by Professor Janet Anderson1 & Dr Satyan Chari2,3
1Professor of Human Factors, Department of Anaesthesiology and Perioperative Medicine, Monash University
2Adjunct fellow, Centre for Human Factors and Sociotechnical Systems
3Program Director – CEQ Bridge Labs, Clinical Excellence Queensland
The field of resilience engineering (RE) offers novel conceptual and practice tools to tackle long-standing quality, safety and performance issues in healthcare. However, healthcare improvement teams are often comprised of nurses and other healthcare professionals. Typically, they have an intimate understanding of the challenges facing frontline staff, but they often do not have training in safety science or human factors methods. They instead rely on targeted training programmes and accepted practices driven by policy makers and regulators. Compounding this, policy makers and regulators often require them to use methods such as root cause analysis in ways that do not foster deep understanding or effective improvement. For example, the requirement to complete recommendations within short timeframes and use restrictive report templates can mean it is not possible to analyse the problem deeply or frame effective solutions that require in-depth planning or approval for more resources, both of which take time (Anderson & Watt, 2020).
In my conversations with quality improvement teams, they often express frustration with these processes and their limitations, and are aware that there is a need for a different approach. Similarly, healthcare practitioners are usually positive about adopting Resilience Engineering (RE) because it speaks to their experiences of clinical work and acknowledges the challenges inherent in navigating a poorly designed complex system. It also provides a language to articulate why flexible adaptation is a core part of clinical work, to discuss decision-making and trade-offs in the context of system complexity, and to change the focus from individual behaviour to system design. Positive reactions to RE is not, however, sufficient to galvanise adoption into practice.
There are two main challenges in translating RE into healthcare improvement practice. First, it requires an understanding of system thinking and the ability to move beyond focusing on individual patients to think about the system as a whole. These ideas are difficult to grasp, especially as the theory and evidence are still evolving and there are multiple ideas which can be confusing and time-consuming to untangle. Second, there are few practical, easily understood methods for implementing RHC into healthcare practice (Anderson et al, 2016). The philosophical underpinnings of RE developed, as is the case in many fields, without considering translation into practice. Research in this area has focused on analysing the dynamics and interactions of complex systems such as emergency departments or hospitals. This has greatly increased our understanding of complexity but harnessing these insights for improvement is now essential, but not straightforward. The idea of understanding work-as-done is attractive, but how can that understanding be captured and used as a basis for improvement? Similarly, learning from what goes right sounds much more positive than focusing on errors and adverse events, but when most things go right how is it possible to learn from everything? In the vignette below, Dr Satyan Chari, a healthcare improvement expert and experienced RE practitioner shares some of his strategies for navigating potentially difficult conversations when introducing RE to clinical colleagues.
| The challenge of the solitary RE practitioner in healthcare settings – Satyan Chari. I periodically find myself in conversation with clinical colleagues on the threshold of undertaking improvement work. I am often that lone voice suggesting a different approach. This used to be a daunting exercise but as I have refined my approach, it has also become much easier. I find some strategies work better than others when it comes to creating the openness necessary to introduce RE into improvement work, even when speaking with teams without any knowledge of the field. Here are my three top tips (link to YouTube video) for getting a foot in the door more often and being more effective in translating your advocacy into meaningful forward movement. |
Translational tools are needed which have been designed for healthcare users specifically and which address their unique problems and challenges. Tools need to speak the language of healthcare quality improvement and be designed to fit with how quality improvement works in practice. Alongside such tools the key principles underpinning RE need to be articulated so that practitioners understand the foundations of the approach and have access to a summary of the state of the science. This is important for ensuring that RE does not share the fate of other tools and methods that have become simplified and distorted in practice. Methods often become corrupted in practice as they are adapted to fit common misunderstandings and shortened to yield quick results. RCA is an example of a method that does not support effective learning because of the way it has been implemented (Peerally et al, 2017).
