in the system was most often due to the need for responding to unforeseen change. Such variability was usually essential to sustaining the tram system's successful operation. However, the findings also revealed that the tram operating system was exposed to several risks due to uncontrolled variability. The findings indicate that the system-based approach reveals all system interactions, considers aggregated variability and leads to comprehensive risk analysis of the tram operating system under various real-life working conditions.
... We used the method to model and analyze the variability in the relations between essential functions of the SUS in the scenarios explored in this study. FRAM models have been extensively used in representing the effects of variability in the functions of complex sociotechnical systems like healthcare [19][20][21][22]. ...
Article
By the time the present study was completed, Brazil had been the second epicenter of COVID-19. In addition, the actions taken to respond to the pandemic in Brazil were the subject of extensive debate, since the Federal Government diverged from most recommendations from health authorities and scientists. Since then, the resulting political and social turmoil showed conflicting strategies to tackle the pandemic in Brazil, with visible consequences in the numbers of casualties, but also with effects on the resilience of the overall health system. This article explores the actions taken in Brazil to cope with the pandemic from a systems analysis perspective. The structure of the domain was analyzed using work domain analysis, and the activated functions were analyzed using the Functional Resonance Analysis Method, identifying the potential variability resulting from the conflicting strategies carried out and the consequences to the capacity of the Brazilian health system to respond to the pandemic. Results of the study show that some government authorities introduced functions that overlapped the operation of the overall system as recommended by health authorities, causing the health system to operate under conflicting objectives, in which functions were created to restrict the outcomes of each other during the entire COVID-19 crisis.
... The method has been widely applied in many work fields (eg, aviation, railway and airway traffic management, and construction), but its implementation in healthcare research remains more limited. [36][37][38][39][40][41][42][43][44][45][46] Hence, this study aims to provide an overview of how ECS therapy is organised and to define suggestions for improvement using FRAM. It is the first step in developing a general cross-domain protocol to improve ECS therapy for patients with either DVT or CVI, matching daily practice, and in adherence to guidelines and scientific evidence. ...
Article
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Objectives: Elastic compression stocking (ECS) therapy is an important treatment for patients with deep venous thrombosis (DVT) and chronic venous insufficiency (CVI). This study aimed to provide insight into the structure and variability of the ECS therapy process, its effects on outcomes, and to elicit improvement themes from a multiple stakeholder perspective. Design: Thirty semi-structured interviews with professionals and patients were performed. The essential functions for the process of ECS therapy were extracted to create two work-as-done models using the Functional Resonance Analysis Method (FRAM). These findings were used to guide discussion between stakeholders to identify improvement themes. Setting: Two regions in the Netherlands, region Limburg and region North-Holland, including an academic hospital and a general hospital and their catchment region. Participants: The interviewees were purposely recruited and included 25 healthcare professionals (ie, general practitioners, internists, dermatologists, nurses, doctor's assistants, occupational therapists, home care nurses and medical stocking suppliers) and 5 patients with DVT or CVI. Results: Two FRAM models were created (one for each region). The variability of the functions and their effect on outcomes, as well as interdependencies between functions, were identified. These were presented in stakeholder meetings to identify the structure of the process and designated variable and uniform parts of the process and its outcomes. Ultimately, six improvement themes were identified: dissemination of knowledge of the entire process; optimising and standardising initial compression therapy; optimising timing to contact the medical stocking supplier (when oedema has disappeared); improving the implementation of assistive devices; harmonising follow-up duration for patients with CVI; personalising follow-up and treatment duration in patients with DVT. Conclusions: This study provided a detailed understanding of how ECS therapy is delivered in daily practice by describing major functions and variability in performances and elicited six improvement themes from a multistakeholder perspective.
... FRAM is a systematic approach for studying complex socio-technical systems (Hollnagel, 2012), which has been used in a range of safety-critical industries (Patriarca et al., 2020). In healthcare, FRAM has been applied, for example, to investigate blood sampling (Pickup et al., 2017), intravenous infusion and medication administration (Furniss et al., 2020;Kaya et al., 2019;Schutijser et al., 2019), handover in emergency care (Sujan and Felici, 2012) and the application of fluoride varnish in dental settings (Ross et al., 2018). FRAM investigates process variability to better understand and improve everyday work. ...
Article
Background Failure to rescue (FTR) denotes mortality from post-operative complications after surgery with curative intent. High-volume, low-mortality units have similar complication rates to others, but have lower FTR rates. Effective response to the deteriorating post-operative patient is therefore critical to reducing surgical mortality. Resilience Engineering might afford a useful perspective for studying how the management of deterioration usually succeeds and how resilience can be strengthened. Methods We studied the response to the deteriorating patient following emergency abdominal surgery in a large surgical emergency unit, using the Functional Resonance Analysis Method (FRAM). FRAM focuses on the conflicts and trade-offs inherent in the process of response, and how staff adapt to them, rather than on identifying and eliminating error. 31 semi-structured interviews and two workshops were used to construct a model of the response system from which conclusions could be drawn about possible ways to strengthen system resilience. Results The model identified 23 functions, grouped into five clusters, and their respective variability. The FRAM analysis highlighted trade-offs and conflicts which affected decisions over timing, as well as strategies used by staff to cope with these underlying tensions. Suggestions for improving system resilience centred on improving team communication, organisational learning and relationships, rather than identifying and fixing specific system faults. Conclusion FRAM can be used for analysing surgical work systems in order to identify recommendations focused on strengthening organisational resilience. Its potential value should be explored by empirical evaluation of its use in systems improvement.
... Several researchers have identified advantages related to FRAM. For example, Belmonte et al. (2011), Patriarca & Bergstrom (2017) and Kaya et al. (2019) described FRAM as offering a dynamic representation of systems, allowing the identification of novel and complex incident and accident scenarios when used prospectively. ...
Article
Many methods have been developed to understand and improve system safety. Previous research has indicated that a ‘research-practice gap’ exists in use of methods, where systemic methods are not adopted in practice. This study extends this research, by using interviews and focus groups with 29 safety experts to investigate their choice and use of different error and accident analysis methods. This study supports previous conclusions on the research-practice gap in different analysis approaches taken by researchers and practitioners, and provides new insights in understanding experts’ familiarity and willingness to consider safety II approaches to safety analysis, including their interpretations of the principles of emergence and resonance. The key findings were that participants, both with and without prior experience of using FRAM (Functional Resonance Analysis Method, Hollnagel, 2012), used various strategies to identify how performance variabilities may resonate through the system to produce unwanted outcomes. They recognised the value of the safety II perspective in providing detailed recommendations for improving system safety, although some did not understand the underlying concepts, or described FRAM as time consuming and complex to use. There is a need to enhance the practical applicability of emerging methods, which provide further avenues of research.
... In healthcare, the FRAM has been for managing risk related to iatrogenic disease, very relevant, even in economic terms, for facilities [10]. The effects of performance variability have been explored to understand the system's success or failure in drug administration process in neonatal intensive care units [11]. From a management standpoint, the method helped to identify lacks of fit between work-asimagined and work-as-done [12]. ...
Article
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Abstract This article aims at systematically reviewing the entire collection of papers published on the development and application of the functional resonance analysis method (FRAM) in the last decade. The Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) methodology has been utilized as a formal systematic literature review standard for data gathering. The analysis encompassed 47 documents devoted to this subject matter, systematically retrieved from the online database Scopus. The findings revealed the necessity for the development of systemic safety assessment approaches to explain performance variability of complex and dynamic socio-technical systems (risk assessment or accident investigation). Indeed, it is crucial to rigorously assess the performance variability throughout safety appraisal since unexpected performance variability can combine in undesirable manners and consequently denotes a threat for safety and losses of human life. However, the FRAM process has some pros and cons as discussed in this review. Consequently, other assessment methods exist to complement the FRAM process. Keywords: Functional Resonance Analysis Method (FRAM), Resilience Engineering (RE), Decision-Making, Strategic Asset Management (SAM), Risk Management (RM), Industry 4.0, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
Thesis
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This systematic review will assess the application of FRAM in healthcare settings to develop a rich understanding of the application of FRAM in healthcare as a complementary method to safety management. Firstly, understanding how FRAM was implemented within healthcare organisations and secondly understanding how healthcare organisations have perceived the value-add of FRAM in terms of safety management. The results are expected to provide healthcare organisations with guidance on applying the FRAM and demonstrate the value it potentially adds to safety management.