The CARe-QI Handbook (Anderson & Ross, 2020) was written to fill this gap. Based on the work of the Centre for Applied Resilience in Healthcare (CARe), it describes how to apply RE to quality improvement, and is based on the empirical work of the Centre in emergency and older peoples’ care. The introductory section begins with an overview of the need for RE and articulates the core principles of the approach. The CARE model is then described which proposes that the need for adaptation is driven by misalignments between demand and capacity (Anderson et al, 2016). Five resilience activities that underpin system adaptive capacity are then explained – anticipating, responding, monitoring, coordinating and learning. These underpinning principles of misalignments, adaptations, and the five resilience activities, are crucial for implementing the method, so it is important that they are articulated clearly and using healthcare language. For example, what we have termed resilience activities have previously been called resilience potentials or systemic potentials (Hollnagel, 2017) which is arguably confusing and not the language usually used when describing a work. Clarity is essential for effective implementation.
The Handbook outlines a four-step method for quality improvement based on RE principles. The first step, project setup involves determining the suitability of the project for the approach. We recommend CARe-QI is particularly helpful for difficult and complex problems which cross system boundaries, and/or which may have been resistant to previous improvement efforts. The aims, scope and system boundaries, and project team are then considered. The second step is to capture work-as-done in the system of interest using a combination of methods such as observations of clinical work, document analysis, interviews with a range of staff and quantitative analysis of relevant data. These are then analysed in a third step to identify the resilience or adaptive capacity in the system, including common misalignments between demand and capacity, which adaptations are used in response and how effective they are, and how effectively the five resilience activities are carried out. This analytic step should reveal opportunities to improve quality through either reducing misalignments, improving adaptations or increasing the effectiveness of the resilience activities, or a combination of these. The final step is to co-design interventions to address the problems and challenges identified and to decide on outcome measures. For each step, there is guidance, tips for success and worksheets for documenting the outcomes of each step. The worksheets structure the problems faced at each step and provide a way to think about effective and defensible approaches.
This method provides guidance for designing interventions based on a deep understanding of the work system which must be completed before deciding on interventions. This is different to most QI methods that start with the intervention design. Analysing the work system from a resilience perspective provides a strong basis for understanding the challenges and adaptations that occur, and for tailoring interventions to the context to support workers as they try to make the system work. Interventions will focus on improving system design by reducing misalignments and reducing the need for adaptations, or by increasing adaptive capacity through the five resilience activities. This provides a strong evidence base for predicting how interventions will work in practice, and for sustaining interventions over time. Implementation and evaluation can follow established methods. The recommendation to evaluate both patient outcomes and resilience outcomes is also important. If the intervention is designed to target, for example, the activities of co-ordinating and responding, outcome measures should include measures of those activities because theory suggests that strengthening these activities will boost resilience and lead to better patient outcomes. Resilience outcome measures will typically be a mix of qualitative and quantitative indicators. For example, responding could be assessed using response time measures, patient and staff experience, adverse reactions due to delayed response, or a mixture of these.
The Handbook is freely available online and the hope is that it will be used by improvement teams and iterated on the basis of feedback from users. We are interested in supporting and coaching teams to use it so that we can gauge how it works in practice and how it can be expanded and improved.
References
Anderson, J. E., & Watt, A. J. (2020). Using Safety-II and resilient healthcare principles to learn from Never Events. International Journal for Quality in Health Care, 32(3), 196-203.
Anderson, J. E., Ross, A. J., Back, J., Duncan, M., Snell, P., Walsh, K., & Jaye, P. (2016). Implementing resilience engineering for healthcare quality improvement using the CARE model: a feasibility study protocol. Pilot and feasibility studies, 2(1), 1-9.
Anderson, J.E. & Ross, A.J. CARe-QI. A handbook for improving quality through resilient systems. (2020). Centre for Applied Resilience in Healthcare. Available from https://resiliencecentre.org.uk/care-qi-handbook/
Hollnagel, E. (2017). Safety-II in practice: developing the resilience potentials. Routledge.
Peerally, M. F., Carr, S., Waring, J., & Dixon-Woods, M. (2017). The problem with root cause analysis. BMJ quality & safety, 26(5), 417-422.