Article
The dynamically changing working environment and complex task requirements in modern industries emphasize the necessity of multiteam with different functions to work collaboratively. The multiteam coordination performance dominates the task process and the achievement of the superordinate goal, which will inevitably influence task safety. Although previous research has broadly identified the importance of inter-team cooperation to task performance, the analysis of the relationship between multiteam coordination structure, process, and system safety has not been fully addressed. Moreover, there is still a lack of an effective method to quantitatively analyze the functional interdependencies, interaction processes, and potential safety risks among teams in multiteam coordination tasks. Based on the construction industry background, this study combines FRAM and multiplex network to describe the multiteam coordination structure and task process variability. The relationship between multiteam coordination performance and construction safety risk is qualitatively and quantitatively analyzed. Case studies are adopted to verify the feasibility of the proposed method. The findings demonstrate the method's advantages in revealing the details of the influence of multiteam coordination performance on complex task safety, which is beneficial for developing targeted countermeasures to control safety risks from the perspective of the multiteam system.
Article
The improvement of safety management in the construction sector, especially in activities for concrete structures, continues to be necessary. This paper aims at increasing understanding of everyday construction activities for building concrete structures in order to improve resilient safety management. The Functional Resonance Analysis Method (FRAM) has been applied to these activities for this purpose. Analysis of available documentation, on-site interviews and observations have been conducted to collect data. The FRAM analysis revealed that the construction phase health and safety plan is rarely used, that organizational pressure affects safety and that leading indicators to monitor normal work are not used. In addition, delivery of concrete on site and crane operations as key factors due to their influence on variability. This study outlined the potential of the FRAM model as the basis of in-depth and systematic analysis of daily performance, highlighting issues that, until now, had been undervalued.
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Introduction Modern safety approaches in healthcare differentiate between daily practice (work-as-done) and the written rules and guidelines (work-as-imagined) as a means to further develop patient safety. Research in this area has shown case study examples, but to date lacks hooking points as to how results can be embedded within the studied context. This study uses Functional Analysis Resonance Method (FRAM) for aligning work-as-imagined with the work-as-done. The aim of this study is to show how FRAM can effectively be applied to identify the gap between work prescriptions and practice, while subsequently showing how such findings can be transferred back to, and embedded in, the daily ward care process of nurses. Methods This study was part of an action research performed among ward nurses on a 38 bed neurological and neurosurgical ward within a tertiary referral centre. Data was collected through document analysis, in-field observations, interviews and group discussions. FRAM was used as an analysis tool to model the prescribed working methods, actual practice and the gap between those two in the use of physical restraints on the ward. Results This study was conducted in four parts. In the exploration phase, work-as-imagined and work-as-done were mapped. Next, a gap between the concerns named in the protocol and the actual employed methods of dealing with physical restraint on the ward was identified. Subsequently, alignment efforts led to the co-construction of a new working method with the ward nurses, which was later embedded in quality efforts by a restraint working group on the ward. Conclusion The use of FRAM proved to be very effective in comparing work-as-done with work-as-imagined, contributing to a better understanding, evaluation and support of everyday performance in a ward care setting.
Article
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In healthcare, patient safety has received substantial attention and, in turn, a number of approaches to managing safety have been adopted from other high‐risk industries. One of these has been risk assessment, predominantly through the use of risk matrices. However, while other industries have criticized the design and use of these risk matrices, the applicability of such criticism has not been investigated formally in healthcare. This study examines risk matrices as used in acute hospitals in England and the guidance provided for their use. It investigates the applicability of criticisms of risk matrices from outside healthcare through a document analysis of the risk assessment policies, procedures, and strategies used in English hospitals. The findings reveal that there is a large variety of risk matrices used, where the design of some might increase the chance of risk misprioritization. Additionally, findings show that hospitals may provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms of risk matrices. Consequently, this is likely to lead to variation in the quality of risk assessment and in the subsequent deployment of resources to manage the assessed risk. Finally, the article outlines ways in which hospitals could use risk matrices more effectively.
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Background Ensuring effective identification and management of sepsis is a healthcare priority in many countries. Recommendations for sepsis management in primary care have been produced, but in complex healthcare systems, an in-depth understanding of current system interactions and functioning is often essential before improvement interventions can be successfully designed and implemented. A structured participatory design approach to model a primary care system was employed to hypothesise gaps between work as intended and work delivered to inform improvement and implementation priorities for sepsis management. Methods In a Scottish regional health authority, multiple stakeholders were interviewed and the records of patients admitted from primary care to hospital with possible sepsis analysed. This identified the key work functions required to manage these patients successfully, the influence of system conditions (such as resource availability) and the resulting variability of function output. This information was used to model the system using the Functional Resonance Analysis Method (FRAM). The multiple stakeholder interviews also explored perspectives on system improvement needs which were subsequently themed. The FRAM model directed an expert group to reconcile improvement suggestions with current work systems and design an intervention to improve clinical management of sepsis. Results Fourteen key system functions were identified, and a FRAM model was created. Variability was found in the output of all functions. The overall system purpose and improvement priorities were agreed. Improvement interventions were reconciled with the FRAM model of current work to understand how best to implement change, and a multi-component improvement intervention was designed. Conclusions Traditional improvement approaches often focus on individual performance or a specific care process, rather than seeking to understand and improve overall performance in a complex system. The construction of the FRAM model facilitated an understanding of the complexity of interactions within the current system, how system conditions influence everyday sepsis management and how proposed interventions would work within the context of the current system. This directed the design of a multi-component improvement intervention that organisations could locally adapt and implement with the aim of improving overall system functioning and performance to improve sepsis management. Electronic supplementary material The online version of this article (10.1186/s12916-018-1164-x) contains supplementary material, which is available to authorized users.
Article
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Patients are continually being put at risk of harm, and health care organisations are struggling to learn effectively from past experiences in order to improve the safe delivery and management of care. Learning from incidents in health care is based on the traditional safety-engineering paradigm, where safety is defined by the absence of negative events (Safety-I). In this paper we make suggestions for the policy and practice of learning from incidents in health care by offering a critique based on a Safety-II perspective. In Safety-II thinking safety is defined as an ability - to make dynamic trade-offs and to adjust performance in order to meet changing demands and to deal with disturbances and surprises. The paper argues that health care organisations might improve their ability to learn from past experience by studying not only what goes wrong (i.e. incidents), but also by considering what goes right, i.e. by learning from everyday clinical work.
Article
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Modern trends of socio-technical systems analysis suggest the development of an integrated view on technological, human and organizational system components. The Air Traffic Management (ATM) system can be taken as an example of one of the most critical socio-technical system, deserving particular attention in managing operational risks and safety. In the ATM system environment, the traditional techniques of risk and safety assessment may become ineffective as they miss in identifying the interactions and couplings between the various functional aspects of the system itself: going over the technical analysis, it is necessary to consider the influences between human factors and organizational structure both in everyday work and in abnormal situations. One of the newly introduced methods for understanding these relations is the Functional Resonance Analysis Method (FRAM) which aims to define the couplings among functions in a dynamic way. This paper evolves the traditional FRAM, proposing an innovative semi-quantitative framework based on Monte Carlo simulation. Highlighting critical functions and critical links between functions, this contribution aims to facilitate the safety analysis, taking account of the system response to different operating conditions and different risk state. The paper presents a walk-through section with a general application to an ATM process.
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Abstract Healthcare organisations are often encouraged to learn from other industries in order to develop proactive and rigorous safety management practices. In the UK safety–critical industries safety cases have been used to provide justification that systems are acceptably safe. There has been growing interest in healthcare in the application of safety cases for medical devices and health information technology. However, the introduction of safety cases into general safety management and regulatory practices in healthcare is largely unexplored and unsupported. Should healthcare as an industry be encouraged to adopt safety cases more widely? This paper reviews safety case practices in six UK industries and identifies drivers and developments in the adoption of safety cases. The paper argues that safety cases might best be used in healthcare to provide an exposition of risk rather than as a regulatory tool to demonstrate acceptable levels of safety. Safety cases might support healthcare organisations in establishing proactive safety management practices. However, there has been criticism that safety cases practices have, at times, contributed to poor safety management and standards by prompting a “tick-box” and compliance-driven approach. These criticisms represent challenges for the adoption of safety cases in healthcare, where the level of maturity of safety management systems is arguably still lower than in traditional safety–critical industries. Healthcare stakeholders require access to education and guidance that takes into account the specifics of healthcare as an industry. Further research is required to provide evidence about the effectiveness of safety cases and the costs involved with the approach.
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Objective To identify, summarise and synthesise available literature on the effectiveness of implementation strategies for optimising implementation of complex interventions in primary care. Design Systematic review of reviews. Data sources MEDLINE, EMBASE, CINAHL, Cochrane Library and PsychINFO were searched, from first publication until December 2013; the bibliographies of relevant articles were screened for additional reports. Eligibility criteria for selecting studies Eligible reviews had to (1) examine effectiveness of single or multifaceted implementation strategies, (2) measure health professional practice or process outcomes and (3) include studies from predominantly primary care in developed countries. Two reviewers independently screened titles/abstracts and full-text articles of potentially eligible reviews for inclusion. Data synthesis Extracted data were synthesised using a narrative approach. Results 91 reviews were included. The most commonly evaluated strategies were those targeted at the level of individual professionals, rather than those targeting organisations or context. These strategies (eg, audit and feedback, educational meetings, educational outreach, reminders) on their own demonstrated a small to modest improvement (2–9%) in professional practice or behaviour with considerable variability in the observed effects. The effects of multifaceted strategies targeted at professionals were mixed and not necessarily more effective than single strategies alone. There was relatively little review evidence on implementation strategies at the levels of organisation and wider context. Evidence on cost-effectiveness was limited and data on costs of different strategies were scarce and/or of low quality. Conclusions There is a substantial literature on implementation strategies aimed at changing professional practices or behaviour. It remains unclear which implementation strategies are more likely to be effective than others and under what conditions. Future research should focus on identifying and assessing the effectiveness of strategies targeted at the wider context and organisational levels and examining the costs and cost-effectiveness of implementation strategies. PROSPERO registration number CRD42014009410.
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Introduction: Neonatal units are one of the hospital areas most exposed to the committing of treatment errors. A medication error (ME) is defined as the avoidable incident secondary to drug misuse that causes or may cause harm to the patient. The aim of this paper is to present the incidence of ME (including feeding) reported in our neonatal unit and its characteristics and possible causal factors. A list of the strategies implemented for prevention is presented. Material and methods: An analysis was performed on the ME declared in a neonatal unit. Results: A total of 511 MEs have been reported over a period of seven years in the neonatal unit. The incidence in the critical care unit was 32.2 per 1000 hospital days or 20 per 100 patients, of which 0.22 per 1000 days had serious repercussions. The ME reported were, 39.5% prescribing errors, 68.1% administration errors, 0.6% were adverse drug reactions. Around two-thirds (65.4%) were produced by drugs, with 17% being intercepted. The large majority (89.4%) had no impact on the patient, but 0.6% caused permanent damage or death. Nurses reported 65.4% of MEs. The most commonly implicated causal factor was distraction (59%). Simple corrective action (alerts), and intermediate (protocols, clinical sessions and courses) and complex actions (causal analysis, monograph) were performed. Conclusions: It is essential to determine the current state of ME, in order to establish preventive measures and, together with teamwork and good practices, promote a climate of safety.
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Background: Uptake of guidelines in healthcare can be variable. A focus on behaviour change and other strategies to improve compliance, however, has not increased implementation success. The contribution of other factors such as clinical setting and practitioner workflow to guideline utilisation has recently been recognised. In particular, differences between work-as-imagined by those who write procedures, and work-as-done-or actually enacted-in the clinical environment, can render a guideline difficult or impossible for clinicians to follow. The Functional Resonance Analysis Method (FRAM) can be used to model workflow in the clinical setting. The aim of this study was to investigate whether FRAM can be used to identify process elements in a draft guideline that are likely to impede implementation by conflicting with current ways of working. Methods: Draft guidelines in two intensive care units (ICU), one in Australia and one in Denmark, were modelled and analysed using FRAM. The FRAM was used to guide collaborative discussion with healthcare professionals involved in writing and implementing the guidelines and to ensure that the final instructions were compatible with other processes used in the workplace. Results: Processes that would have impeded implementation were discovered early, and the guidelines were modified to maintain compatibility with current work processes. Missing process elements were also identified, thereby, avoiding the confusion that would have ensued had the guideline been introduced as originally written. Conclusions: Using FRAM to reconcile differences between work-as-imagined and work-as-done when implementing a guideline can reduce the need for clinicians to adjust performance and create workarounds, which may be detrimental to both safety and quality, once the guideline is introduced.
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In discussions of the quality and safety problems of modern, Western healthcare, one of the most frequently heard criticisms has been that: "It is not standardised." This paper explores issues around standardisation that illustrate its surprising complexity, its potential advantages and disadvantages, and its political and sociological implications, in the hope that discourses around standardisation might become more fruitful.
Conference Paper
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Socio-technical systems rely on technological artefacts as well as human and professional practices in order to achieve organisational safety. From an organisational viewpoint of analysis, different safety barriers are often put in place in order to mitigate risks. The complexity of such systems poses challenges to safety assessment approaches that rely on simple, identifiable cause and effect links. Failure Mode and Effects Analysis (FMEA), for instance, is an established technique for the safety analysis of technical systems, but the assessment of the severity of consequences is difficult in socio-technical settings like healthcare. This paper argues that such limitations need to be addressed by combining diverse methodologies in order to assess vulnerabilities that might affect complex socio-technical settings. The paper describes the application of FMEA for the identification of vulnerabilities related to communication and handover within an emergency care pathway. It reviews and discusses the applicability of the Functional Resonance Analysis Method (FRAM) as a complementary approach. Finally, a discussion about different aspects of emerging technological risk argues that taking into account socio-technical hazards could be useful in order to overcome limitations of analytical approaches that tend to narrow the scope of analysis.
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Resilience engineering has consistently argued that safety is more than the absence of failures. Since the first book was published in 2006, several book chapters and papers have demonstrated the advantage in going behind 'human error' and beyond the failure concept, just as a number of serious accidents have accentuated the need for it. But there has not yet been a comprehensive method for doing so; the Functional Resonance Analysis Method (FRAM) fulfils that need. Whereas commonly used methods explain events by interpreting them in terms of an already existing model, the FRAM is used to model the functions that are needed for everyday performance to succeed. This model can then be used to explain specific events, by showing how functions can be coupled and how the variability of everyday performance sometimes may lead to unexpected and out-of-scale outcomes - either good or bad. The FRAM is based on four principles: equivalence of failures and successes, approximate adjustments, emergence, and functional resonance. As the FRAM is a method rather than a model, it makes no assumptions about how the system under investigation is structured or organised, nor about possible causes and cause-effect relations. Instead of looking for failures and malfunctions, the FRAM explains outcomes in terms of how functions become coupled and how everyday performance variability may resonate. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, to understand why things sometimes go wrong but also why they normally succeed.
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Health care is everywhere under tremendous pressure with regard to efficiency, safety, and economic viability - to say nothing of having to meet various political agendas - and has responded by eagerly adopting techniques that have been useful in other industries, such as quality management, lean production, and high reliability. This has on the whole been met with limited success because health care as a non-trivial and multifaceted system differs significantly from most traditional industries. In order to allow health care systems to perform as expected and required, it is necessary to have concepts and methods that are able to cope with this complexity. Resilience engineering provides that capacity because its focus is on a system’s overall ability to sustain required operations under both expected and unexpected conditions rather than on individual features or qualities. Resilience engineering’s unique approach emphasises the usefulness of performance variability, and that successes and failures have the same aetiology. This book contains contributions from acknowledged international experts in health care, organisational studies and patient safety, as well as resilience engineering. Whereas current safety approaches primarily aim to reduce or eliminate the number of things that go wrong, Resilient Health Care aims to increase and improve the number of things that go right. Just as the WHO argues that health is more than the absence of illness, so does Resilient Health Care argue that safety is more than the absence of risk and accidents. This can be achieved by making use of the concrete experiences of resilience engineering, both conceptually (ways of thinking) and practically (ways of acting).
Article
In this paper, we look into how some qualitative types of risk assessments can be used in conjunction with functional resonance analysis method (FRAM) to strengthen the resilience of systems. In FRAM, variation in relation to meeting specified functions is central, but risk and uncertainty considerations are not an integral part. We suggest to add to FRAM an assessment of the modelling choices and judgements using strength of knowledge considerations and a qualitative sensitivity analysis. In this way, an improved basis for assessing and strengthening system resilience with FRAM is established. We illustrate the idea with a simple example from the oil and gas industry.
Article
In healthcare, patient safety has received substantial attention and, in turn, a number of approaches to managing safety have been adopted from other high‐risk industries. One of these has been risk assessment, predominantly through the use of risk matrices. However, while other industries have criticized the design and use of these risk matrices, the applicability of such criticism has not been investigated formally in healthcare. This study examines risk matrices as used in acute hospitals in England and the guidance provided for their use. It investigates the applicability of criticisms of risk matrices from outside healthcare through a document analysis of the risk assessment policies, procedures, and strategies used in English hospitals. The findings reveal that there is a large variety of risk matrices used, where the design of some might increase the chance of risk misprioritization. Additionally, findings show that hospitals may provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms of risk matrices. Consequently, this is likely to lead to variation in the quality of risk assessment and in the subsequent deployment of resources to manage the assessed risk. Finally, the article outlines ways in which hospitals could use risk matrices more effectively.
Article
Functional Resonance Analysis Method (FRAM) is a relatively new method that has been proposed to explore how functional variability can escalate into unexpected, and often unwanted, events. It has been used for accident analyses and risk assessments in safety. We apply (and slightly modify) FRAM, to analyse how functions are configured to create systems that excel. Our case study focuses on how functions in human factors project work positively resonate to improve the delivery of value. From interviews with 22 practitioners we derived 29 functions and 6 subsystems showing how functions are coupled. Practitioners validated this model through respondent validation. Our case study evaluates the applicability and usability of FRAM. It shows how we adapted the method to make it more usable. It shows that FRAM can be used to examine positive and negative resonances in systems, to investigate how complex sociotechnical systems can flourish or stall.
Article
In the quest to continually improve the health care delivered to patients, it is important to understand "what went wrong," also known as Safety-I, when there are undesired outcomes, but it is also important to understand, and optimize "what went right," also known as Safety-II. The difference between Safety-I and Safety-II are philosophical as well as pragmatic. Improving health care delivery involves understanding that health care delivery is a complex adaptive system; components of that system impact, and are impacted by, the actions of other components of the system. Challenges to optimal care include regular, irregular and unexampled threats. This article addresses the dangers of brittleness and miscalibration, as well as the value of adaptive capacity and margin. These qualities can, respectively, detract from or contribute to the emergence of organizational resilience. Resilience is characterized by the ability to monitor, react, anticipate, and learn. Finally, this article celebrates the importance of humans, who make use of system capabilities and proactively mitigate the effects of system limitations to contribute to successful outcomes.
Article
Neonatal intensive care units (NICUs) are at high risk for medical errors due to the population, setting, and complexity of care. Furthermore, "near misses" often precede actual errors yet are mostly underreported and unrecognized as safety concerns. There is a growing recognition that a systems approach to quality and safety is foundational to improving care at the bedside and patient outcomes. The High Reliability Organization model is one such approach. It recognizes the challenges of a highly complex system and combines this recognition with a continual emphasis on reducing errors. Although the principles of the High Reliability Organization hold promise in accelerating quality and safety in the NICU, it is imperative that nurses at the bedside as well as nurse leaders actually learn how to operationalize high reliability principles and strategies that lead to better outcomes. This article outlines the necessary principles, culture, strategies, and behaviors that NICU nurses and nurse leaders must adopt to achieve high reliability in their units.
Article
Background: Nonlinear systems are found everywhere throughout the natural world. In these systems there exists no proportionality and no simple causality between the magnitude of responses and the strength of their stimuli: small changes can have striking and unanticipated effects, whereas great stimuli will not always lead to drastic changes in a system's behavior. Over the past few years, several groups have been interested in pursuing the relevance of nonlinear concepts to medicine. Although the initial focus was on cardiovascular and neurophysiologic dynamics, it soon became clear that the models they were using had more general applications in biology and medicine. In the field of traumatology, up to now the nonlinear dynamics of the innumerable reactions and feedback loops at many structural levels of the traumatized patient have not been analyzed. Method: For a better understanding of the concept of nonlinearity and its possible implications in the field of traumatology, three examples at the molecular, the cellular and the organic levels are presented. Results and Conclusions: Nonlinear behavior in principle is the rule in highly complex reactions. This nonlinearity exists also in traumatologically relevant systems. The theories of nonlinear dynamics offer new mathematical tools to quantify, model, predict or modulate the behavior of biological systems. It should be demonstrated that the traditional Newtonian linear approach and the new nonlinear approach are essential dual aspects of any system, both being essential for a better understanding of the pathophysiologic reactions in complex situations like trauma, shock, and sepsis.
Article
Medication errors are quite common in the neonatal intensive care unit Medical errors are a common occurrence in the neonatal intensive care unit (NICU). Although this high risk, fragile patient population is prone to a wide array of errors, medication errors are particularly common. Medication errors were the most common error type submitted to the Vermont Oxford Network’s NICQ.org voluntary reporting system.1 Kaushal and colleagues2 identified errors in 5.5% of NICU medication orders. Of note, potential adverse drug events (errors that had the potential to harm the patient but were intercepted, or potentially harmful errors that reached the patient but fortuitously did not result in injury) occurred eight times more often in NICU patients than in adults in hospital. Neonates, especially very low birthweight babies, are particularly vulnerable to adverse sequelae of medication errors as they have a limited ability to “buffer” such mistakes. Nursing practice has long recognised the need for extreme vigilance and a structured approach to preventing medication errors. The five “Rights” provide a framework for improving medication safety in nursing. These basic principles of standard operating procedure try to address all of the steps in the medication process: ordering, dispensing, administering, and monitoring drugs. Nurses attempt to ensure that the Right drug is given in the Right dose at the Right interval via the Right route to the Right patient. Although nurses focus on providing error-free care, research into human factors teaches us that dedication, training, and vigilance are not enough to prevent errors in complex systems.3,4 Error prevention must be a multidisciplinary process, involving doctors, pharmacists, and nurses working as a team. The team must be backed up by robust healthcare delivery systems operating in a “culture of safety”, providing staff with a working environment that provides safeguards against human fallibility. …
Human Factors: A System View of Human, Technology and Organisation
  • H Alm
  • R Woltjer
Alm, H., Woltjer, R., 2010. Patient safety investigation through the lens of FRAM. In: de Waard, D. (Ed.), Human Factors: A System View of Human, Technology and Organisation. Maastricht, The Netherlands, pp. 153-165.
Safety I and safety II
  • E Hollnagel
Hollnagel, E., 2014. Safety I and safety II. Ashgate, Surrey.
From safety-I to safety-II: a white paper. Resilient Health Care Net
  • E Hollnagel
  • R Wears
  • J Braithwaite
Hollnagel, E., Wears, R., Braithwaite, J., 2015. From safety-I to safety-II: a white paper. Resilient Health Care Net.
To err is human: building a safer healthcare system
IOM, 1999. To err is human: building a safer healthcare system. Kohn, L.T., Corrigan, J. M., Donaldson, M.S. (Eds.). Institute of Medicine.
Introduction to the use of FRAM on the effectiveness assessment of a radiopharmaceutical dispatches process
  • A G A A Pereira
Pereira, A.G.A.A., 2013. Introduction to the use of FRAM on the effectiveness assessment of a radiopharmaceutical dispatches process. In: International Nuclear Atlantic Conference (INAC 2013). pp. 1-13.